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BMJ Open is committed to open peer review. As part of this commitment we make the peer review history of every article we publish publicly available. When an article is published we post the peer reviewers’ comments and the authors’ responses online. We also post the versions of the paper that were used during peer review. These are the versions that the peer review comments apply to. The versions of the paper that follow are the versions that were submitted during the peer review process. They are not the versions of record or the final published versions. They should not be cited or distributed as the published version of this manuscript. BMJ Open is an open access journal and the full, final, typeset and author-corrected version of record of the manuscript is available on our site with no access controls, subscription charges or pay-per-view fees (http://bmjopen.bmj.com). If you have any questions on BMJ Open’s open peer review process please email
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A guided and unguided internet- and mobile-based intervention for chronic pain: Health economic evaluation
alongside a randomized controlled trial
Journal: BMJ Open
Manuscript ID bmjopen-2018-023390
Article Type: Research
Date Submitted by the Author: 06-Apr-2018
Complete List of Authors: Paganini, Sarah; Albert-Ludwigs-Universitat Freiburg, Department of Rehabilitation Psychology and Psychotherapy, Institute of Psychology Lin, Jiaxi; University of Freiburg, Department of Sports and Sport Science
Kaehlke, Fanny; Friedrich-Alexander University of Erlangen-Nuremberg, Department of Clinical Psychology and Psychotherapy Buntrock, Claudia; Friedrich-Alexander-Universitat Erlangen-Nurnberg, Clinical Psychology and Psychotherapy Leiding, Delia; RWTH Aachen University, Department of Psychiatry, Psychotherapy and Psychosomatics Ebert, David; Friedrich-Alexander University Erlangen Nuremberg, Clinical Psychology and Psychotherapy Baumeister, Harald; Universitat Ulm, Institut of Psychology and Education, Department of Clinical Psychology and Psychotherapy;
Keywords: Chronic pain, Internet-and mobile-based intervention, Health economic evaluation, Cost-effectiveness, Cost-utility
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A guided and unguided internet- and mobile-based intervention for chronic pain: Health
economic evaluation alongside a randomized controlled trial
S. Paganini 1a
, J. Lin2, F. Kählke
3, C. Buntrock
3, D. Leiding
4, D.D. Ebert
3, H. Baumeister
5
1Department of Rehabilitation Psychology and Psychotherapy, Institute of Psychology, University of
Freiburg, Germany, [email protected]
2Department of Sports and Sport Science, University of Freiburg, Germany, [email protected]
freiburg.de
3Department of Clinical Psychology and Psychotherapy, Friedrich-Alexander University of Erlangen-
Nuremberg, Germany, [email protected], [email protected], [email protected]
4Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany,
5Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education,
University of Ulm, Germany, [email protected]
a Corresponding author: Sarah Paganini, Department of Rehabilitation Psychology and
Psychotherapy, Institute of Psychology, University of Freiburg, Engelbergerstr. 41, D-79085 Freiburg,
Phone: ++49-761-203-3045, Fax: ++49-761-203-3040, Email: [email protected]
freiburg.de
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ABSTRACT
Objective: This study aims at evaluating the cost-effectiveness and cost-utility of a guided and
unguided internet-based intervention for chronic pain patients (ACTonPainguided/unguided) compared to a
waitlist control condition (WLC) and the comparative cost-effectiveness of ACTonPainguided/unguided.
Design: This is a health-economic evaluation alongside a three-armed randomized controlled trial.
Assessments were conducted at baseline, nine weeks after randomization and 6-month follow-up.
Setting: Participants were recruited through comprehensive online and offline strategies and in
collaboration with a German health insurance company.
Participants: All suitable participants (≥18 years, pain for at least six months, with at least Grade II in
the Chronic Pain Grade) filled out pre-treatment assessment. 302 individuals were randomly allocated
to one of the three groups (ACTonPainguided,ACTonPainunguided,WLC).
Interventions: ACTonPain consists of seven modules and is based on Acceptance and Commitment
Therapy. ACTonPainguided/unguided only differ in provision of human support.
Primary and secondary outcome measures: Main outcome of the cost-effectiveness analysis was
treatment response (in terms of pain interference). The outcome of the cost-utility analysis was
quality-adjusted life years (QALYs). Costs were measured from a societal perspective and were
related to treatment response and QALYs, respectively.
Results: If society is not willing to pay anything (€0) the probability of being cost-effective was 50%
for ACTonPainguided and 66% for ACTonPainunguided, respectively, for both treatment response and
QALY compared to WLC. The direct comparison revealed that from a willingness-to-pay of €2,188
(treatment response) and €27,221 (QALY), ACTonPainguided reaches higher probabilities of being cost-
effective than ACTonPainunguided.
Conclusions:
Findings indicate that ACTonPain might be a cost-effective alternative or adjunct to established pain
treatment. However, whether the intervention should be delivered guided or unguided depends on the
society´s willingness-to-pay and decision makers need to decide whether they focus on cost-
effectiveness or on patient health improvement at higher costs.
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Trial Registration: German Clinical Trial Registration: DRKS00006183,
URL:https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00006
183
Keywords: Chronic pain; internet- and mobile-based intervention; health economic evaluation; cost-
effectiveness; cost-utility
Strengths and limitations of this study
• This is the first study that evaluates the (comparative) cost-effectiveness of a guided and an
unguided internet-based intervention for chronic pain patients.
• In this study state-of-the-art statistical methods were applied, like seemingly unrelated
regression equations models or non-parametric bootstrapping techniques.
• Results should be interpreted cautiously, as the study was not powered to statistically test
health economic differences.
• As the costs and effects were evaluated over six months, no conclusions regarding the long-
term cost-effectiveness can be drawn.
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BACKGROUND
Chronic pain is highly prevalent [1–4] and associated with substantial decreases in quality of life [1, 5,
6] and high economic costs for society [3, 7–9]. Evidence supports psychological interventions as one
approach for effectively treating patients with chronic pain [10]. Treatment based on cognitive-
behavioral therapy (CBT) or third-wave therapies, like the Acceptance and Commitment Therapy
(ACT, a particular form of CBT) showed to be effective for chronic pain patients [11, 12] and could
show acceptable results concerning cost-effectiveness [13]. However, accessibility and availability of
treatment is often restricted and up to 40% of individuals with chronic pain do not receive adequate
pain management [1, 14]. Internet- and mobile- based interventions (IMIs) are an effective, acceptable
and feasible way for providing psychological interventions [15, 16]. IMIs for chronic pain have been
shown to effectively improve pain interference (standardized mean difference (SMD)=.4 [17],
SMD=−0.50 [18]).
IMIs can not only facilitate the access to psychological treatment, they also have the potential to
reduce treatment costs [19, 20], particularly by saving therapist resources. IMIs can be delivered as
guided or unguided self-help interventions, with both versions usually necessitating less therapist time
compared to traditional on-site therapies [21]. A relevant health care policy question is what amount of
professional human guidance is necessary in order to improve patients´ health, with guided IMIs being
seemingly more effective than unguided IMIs [21, 22]. However, as unguided IMIs can be delivered at
lower costs per participant, they might as well be an attractive option particularly given their high
scalability on a population level.
To the best of our knowledge, no randomized controlled trial (RCT) has investigated the
(comparative) cost-effectiveness of a guided and unguided IMI for chronic pain. However, Boer and
colleagues found that an IMI for chronic pain was cost-effective compared to a face-to-face group
intervention (concerning a one-point-improvement in a pain catastrophizing scale) [23]. Lin and
colleagues recently finalized a three arm RCT comparing a guided and unguided version of an
Acceptance and Commitment Therapy based IMI for chronic pain (ACTonPain) against a waitlist
control group [24, 25]. Compared to the waitlist control condition, ACTonPainguided showed
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significantly lower pain interference at post-treatment and 6-month post-baseline (d=0.58).
Differences between ACTonPainunguided and the control group and between both ACTonPain-groups
were not statistically significant [25].
The present paper provides the cost-effectiveness and cost-utility of ACTonPainguided/unguided compared
to the waitlist control condition as well as the comparative cost-effectiveness of
ACTonPainguided/unguided.
METHODS
Study design and sample
This health-economic evaluation was conducted with a 6-month time horizon from the societal
perspective alongside a three-armed RCT to investigate the cost-effectiveness and cost-utility of
ACTonPain. Full details of the trial design can be found in the study protocol and the main outcome
paper of this trial [24, 25]. The economic evaluation was conducted and reported in agreement with
the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement [26] and the
International Society For Pharmacoeconomics and Outcomes Research (ISPOR) guidelines [27].
The study has been registered in the German Clinical Trial Register (DRKS00006183) and was
approved by the ethics committee of the University of Freiburg (reference: 387/14). In total, 302
participants were recruited from 10/2014 until 08/2015 in German pain clinics, largescale
organizations for chronic pain (e.g. self-help groups), on websites and with assistance of a German
health insurance company. Inclusion criteria were 1) age 18 years or older, 2) chronic pain for at least
six months, with 3) considerable intensity (=at least Grade II in the Chronic Pain Grade [28]), 4) being
medically suitable for participation in a chronic pain IMI, 5) sufficient knowledge of the German
language, 6) sufficient computer and internet literacy, and 7) having internet access. Exclusion criteria
were 1) cancer-related pain, 2) ongoing or planned psychological pain intervention within the
forthcoming three months and 3) elevated risk of suicide.
Randomization
All eligible participants who provided informed consent were asked to fill out the baseline assessment
and were randomly allocated to one of the three conditions ACTonPainguided/unguided and waitlist.
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Permuted block randomization with variable block sizes (6, 9, 12) was performed by an independent
researcher not otherwise involved in the study using an automated, web-based randomization program.
Interventions
ACTonPain is a German adaption of an IMI by Buhrman and colleagues [29] for individuals suffering
from chronic pain. The intervention is based on ACT and consists of seven modules, which include
information, metaphors, assignments, and mindfulness exercises. Both treatment conditions differ only
in the provision of guidance. Participants were advised to work on one module every week (~60
minutes). In both intervention groups, participants had the option to receive daily automated text
messages that repeated content, reminded and motivated participants.
In ACTonPainguided trained and supervised eCoaches (psychologists) provided written feedback for
each module, which aimed at increasing participants' motivation and adherence. The total time of an
eCoach spent per participant was approximately 1.75 hours. Participants in the waitlist condition
received the offer to use ACTonPainunguided after the last follow-up assessment. Participants of all three
trial arms had unrestricted access to care-as-usual.
Outcome measures
Assessment took place at baseline (T0), post-treatment (T1; nine weeks after randomisation) and 6-
month follow-up (T2; six months after randomization). Outcomes were assessed by means of an
online self-report assessment using a secured internet-based platform (AES, 256-bit encrypted).
Treatment response
Main clinical outcome in the cost-effectiveness analysis was treatment response. According to the
Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT)
recommendations clinically important changes were identified with a combination of a distribution-
based approach (Pain Interference Scale of the Multidimensional Pain Inventory MPI [30, 31]) and an
anchor-based approach (Patient Global Impression of Change scale PGIC [32]) [33]. First, participants
with a change of 0.6 points (based on the scale’s standard deviation) on the Pain Interference Scale of
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the MPI (range of the scale:0-6) were identified as having minimal clinically important changes [33].
Second, participants were identified, that rated their global improvement in the PGIC [32] as
“minimally, much or very much improved”. Participants who fulfilled both criteria were classified as
having achieved a clinically important change [33], defined as “treatment response”.
Quality-adjusted life years
The clinical outcome in the cost-utility analysis was quality-adjusted life years (QALYs) based on the
AQoL-8D [34] and the EQ5D-3L [35]. Utility scores are a preference-based measure of quality of life
that is normed by the value 1 meaning complete health and 0 meaning death [36].
The AQoL-8D comprises 35 items, which load on three physical (independent living, pain, senses)
and five psycho-social (mental health, happiness, coping, relationships, self-worth) dimensions [34].
The utility scores are scaled by SPSS algorithm for AQoL-8D utility model [34]. The AQoL-8D has
been shown as a reliable and valid instrument, suitable when psychosocial elements of health are the
focus of research [34].
The EQ-5D-3L consists of five dimensions (mobility, self-care, usual activities, pain/discomfort, and
anxiety/depression), each of which is rated as causing ‘no’, ‘some’ or ‘extreme problems,’ and is a
well validated instrument [35, 37, 38]. Theoretically, the EQ-5D-3L generates 243 different health
states. Utility scores were calculated using the UK tariffs [39].
The AQoL-8D covers more dimensions that might be affected by chronic pain and shows a higher
sensitivity to mental health-related quality of life dimensions [40] compared to the EQ5D-3L.
Subsequently, and different to our protocol, this instrument was chosen for the main analyses[24].
QALY health gains for the 6-months period were estimated by calculating the area under the curve
(AUC) of linearly interpolated AQoL-8D and EQ-5D-3L utility scores [41].
Resource use and costing
The Trimbos and iMTA questionnaire for costs associated with psychiatric illness (TiC-P) [42, 43]
was adapted to the German health care system and used to assess the direct and indirect costs of the
past three month at T0 and T2. Costs were expressed in Euros (€) for the reference year 2015 (index
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factor 1.003 and 1.01 for outpatient medical service, respectively) referring to the German consumer
price index [44] (list of unit cost prices see Table 1).
Table 1: List of unit cost prices
Sector Unit Category 2015 (in Euro)
Outp
atie
nt
med
ical
ser
vic
e /
ou
tpat
ien
t se
ctor
Euro/contact
Physician
Gynecologist
Orthopedist Specialists for internal medicine
Ophthalmologist
Dermatologist
ETN specialist
Surgeon
Urologist Neurologist
Psychotherapist
Dentist
20.81
31.62
25.82 64.25
36.96
19.58
28.12
44.59
25.20 47.02
79.42
55.24
remedies Logopedics / speech therapy
Physiotherapy
Ergotherapy / occupational therapy
Podiatry / podology
Mean remedies
41.02
17.50
39.45
29.13
31.77
hospitals Euro/day
Completely stationary normal ward
Completely stationary intensive care
Completely stationary psychiatry Semi-stationary general hospital
Semi-stationary psychiatry
648.11
1,424.60
348.26 421.27
226.37
rehabilitation Euro/day Outpatient
Inpatient
49.43
138.19
opportunitiy costs Euro/hour
opportunity costs (free time)
opportunity costs (work) substitution costs for informal care
21.77
31.89 18.97
Note: Prices for outpatient medical service/outpatient sector were calculated fort the year 2013; all other prices
for the year
201444, 45
and adjusted by the German consumer price index for 201543
. ETN specialist, Ear, nose, and throat
specialist.
Direct medical costs
Healthcare costs (e.g. out-and inpatient care) were calculated according to the German guideline of
Bock and colleagues [45, 46]. The costs of therapeutic appliances (that were not listed in Bock and
colleagues [45, 46]) and medication were obtained from the Lauer-Taxe [47].
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Patient and family costs
Self-reported out-of-pocket expenses and direct non-medical costs (travel expenses, opportunity costs,
domestic help) were assessed. Participants reported the cost of travelling by bus or taxi. If not stated,
each kilometer was valued at €0.30. Opportunity costs (i.e.,time spent at the practitioners waiting
room) were estimated at €21.77 per hour. Costs of informal care were valued using a shadow price of
€18.97 per hour [45].
Indirect costs
Indirect costs included productivity losses caused by absenteeism and presenteeism. Absenteeism
costs were calculated according to the human capital approach [48]. Self-reported lost work days were
multiplied by the corresponding gross average of participants’ income per day. To calculate
presenteeism costs, participants reported the number of days of reduced efficiency at work. These days
were weighted by an inefficiency score. Productivity losses from unpaid work (i.e. domestic help from
family members) were valued using a shadow price of €18.97 per hour [45].
Intervention costs
Intervention costs of ACTonPainguided (€299) and ACTonPainunguided (€69) were based on actual
market prices for (un)guided interventions with a similar amount of modules that contain all costs for
developing and hosting the intervention (https://geton-institut.de/).
Statistical analysis
This study was not powered to statistically test differences in health economic outcomes. Therefore,
we took a probabilistic decision-making approach for health-economic inferences [49], that aims at
informing decision makers on probabilities rather than statistical significance. There was no need to
discount costs or outcomes as the time frame for the study was six months.
All analyses were conducted according to the intention-to-treat principle. All participants completed
T0. Missing clinical outcome data was imputed using the expectation maximization algorithm in
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Statistical Package for the Social Sciences (SPSS, version 20). Analyses of clinical outcomes were
conducted and reported elsewhere [25] in accordance with the CONSORT 2010 Statement[50].
Missing cost data was imputed using the regression imputation procedure in Stata version 13 [51].
Predictors of cost data and dropout were identified by logistic regression analysis and were used to
obtain the most likely values of the missing cost data. At baseline, AQoL-utilities were similar
between groups (ACTonPainguided:M=0.496, SD=0.16; ACTonPainunguided: M=0.485, SD=0.17; waitlist:
M=0.463, SD=0.15). Therefore, no baseline adjustments were made when calculating QALYs.
We tested group differences in treatment response using the chi-squared test and the Kruskall-Wallis
test for QALYs both followed by post-hoc comparisons (Bonferroni and Dunn´s test, respectively).
In the cost-effectiveness analyses, the outcome estimate is the incremental cost-effectiveness ratio
(ICER), where incremental costs over the 6-month period are divided by incremental effects
(treatment response or QALYs): ICER=(CostsIG–CostsCG)/(EffectsIG–EffectsCG) subscripted with IG
for the two intervention groups and CG for the comparison groups. Different to the protocol [24],
ICERs are reported for a 6-month horizon (baseline data; T0 and 6-month follow-up; T2) and not
based on pre-post (T0 and post-treatment; T1). As participants are asked for their health care
utilization during the last three months, the TiC-P can only be evaluated appropriately at T0 and T2 (as
T1 assessments are conducted nine weeks after randomization).
Non-parametric bootstrapping by resampling patient-level data with 5,000 replications was used to
take into account the sampling uncertainty of the ICER estimates. Seemingly unrelated regression
equations models were bootstrapped to allow for correlated residuals of the cost and effect equations.
Bootstrapping was used to obtain 95% confidence intervals for the ICERs based on the percentile
method, since parametric techniques are inappropriate for use on skewed variables and ratios [49].
The bootstrapped ICERs were plotted on a cost-effectiveness plane. In addition, a cost-effectiveness
acceptability curve was graphed to assess the probability that the intervention is cost-effective relative
to the comparator condition given varying willingness-to-pay (WTP) ceilings. In order to increase
readability of the direct comparison ACTonPainguided vs. ACTonPainunguided the inverse cost-
effectiveness acceptability curve (ACTonPainunguided vs. ACTonPainguided) was additionally plotted. All
analyses were performed using Stata version 13 [51].
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Sensitivity analysis
We tested the robustness of the outcomes of the main analysis in a sensitivity analysis. Therefore we
used the EQ-5D-3L as a widely used instrument for calculating QALYs.
Patient and public involvement
No patients or public were involved in developing the research question or the outcome measures, nor
were they involved in developing plans for design or implementation of the study. The burden of the
interventions on participants was not assessed, but the satisfaction with the intervention. The results of
the research will be disseminated to those study participants who wished to be notified.
RESULTS
Sample characteristics
The overall sample size was 302. Due to missing assessments the dropout rate was 25.8% at 6-month
follow-up (ACTonPainguided:33/100; ACTonPainunguided:35/101; waitlist:10/101). At 6-month follow
up, dropout rates differed significantly between groups (χ2(2)=20.17, p<.001). Pairwise comparison
revealed significant differences for ACTonPainguided vs. waitlist (t(1)=-3.85, p<.001) and
ACTonPainunguided vs. waitlist (t(1)=-4.14, p<.001). Study dropout was not associated with baseline
pain interference or socio-demographic factors.
The average participant was female, 52 years of age, with an above average level of education,
employed and was already treated for chronic pain. Detailed participants’ characteristics and the
CONSORT flowchart have already been reported elsewhere [25].
Outcomes
Table 2 shows treatment response and QALY outcomes as well as group differences. At 6-month
follow-up, treatment response differed significantly between groups (ACTonPainguided: 44/100;
ACTonPainunguided: 28/101; waitlist: 16/101). Pairwise comparison revealed significant differences for
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ACTonPainguided vs. waitlist and ACTonPainguided vs. ACTonPainunguided but not for ACTonPainunguided
vs. waitlist. Between-group differences in AQoL-8D QALY gains were statistically significant.
Pairwise comparison revealed significant differences only for ACTonPainguided vs. waitlist. Incremental
EQ5D-3L QALY gains did not differ significantly between study groups.
Table 2. Treatment response and quality-adjusted life-year (QALY) outcomes and group differences at
6-month follow up.
ACTonPain guided
(n = 100)
ACTonPain unguided
(n = 101)
WLC group
(n = 101)
Test statistic
Mean (SD) Mean (SD) Mean (SD) χ2 (df=2) Post-hoc test
c:
p
Treatment response
(pain interference)
0.44 (0.5)
0.28 (0.45)
0.16 (0.37)
19.44 a
<001
ACTonPain guided vs. WLC group t(1)=4.52 <.001
ACTonPain unguided vs. WLC group t(1)=1.91 .17
ACTonPain guided vs. unguided t(1)=2.61 .03
QALY
AQoL-8D
0.28 (0.08)
0.27 (0.09)
0.24 (0.08)
9.45 b
.009
ACTonPain guided vs. WLC group Z=-3.07 .003
ACTonPain unguided vs. WLC group Z=-1.61 .16
ACTonPain guided vs. unguided Z=-1.47 .21
EQ5D-3L 0.27 (0.12) 0.25 (0.12) 0.25 (0.13) 2.17 b .34
WLC group, waitlist control group; SD, standard deviation; df, degrees of freedom; QALY, quality-adjusted life-
year a Chi-squared test
b Kruskall-Wallis H test
c Post-hoc test for treatment response: Bonferroni pairwise comparison; Post-hoc test for QALY: Dunn´s test
Costs
At baseline, mean total costs were €3,233 in ACTonPainguided, €3,724 in ACTonPainunguided and €3,570
in the waitlist group. The 6-month accumulated per-participants costs by study condition are presented
in Table 3. ACTonPainguided showed the highest mean total costs (€6,945), followed by the waitlist
group (€6,908) and ACTonPainunguided (€6,560). Mean direct costs were the highest in the guided
group, followed by the unguided group and waitlist. The opposite order was found for the indirect
costs. Medication, domestic help and opportunity costs were major cost drivers. Productivity losses
produced the highest cost differences between the intervention groups and waitlist of -€871
(ACTonPainguided vs. waitlist) and -€721 (ACTonPainunguided vs. waitlist).
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Table 3. 6-month accumulated per-participants costs (in €) by condition (based on intention-to-treat
sample, N = 302).
ACTonPain guided
(n = 100)
ACTonPain unguided
(n = 101)
WLC group
(n = 101)
Incremental costs
Difference, €
Mean, €
(SD)
Mean, €
(SD)
Mean
, €
(SD)
ACTon
Pain guided
vs.
WLC
ACTon
Pain unguided
vs.
WLC
ACTon
Pain guided
vs. unguided
Intervention 299 (-) 69 (-) 0 (-) 299 69 230
Direct medical costs
Health care costs
Medical specialist 576 (478) 511 (381) 511 (382) 65 0 65
Mental health care 212 (431) 181 (397) 258 (455) -46 -77 31
Other medical
specialist a
369 (515) 357 (435) 406 (576) -37 -49 12
In-patient care
(hospital)
198 (479) 173 (369) 141 (420) 57 32 25
Day care 147 (687) 122 (381) 306 (1,584) -159 -184 25
Rehabilitation 190 (794) 134 (507) 191 (773) -1 -57 56
Medication 1,092 (2,748) 784 (1,438) 660 (1,638) 432 124 308
Therapeutic appliances 65 (139) 86 (222) 46 (96) 19 40 -21
Direct non-medical costs
Patient and family costs
Travel 131 (229) 105 (150) 101 (100) 30 4 26
Domestic help 1,297 (4,064) 1,147 (1,936) 840 (1,490) 457 307 150
Opportunity costs b 1,553 (1,965) 1,925 (3,251) 1,759 (3,116) -206 166 -372
Indirect costs
Productivity losses
Absenteeism 517 (1,647) 647 (1,979) 1,133 (3,333) -616 -486 -130
Presenteeism 300 (740) 320 (774) 555 (1,360) -255 -235 -20
Total direct costs 5,829 (7,129) 5,525 (4,959) 5,220 (5,133) 611 306 305
Total indirect costs 817 (1,978) 966 (2,283) 1,688 (3,735) -871 -721 -150
Total societal costs 6,945 (7,327) 6,560 (5,549) 6,908 (6,279) 39 -346 385
WLC group, waitlist control group a i.e. physiotherapist, occupational therapist
b i.e. for waiting time before treatment
Health-economic evaluation
Table 4 shows the incremental costs, effects and cost-effectiveness ratios for the main analysis and the
sensitivity analysis.
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Table 4. Results of the main and sensitivity analyses (based on 5,000 bootstrap simulations).
Analysis
ACTonPain guided vs.
WLC group
Incremental
costs, €
(95% CI)
Incremental
effects
(95% CI)
Mean
ICER
(95% CI)
Distribution over the
ICER plane
NE NW SE SW
Cost-effectiveness,
treatment response
(MPID and PGIC)
6
(-916-953)
0.14
(0.08-0.2)
171
(-6,671-8,260)
50% - 50% -
Cost-utility, AQoL QALYs
6
(-916-953)
0.018
(-0.007-
0.029)
7,514
(-49,275-
88,521)
50%
-
50%
-
Sensitivity analysis
EQ5D QALYs 6
(-916-953)
0.01
(-0.006-
0.027)
-8,116 a
42% 8% 47% 3%
Analysis
ACTonPain unguided vs.
WLC group
Incremental
costs, €
(95% CI)
Incremental
effects
(95% CI)
Mean
ICER
(95% CI)
Distribution over the
ICER plane
NE NW SE SW
Cost-effectiveness,
treatment response
(MPID and PGIC)
-352
(-1,968-
1,272)
0.12
(0.006-
0.232)
-3,320
(-82,925-
29,821)
32% 1% 66% 1%
Cost-utility, AQoL QALYs
-352
(-1,968-
1,272)
0.023
(-0.0002-
0.046)
-11,689 a
31%
2%
66%
1%
Sensitivity analysis
EQ5D QALYs -352
(-1,968-
1,272)
0.001
(-0.032-
0.035)
46,304 a
11% 22% 41% 25%
Analysis
ACTonPain guided vs.
ACTonPain unguided
Incremental
costs, €
(95% CI)
Incremental
effects
(95% CI)
Mean
ICER
(95% CI)
Distribution over the
ICER plane
NE NW SE SW
Cost-effectiveness,
treatment response
(MPID and PGIC)
388
(-1,416-
2,185)
0.164
(0.034-0.29)
2,949
(-11,097-
25,276)
65% - 35% -
Cost-utility, AQoL QALYs
388
(-1,416-
2,185)
0.013
(-0.011-
0.037)
22,290 a
54%
11%
32%
3%
Sensitivity analysis
EQ5D QALYs 388
(-1,416-
2,158)
0.02
(-0.014-
0.053)
1,734 a
54% 11% 33% 2%
WLC group, waitlist control group; 95% CI, 95% confidence interval; EQ-5D QALYs, Quality-adjusted life
years based on EuroQol; ICER, incremental cost-effectiveness ratio; NE, northeast quadrant; NW, northwest
quadrant; SE, southeast quadrant; SW, southwest quadrant. a A dependably accurate 95% confidence interval for this distribution cannot be defined because there is no line
through the origin that excludes α/2 of the distribution[52].
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Cost-effectiveness
The cost-effectiveness planes and acceptability curves, representing the 5,000 bootstrap replications,
are shown in Figure 1(a,b,c) and 2(a,b). ACTonPainguided showed the same and ACTonPainunguided a
higher potential of being cost-effective compared to waitlist at a WTP of €0 (ACTonPainguided 50%,
ACTonPainunguided 66%). The probability of ACTonPainguided being more cost-effective compared to
waitlist increased up to 70% at a WTP of €1,738 and to 95% at a WTP of €6,490 for an additional
treatment response, and for ACTonPainunguided to 70% at a WTP of €660 and to 95% at a WTP of
€13,460.
The probability that ACTonPainguided is more cost-effective than ACTonPainunguided was 35% at a WTP
of €0 for an additional treatment response. When society’s WTP increases up to €5,535 or €17,170
this probability rises to 70% or 95%, respectively. The break even point (where ACTonPainguided and
ACTonPainunguided have the same possibility of being cost-effective at same costs) is at €2,188 (see
Figure 2b).
- Figure 1-
- Figure 2-
Cost-utility
Cost-effectiveness planes and acceptability curves that refer to cost-utility are shown in figure 1(d,e,f)
and 2(c,d). ACTonPainguided showed the same and ACTonPainunguided a higher potential of being cost-
effective compared to waitlist at a WTP of €0 (50% and 66%, respectively). The interventions’
probability of being more cost-effective compared to waitlist increased up to 70% and to 95% at a
WTP of €14,680 and €62,580, respectively, in ACTonPainguided and €3,920 (70%) and €117,000 (95%)
in ACTonPainunguided for one additional QALY. The probability that ACTonPainguided is more cost-
effective than ACTonPainunguided was 32% at a WTP of €0 for one additional QALY. When society’s
WTP increases up to €92,400 this probability rises to 70% and stagnates on this level. The break-even
point is at €27,221 (see Figure 2d).
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Sensitivity analysis
Compared to the AQoL-8D, using the EQ-5D-3L resulted in smaller incremental QALY gains for
ACTonPainguided and ACTonPainunguided vs. waitlist, but still in favor of the intervention group,
respectively. QALY gains were higher and in favor of ACTonPainguided vs. ACTonPainunguided
compared to the AQoL-8D QALY gains.
DISCUSSION
Whether an intervention can be considered as cost-effective or not strongly depends on the society's
willingness-to-pay (WTP). At first glance, ACTonPainunguided seems to be more cost-effective and
shows the lower incremental societal cost than ACTonPainguided when compared to waitlist. The
probability of being cost-effective at a WTP of €0 compared to waitlist is higher in ACTonPainunguided,
for both, treatment response and QALYs gained (66%) than in ACTonPainguided (50%).
However, when increasing the WTP threshold for a treatment response, the probability of being cost-
effective rises more for ACTonPainguided than for ACTonPainunguided. The direct comparison of
ACTonPainguided/unguided shows the same pattern with ACTonPainguided exceeding ACTonPainunguided
given a WTP threshold higher than €2,188 and €27,221 for treatment response and QALY,
respectively.
The results of ACTonPain being cost-effective are in line with a recent study and a review on IMIs
for depression [23, 53]. The guided IMI for chronic pain of Boer and colleagues revealed an ICER of
40 (defined as cost savings of €40) for an one-point improvement in a pain catastrophizing scale
compared to a face-to-face group intervention [23]. QALYs where not reported. ACTonPainguided
reached higher ICERs for the clinical outcome pain interference (171 compared to waitlist group and
2,949 compared to ACTonPainunguided). However, generic measures, like QALYs should be used to
compare between studies [48]. In the systematic review, IMIs that were classified as cost-effective
were all guided and showed probabilities of being cost-effective between 28% and 49% at a WTP of
€0 for a QALY gained (50-66% in ACTonPain). Thus, integrating psychological e-health approaches
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in pain management programs might even be more promising from an economical point of view when
compared to the well-established area of depression e-health care. The higher direct costs over a 6-
month period in both intervention groups compared to waitlist might be explained by higher or stable
health care utilization similar to findings in a previous study on the costs of established depression
treatments [54]. However, research indicates that indirect rather than direct costs represent the
majority of overall costs [55, 56], where ACTonPain seemingly has its core advantage. Mean indirect
costs over the 6-month period were almost half as high in the intervention groups compared to waitlist,
regarding both absenteeism and presenteeism.
Next to the question of whether ACTonPain is cost-effective with a “highly probable” and whether it
should rather be provided guided or unguided with an “it depends on the WTP” as answers, it would
be of interest how ACTonPain performs compared to established medical, psychological,
physiotherapeutical, and surgical treatments that result in enormous direct costs [57–60]. However,
surprisingly little is known about the cost-effectiveness of these established pain treatments. In two
reviews it was highlighted, that interdisciplinary pain rehabilitation programs are more cost-effective
or produce lower costs than interventions such as surgery and conservative care [61, 62].For
individuals with low back pain it was concluded that interdisciplinary rehabilitation, exercise,
acupuncture, spinal manipulation and CBT are potentially cost-effective [63]. A further systematic
review focused on economic evaluations of third-wave CBT therapies (including ACT), were available
ICERs ranged from -€19,300 (National Health Service perspective, converted into Euro [64]) to
€56,637 (societal perspective) per QALY gained [13]. The three ICERs based on the AQoL-8D in this
study were €7,514, -€11,689 and €22,290 per QALY gained. Thus, it seems safe to argue that
ACTonPain, as an example of an innovative IMI for the treatment of chronic pain, is effective [25] and
can be an cost-effective intervention. A comparison across treatment approaches for chronic pain,
however, cannot be provided as the evidence base for the cost-effectiveness of established pain
treatments is rather weak and the comparability of results across studies is limited due to very
heterogeneous methods across trials [65].
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Limitations
First, when interpreting the results, it has to be considered that the study was not powered to
statistically test health economic differences. Second, the costs and effects were evaluated over six
months. Therefore, no conclusions regarding the long-term cost-effectiveness can be drawn. Finally,
costs were assessed via self-report. However, as the questionnaire used in this study is a valid
instrument to recall periods up to 3 months [66], the impact of this bias on results is limited.
Implications and future research
For patients with chronic pain, IMIs might become an important alternative to established
interventions. IMIs can expand treatment options for people, whose physical impairment or location
makes access to relevant care difficult [19]. Findings from this health economic evaluation study show
that both the guided and unguided version of ACTonPain have the potential of being cost-effective.
Thus, the decision whether to choose the guided or unguided version is a public health issue and
strongly depends on whether to mainly focus on patients´ health or societies´ resources. If the focus is
set on health improvement, the guided version should be preferred. Under economic aspects
ACTonPainunguided might be the preferred intervention. Future research should examine long-term
follow-up studies and further evaluate the (comparative) cost-effectiveness of different guidance
formats of IMIs, particularly of ACTonPain, and established pain treatments. Moreover, future studies
should examine ACTonPain as integrated part of multi-component pain programs and aim to
dismantle the ingredients that are effective and cost-effective in those complex approaches.
DECLARATIONS
Funding
This research received no specific grant from any funding agency in the public, commercial or not-for-
profit sectors. The article processing charge was funded by the German Research Foundation (DFG)
and the Albert Ludwigs University Freiburg in the funding programme Open Access Publishing.
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Competing interests
Two of the authors of the manuscript were involved in the development of ACTonPain (JL and HB).
HB and DDE are consultants for several stakeholders (insurance companies, ministries, psychotherapy
chambers, companies). DDE is part of the GET.ON Institut GmbH, which aims at implementing
evidence-based internet- and mobile based interventions into routine care. SP, CB, FK and DL declare
that they have no competing interests.
Data sharing statement
The datasets used and/or analyzed during the current study are available from the corresponding
author on reasonable request.
Authors’ contributions
JL and HB initiated the randomized control trial for this health economic evaluation. SP, FK, CB, DL
and DDE contributed to the design of this health economic evaluation. SP, DL, FK and CB
contributed to the data analysis. SP had full access to all the data in the study and had responsibility
for the decision to submit for publication. SP wrote the draft of the manuscript. All authors contributed
to the further writing and approved the final version of the manuscript.
Acknowledgements
We would like to thank Yannik Terhorst and Nelli Hirschauer for their assistance in data processing.
Figure Legends
Figure 1. Cost-effectiveness planes of all group comparisons based on 5,000 replicates of the
incremental cost-effectiveness ratio using mean differences in costs from a societal perspective and
mean incremental effects (treatment response: a, b, c; QALYs: d, e, f)
Figure 2. Cost-effectiveness acceptability curves of all group comparisons based on 5,000 replicates
of the incremental cost-effectiveness ratio using mean differences in costs from a societal
perspective and mean incremental effects (treatment response: a, b; QALYs: c, d). For the
comparison of ACTonPain guided vs. ACTonPain unguided the inverse function (ACTonPain
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unguided vs. ACTonPain guided) was included.
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Figure 1. Cost-effectiveness planes of all group comparisons based on 5,000 replicates of the incremental cost-effectiveness ratio using mean differences in costs from a societal perspective and mean incremental
effects (treatment response: a, b, c; QALYs: d, e, f)
363x190mm (150 x 150 DPI)
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Figure 2. Cost-effectiveness acceptability curves of all group comparisons based on 5,000 replicates of the incremental cost-effectiveness ratio using mean differences in costs from a societal perspective and mean incremental effects (treatment response: a, b; QALYs: c, d). For the comparison of ACTonPain guided vs.
ACTonPain unguided the inverse function (ACTonPain unguided vs. ACTonPain guided) was included.
296x195mm (150 x 150 DPI)
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Additional file 1 – CHEERS checklist
Section/item Item
No
Recommendation Reported on page
No
Title and abstract
Title 1 Identify the study as an economic evaluation or
use more specific terms such as “cost-
effectiveness analysis”, and describe the
interventions compared.
Page 1
Abstract 2 Provide a structured summary of objectives,
perspective, setting, methods (including study
design and inputs), results (including base case
and uncertainty analyses), and conclusions.
Page 2 and 3 (the
sensitivity analysis
is not mentioned
in the abstract
due to limited
words)
Introduction
Background and
objectives
3 Provide an explicit statement of the broader
context for the study.
Present the study question and its relevance for
health policy or practice decisions.
Page 4 and 5
Methods
Target population
and subgroups
4 Describe characteristics of the base case
population and subgroups analysed, including
why they were chosen.
Page 5
Setting and location 5 State relevant aspects of the system(s) in which
the decision(s) need(s) to be made.
Page 5
Study perspective 6 Describe the perspective of the study and relate
this to the costs being evaluated.
Page 5, 8 and 9
Comparators 7 Describe the interventions or strategies being
compared and state why they were chosen.
Page 6
Time horizon 8 State the time horizon(s) over which costs and
consequences are being evaluated and say why
appropriate.
Page 6 and 7
Discount rate 9 Report the choice of discount rate(s) used for
costs and outcomes and say why appropriate.
Page 9
Choice of health
outcomes
10 Describe what outcomes were used as the
measure(s) of benefit in the evaluation and their
relevance for the type of analysis performed.
Page 6 and 7
Measurement of
effectiveness
11a Single study-based estimates: Describe fully the
design features of the single effectiveness study
and why the single study was a sufficient source
of clinical effectiveness data.
Page 4 and 5
11b Synthesis-based estimates: Describe fully the
methods used for identification of included
studies and synthesis of clinical effectiveness
data.
N/A
Measurement and
valuation of
preference based
outcomes
12 If applicable, describe the population and
methods used to elicit preferences for outcomes.
Page 7
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Section/item Item
No
Recommendation Reported on page
No
Estimating costs and
resources
13a Single study-based economic evaluation:
Describe approaches used to estimate resource
use associated with the alternative
interventions. Describe primary or secondary
research methods for valuing each resource item
in terms of its unit cost. Describe any
adjustments made to approximate to
opportunity costs.
Page 7 and 8,
Table 1
13b Model-based economic evaluation: Describe
approaches and data sources used to estimate
resource use associated with model health
states. Describe primary or secondary research
methods for valuing each resource item in terms
of its unit cost. Describe any adjustments made
to approximate to opportunity costs.
N/A
Currency, price date
and conversion
14 Report the dates of the estimated resource
quantities and unit costs. Describe methods for
adjusting estimated unit costs to the year of
reported costs if necessary. Describe methods for
converting costs into a common currency base
and the exchange rate.
Page 7 and 8
Choice of model 15 Describe and give reasons for the specific type of
decision-analytical model used. Providing a figure
to show model structure is strongly
recommended.
N/A
Assumptions 16 Describe all structural or other assumptions
underpinning the decision-analytical model.
N/A
Analytical methods 17 Describe all analytical methods supporting the
evaluation. This could include methods for
dealing with skewed, missing, or censored data;
extrapolation methods; methods for pooling
data; approaches to validate or make
adjustments (such as half cycle corrections) to a
model; and methods for handling population
heterogeneity and uncertainty.
Page 9, 10 and 11
Results
Study parameters 18 Report the values, ranges, references, and, if
used, probability distributions for all parameters.
Report reasons or sources for distributions used
to represent uncertainty where appropriate.
Providing a table to show the input values is
strongly recommended.
Page 11-16, Table
2 and 4
Incremental costs
and outcomes
19 For each intervention, report mean values for the
main categories of estimated costs and outcomes
of interest, as well as mean differences between
the comparator groups. If applicable, report
incremental cost-effectiveness ratios.
Page 12 and 13;
Table 3
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Section/item Item
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Recommendation Reported on page
No
Characterising
uncertainty
20a Single study-based economic evaluation:
Describe the effects of sampling uncertainty for
the estimated incremental cost and
incremental effectiveness parameters, together
with the impact of methodological assumptions
(such as discount rate, study
perspective).
Page 15 and
Figure 1
20b Model-based economic evaluation: Describe the
effects on the results of uncertainty for all input
parameters, and uncertainty related to the
structure of the model and assumptions.
N/A
Characterising
heterogeneity
21 If applicable, report differences in costs,
outcomes, or cost-effectiveness that can be
explained by variations between subgroups of
patients with different baseline characteristics or
other observed variability in effects that are not
reducible by more information.
N/A
Discussion
Study findings,
limitations,
generalisability, and
current knowledge
22 Summarise key study findings and describe how
they support the conclusions reached. Discuss
limitations and the generalisability of the findings
and how the findings fit with current knowledge.
Page 16-18
Other
Source of funding 23 Describe how the study was funded and the role
of the funder in the identification, design,
conduct, and reporting of the analysis. Describe
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Conflicts of interest 24 Describe any potential for conflict of interest of
study
contributors in accordance with journal policy. In
the absence of a journal policy, we recommend
authors comply with International Committee of
Medical Journal Editors recommendations.
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N/A, Not applicable
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For peer review onlyA guided and unguided internet- and mobile-based
intervention for chronic pain: Health economic evaluation alongside a randomized controlled trial
Journal: BMJ Open
Manuscript ID bmjopen-2018-023390.R1
Article Type: Research
Date Submitted by the Author: 17-Jul-2018
Complete List of Authors: Paganini, Sarah; Albert-Ludwigs-Universitat Freiburg, Department of Rehabilitation Psychology and Psychotherapy, Institute of PsychologyLin, Jiaxi; University of Freiburg, Department of Sports and Sport ScienceKählke, Fanny; Friedrich-Alexander University of Erlangen-Nuremberg, Department of Clinical Psychology and PsychotherapyBuntrock, Claudia; Friedrich-Alexander-Universitat Erlangen-Nurnberg, Clinical Psychology and PsychotherapyLeiding, Delia; RWTH Aachen University, Department of Psychiatry, Psychotherapy and PsychosomaticsEbert, David; Friedrich-Alexander University Erlangen Nuremberg, Clinical Psychology and PsychotherapyBaumeister, Harald; Universitat Ulm, Institut of Psychology and Education, Department of Clinical Psychology and Psychotherapy;
<b>Primary Subject Heading</b>: Mental health
Secondary Subject Heading: Health economics, Mental health
Keywords: Chronic pain, Internet-and mobile-based intervention, Health economic evaluation, Cost-effectiveness, Cost-utility
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A guided and unguided internet- and mobile-based intervention for chronic pain: Health
economic evaluation alongside a randomized controlled trial
S. Paganini 1a
, J. Lin2, F. Kählke
3, C. Buntrock
3, D. Leiding
4, D.D. Ebert
3, H. Baumeister
5
1Department of Rehabilitation Psychology and Psychotherapy, Institute of Psychology, University of
Freiburg, Germany, [email protected]
2Department of Sports and Sport Science, University of Freiburg, Germany, [email protected]
freiburg.de
3Department of Clinical Psychology and Psychotherapy, Friedrich-Alexander University of Erlangen-
Nuremberg, Germany, [email protected], [email protected], [email protected]
4Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany,
5Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education,
University of Ulm, Germany, [email protected]
a Corresponding author: Sarah Paganini, Department of Rehabilitation Psychology and
Psychotherapy, Institute of Psychology, University of Freiburg, Engelbergerstr. 41, D-79085 Freiburg,
Phone: ++49-761-203-3045, Fax: ++49-761-203-3040, Email: [email protected]
freiburg.de
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ABSTRACT
Objective: This study aims at evaluating the cost-effectiveness and cost-utility of a guided and
unguided internet-based intervention for chronic pain patients (ACTonPainguided/ACTonPainunguided)
compared to a waitlist control (WLC) condition as well as the comparative cost-effectiveness of the
two interventions.
Design: This is a health-economic evaluation alongside a three-armed randomized controlled trial
from a societal perspective. Assessments were conducted at baseline, nine weeks and six months after
randomization.
Setting: Participants were recruited through comprehensive online and offline strategies and in
collaboration with a German health insurance company.
Participants: 302 adults (≥18 years, pain for at least six months, with at least Grade II in the Chronic
Pain Grade) were randomly allocated to one of the three groups (ACTonPainguided, ACTonPainunguided,
WLC).
Interventions: ACTonPain consists of seven modules and is based on Acceptance and Commitment
Therapy. ACTonPainguided/ACTonPainunguided only differ in provision of human support.
Primary and secondary outcome measures: Main outcomes of the cost-effectiveness and the cost-
utility analyses were treatment response (meaningful change in pain interference) and quality-adjusted
life years (QALYs), respectively.
Results: At 6-month follow-up treatment response and QALYs were highest in ACTonPainguided (44%
and 0.280; mean costs=€6,945), followed by ACTonPainunguided (28% and 0.266; mean costs=€6,560)
and WLC (16% and 0.244; mean costs=€6,908). At a willingness-to-pay of €0 the probability of being
cost-effective was 50% for ACTonPainguided and 66% for ACTonPainunguided, respectively, for both
treatment response and QALY compared to WLC and in the comparative analysis 35% per treatment
response and 31% per QALY gained.
Conclusions:
Findings indicate that ACTonPain has the potential of being a cost-effective alternative or adjunct to
established pain treatment, with ACTonPainunguided (vs. WLC) even leading to lower costs at better
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health outcomes. The direct comparison of the two interventions indicates a preference for
ACTonPainunguided under health economic aspects.
Trial Registration: German Clinical Trial Registration: DRKS00006183,
URL:https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00006
183
Keywords: Chronic pain; internet- and mobile-based intervention; health economic evaluation; cost-
effectiveness; cost-utility
Strengths and limitations of this study
• This is the first study that evaluates the (comparative) cost-effectiveness of a guided and an
unguided internet-based intervention for individuals with chronic pain.
• In this study state-of-the-art statistical methods such as seemingly unrelated regression
equations models or non-parametric bootstrapping techniques were applied.
• Results should be interpreted cautiously, as the study was not powered to statistically test
health economic differences.
• As the costs and effects were evaluated over six months, no conclusions regarding the long-
term cost-effectiveness can be drawn.
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BACKGROUND
Chronic pain is highly prevalent [1–4] and associated with substantial decreases in quality of life [1, 5,
6] and high economic costs for society [3, 7–9]. Evidence supports psychological interventions as one
approach for effectively treating patients with chronic pain [10]. Treatment based on cognitive-
behavioral therapy (CBT) or third-wave therapies, like the Acceptance and Commitment Therapy
(ACT, a particular form of CBT) have shown to be effective for chronic pain patients [11, 12] and
could show acceptable results concerning cost-effectiveness [13]. However, accessibility and
availability of treatment is often restricted and up to 40% of individuals with chronic pain do not
receive adequate pain management [1, 14]. Internet- and mobile- based interventions (IMIs) are an
effective, acceptable and feasible way for providing psychological interventions [15, 16]. IMIs for
chronic pain have been shown to effectively improve pain interference compared to different control
groups, such as standard (medical) care, text-based material and mostly waitlist control condition
(standardized mean difference (SMD)=.4 [17], SMD=−0.50 [18]).
IMIs can not only facilitate the access to psychological treatment, they also have the potential to
reduce treatment costs [19, 20], particularly by saving therapist resources. IMIs can be delivered as
guided or unguided self-help interventions, with both versions usually necessitating less therapist time
compared to traditional on-site therapies [21]. A relevant health care policy question is what amount of
professional human guidance is necessary in order to improve patients´ health, with guided IMIs being
seemingly more effective than unguided IMIs [21, 22]. However, as unguided IMIs can be delivered at
lower costs per participant, they might as well be an attractive option particularly given their high
scalability on a population level.
To the best of our knowledge no randomized controlled trial (RCT) has investigated the (comparative)
cost-effectiveness of a guided and unguided IMI for chronic pain. However, Boer and colleagues
found that an IMI for chronic pain was cost-effective compared to a face-to-face group intervention
(concerning a one-point-improvement in a pain catastrophizing scale) [23]. Lin and colleagues
recently finalized a three arm RCT comparing a guided and unguided version of an Acceptance and
Commitment Therapy based IMI for chronic pain (ACTonPain) against a waitlist control group [24,
25]. Compared to the waitlist control condition, ACTonPainguided showed significantly lower pain
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interference at nine weeks and six months after randomization (d=0.58). Differences between
ACTonPainunguided and the control group and between both ACTonPain groups were not statistically
significant [25].
The present paper provides the cost-effectiveness and cost-utility of ACTonPainguided/unguided compared
to the waitlist control condition as well as the comparative cost-effectiveness of
ACTonPainguided/unguided.
METHODS
Study design and sample
This health-economic evaluation was conducted with a 6-month time horizon from the societal
perspective alongside a three-armed RCT to investigate the cost-effectiveness and cost-utility of
ACTonPain. Full details of the trial design can be found in the study protocol and the main outcome
paper of this trial [24, 25]. The economic evaluation was conducted and reported in agreement with
the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement [26] and the
International Society For Pharmacoeconomics and Outcomes Research (ISPOR) guidelines [27].
The study has been registered in the German Clinical Trial Register (DRKS00006183) and was
approved by the ethics committee of the University of Freiburg (reference: 387/14). In total, 302
participants were recruited from 10/2014 until 08/2015 in German pain clinics, largescale
organizations for chronic pain (e.g. self-help groups), on websites and with assistance of a German
health insurance company. Inclusion criteria were 1) age 18 years or older, 2) chronic pain for at least
six months, with 3) considerable intensity (=at least Grade II in the Chronic Pain Grade [28]), 4) being
medically suitable for participation in a chronic pain IMI, 5) sufficient knowledge of the German
language, 6) sufficient computer and internet literacy, and 7) having internet access. Exclusion criteria
were 1) cancer-related pain, 2) ongoing or planned psychological pain intervention within the
forthcoming three months and 3) elevated risk of suicide.
Randomization
All eligible participants who provided informed consent were asked to fill out the baseline assessment
and were randomly allocated to one of the three conditions ACTonPainguided, ACTonPainunguided and
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waitlist. Permuted block randomization with variable block sizes (6, 9, 12) was performed by an
independent researcher not otherwise involved in the study using an automated, web-based
randomization program.
Interventions
ACTonPain is a German adaption of an IMI by Buhrman and colleagues [29] for individuals suffering
from chronic pain. The intervention is based on ACT and consists of seven modules, which include
information, metaphors, assignments, and mindfulness exercises. Both treatment conditions differ only
in the provision of guidance. Participants were advised to work on one module every week (~60
minutes). In both intervention groups, participants had the option to receive daily automated text
messages that repeated content, reminded and motivated participants.
In ACTonPainguided trained and supervised eCoaches (psychologists) provided written feedback for
each module, which aimed at increasing participants' motivation and adherence. The total time of an
eCoach spent per participant was approximately 1.75 hours. Participants in the waitlist condition
received the offer to use ACTonPainunguided after the last follow-up assessment. Participants of all three
trial arms had unrestricted access to care-as-usual.
Outcome measures
Assessment took place at baseline (T0), post-treatment (T1; nine weeks after randomization) and 6-
month follow-up (T2; six months after randomization). Outcomes were assessed by means of an
online self-report assessment using a secured internet-based platform (AES, 256-bit encrypted).
Treatment response
Main clinical outcome in the cost-effectiveness analysis was treatment response. This outcome was
not defined in the protocol paper. However, it was chosen to calculate a reliable and meaningful
change in pain interference according to the recommendations of the Initiative on Methods,
Measurement, and Pain Assessment in Clinical Trials (IMMPACT) [33] instead of a one-point change
on the MPI, that would be difficult to interpret.
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According to the IMMPACT recommendations clinically important changes were identified with a
combination of a distribution-based approach (Pain Interference Scale of the Multidimensional Pain
Inventory MPI [30, 31]) and an anchor-based approach (Patient Global Impression of Change scale
PGIC [32]) [33]. First, participants with a change of 0.6 points (based on the scale’s standard
deviation) on the Pain Interference Scale of the MPI (range of the scale: 0-6) were identified as having
minimal clinically important changes [33]. Second, participants were identified, that rated their global
improvement in the PGIC [32] as “minimally, much or very much improved”. Participants who
fulfilled both criteria were classified as having achieved a clinically important change [33], defined as
“treatment response”.
Quality-adjusted life years
The clinical outcome in the cost-utility analysis was quality-adjusted life years (QALYs) based on the
AQoL-8D [34] in the main analysis and the EQ5D-3L [35] in the sensitivity analysis. Utility scores
are a preference-based measure of quality of life that is normed by the value 1 meaning complete
health and 0 meaning death [36].
The AQoL-8D comprises 35 items, which load on three physical (independent living, pain, senses)
and five psycho-social (mental health, happiness, coping, relationships, self-worth) dimensions [34].
The utility scores are scaled by SPSS algorithm for AQoL-8D utility model [34]. The AQoL-8D has
been shown as a reliable and valid instrument, suitable when psychosocial elements of health are the
focus of research [34], whereas utility weights are derived from the Australian adult population [37].
The EQ-5D-3L consists of five dimensions (mobility, self-care, usual activities, pain/discomfort, and
anxiety/depression), each of which is rated as causing ‘no’, ‘some’ or ‘extreme problems,’ and is a
well validated instrument [35, 38, 39]. Theoretically, the EQ-5D-3L generates 243 different health
states. Utility scores were calculated using the UK tariffs [40].
The AQoL-8D covers more dimensions that might be affected by chronic pain and shows a higher
sensitivity to mental health-related quality of life dimensions [41] compared to the EQ5D-3L.
Subsequently, and different to our protocol, this instrument was chosen for the main analyses[24].
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QALY health gains for the 6-months period were estimated by calculating the area under the curve
(AUC) of linearly interpolated AQoL-8D and EQ-5D-3L utility scores [42].
Resource use and costing
The Trimbos and iMTA questionnaire for costs associated with psychiatric illness (TiC-P) [43, 44]
was adapted to the German health care system and to the healthcare use of individuals with chronic
pain. It was used to assess the direct and indirect costs of the past three month at T0 and T2. Costs
were expressed in Euros (€) for the reference year 2015 (index factor 1.003 and 1.01 for outpatient
medical service, respectively) referring to the German consumer price index [45] (list of unit cost
prices see Table 1). To calculate the 6-month accumulated per-participants costs, the area under curve
(AUC) method was used by linearly interpolating 3-month costs (measured at T0 und T2) to cover the
full period of six months [42].
��� = �����03 + ����232 � ∗ 3 + ����2
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Table 1: List of unit cost prices
Sector Unit Category 2015 (in Euro)
Ou
tpat
ien
t m
edic
al s
erv
ice
/
outp
atie
nt
sect
or
Euro/contact
Physician Gynecologist
Orthopedist
Specialists for internal medicine Ophthalmologist
Dermatologist
ETN specialist Surgeon
Urologist
Neurologist
Psychotherapist
Dentist
20.81 31.62
25.82
64.25 36.96
19.58
28.12 44.59
25.20
47.02
79.42
55.24
remedies Logopedics / speech therapy Physiotherapy
Ergotherapy / occupational therapy
Podiatry / podology Mean remedies
41.02 17.50
39.45
29.13 31.77
hospitals Euro/day
Completely stationary normal ward
Completely stationary intensive care Completely stationary psychiatry
Semi-stationary general hospital
Semi-stationary psychiatry
648.11
1,424.60 348.26
421.27
226.37
rehabilitation Euro/day Outpatient
Inpatient
49.43
138.19
opportunitiy costs Euro/hour
opportunity costs (free time)
opportunity costs (work)
substitution costs for informal care
21.77
31.89
18.97
Note: Prices for outpatient medical service/outpatient sector were calculated fort the year 2013; all other prices
for the year 2014 [46, 47] and adjusted by the German consumer price index for 2015 [45]. ETN specialist, Ear,
nose, and throat specialist.
Direct medical costs
Healthcare costs (e.g. out- and inpatient care) were calculated according to the German guideline of
Bock and colleagues [46, 47]. The costs of therapeutic appliances (that were not listed in Bock and
colleagues [46, 47]) and medication were obtained from the Lauer-Taxe [48].
Patient and family costs
Self-reported out-of-pocket expenses and direct non-medical costs (travel expenses, opportunity costs,
domestic help) were assessed. Participants reported the cost of travelling by bus or taxi. If not stated,
each kilometer was valued at €0.30. Opportunity costs (i.e., time spent at the practitioners waiting
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room) were estimated at €21.77 per hour. Costs of informal care were valued using a shadow price of
€18.97 per hour [47].
Indirect costs
Indirect costs included productivity losses caused by absenteeism and presenteeism. Absenteeism
costs were calculated according to the human capital approach [49]. Self-reported lost work days were
multiplied by the corresponding gross average of participants’ income per day. To calculate
presenteeism costs, participants reported the number of days of reduced efficiency at work. These days
were weighted by an inefficiency score. Productivity losses from unpaid work (i.e. domestic help from
family members) were valued using a shadow price of €18.97 per hour [47].
Intervention costs
Intervention costs of ACTonPainguided (€299) and ACTonPainunguided (€69) were based on actual
market prices for (un)guided interventions with a similar amount of modules that contain all costs for
developing and hosting the intervention (https://geton-institut.de/).
Statistical analysis
This study was not powered to statistically test differences in health economic outcomes. Therefore,
we took a probabilistic decision-making approach for health-economic inferences [50], that aims at
informing decision makers on probabilities rather than statistical significance. There was no need to
discount costs or outcomes as the time frame for the study was six months.
All analyses were conducted according to the intention-to-treat principle. All participants completed
T0. Missing clinical outcome data was imputed using the expectation maximization algorithm in
Statistical Package for the Social Sciences (SPSS, version 20). Analyses of clinical outcomes were
conducted and reported elsewhere [25] in accordance with the CONSORT 2010 Statement[51].
Missing cost data was imputed using the regression imputation procedure in Stata version 13 [52].
Predictors of cost data and dropout were identified by logistic regression analysis and were used to
obtain the most likely values of the missing cost data. At baseline, AQoL-utilities differed between
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groups (ACTonPainguided: M=0.496, SD=0.16; ACTonPainunguided: M=0.485, SD=0.17; waitlist:
M=0.463, SD=0.14). Therefore, baseline adjustments were made in further calculations.
We tested group differences in treatment response using the chi-squared test and the Kruskall-Wallis
test for QALYs both followed by post-hoc comparisons (Bonferroni and Dunn´s test, respectively).
In the cost-effectiveness analyses, the outcome estimate is the incremental cost-effectiveness ratio
(ICER), where incremental costs over the 6-month period are divided by incremental effects
(treatment response or QALYs): ICER=(CostsIG–CostsCG)/(EffectsIG–EffectsCG) subscripted with IG
for the two intervention groups and CG for the comparison groups. Different to the protocol [24],
ICERs are reported for a 6-month horizon (baseline data; T0 and 6-month follow-up; T2) and not
based on pre-post (T0 and post-treatment; T1). As participants are asked for their health care
utilization during the last three months, the TiC-P can only be evaluated appropriately at T0 and T2 (as
T1 assessments are conducted nine weeks after randomization).
Non-parametric bootstrapping by resampling patient-level data with 5,000 replications was used to
take into account the sampling uncertainty of the ICER estimates. Seemingly unrelated regression
equations models were bootstrapped to allow for correlated residuals of the cost and effect equations.
Bootstrapping was used to obtain 95% confidence intervals for the ICERs based on the percentile
method, since parametric techniques are inappropriate for use on skewed variables and ratios [50].
The bootstrapped ICERs were plotted on a cost-effectiveness plane. In addition, a cost-effectiveness
acceptability curve was graphed to assess the probability that the intervention is cost-effective relative
to the comparator condition given varying willingness-to-pay (WTP) ceilings. In order to increase
readability of the direct comparison ACTonPainguided vs. ACTonPainunguided the inverse cost-
effectiveness acceptability curve (ACTonPainunguided vs. ACTonPainguided) was additionally plotted. All
analyses were performed using Stata version 13 [52].
Sensitivity analysis
We tested the robustness of the outcomes of the main analysis in a sensitivity analysis. Therefore, we
used the EQ-5D-3L as a widely used instrument for calculating QALYs. As baseline EQ5D-utilities
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differed between groups (ACTonPainguided: M=0.469, SD=0.32; ACTonPainunguided: M=0.436,
SD=0.31; waitlist: M=0.494, SD=0.3), baseline adjustment was made in the sensitivity analyses.
Patient and public involvement
No patients or public were involved in developing the research question or the outcome measures, nor
were they involved in developing plans for design or implementation of the study. Possible negative
effects were assessed as well as the satisfaction with the intervention (for results, see [25]). The results
of the research will be disseminated to those study participants who wished to be notified.
RESULTS
Sample characteristics
The overall sample size was 302. Due to missing assessments the dropout rate was 25.8% at 6-month
follow-up (ACTonPainguided: 33/100; ACTonPainunguided: 35/101; waitlist: 10/101). At 6-month follow
up, dropout rates differed significantly between groups (χ2(2)=20.17, p<.001). Pairwise comparison
revealed significant differences for ACTonPainguided vs. waitlist (t(1)=-3.85, p<.001) and
ACTonPainunguided vs. waitlist (t(1)=-4.14, p<.001). Study dropout was not associated with baseline
pain interference or socio-demographic factors.
The average participant was female, 52 years of age, with an above average level of education,
employed and was already treated for chronic pain. Detailed participants’ characteristics and the
CONSORT flowchart have already been reported elsewhere [25].
Outcomes
Table 2 shows treatment response and QALY outcomes as well as group differences. At 6-month
follow-up, treatment response differed significantly between groups (ACTonPainguided: 44/100;
ACTonPainunguided: 28/101; waitlist: 16/101). Pairwise comparison revealed significant differences for
ACTonPainguided vs. waitlist and ACTonPainguided vs. ACTonPainunguided but not for ACTonPainunguided
vs. waitlist. Between-group differences in AQoL-8D QALY gains were statistically significant.
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Pairwise comparison revealed significant differences only for ACTonPainguided vs. waitlist. Incremental
EQ5D-3L QALY gains did not differ significantly between study groups.
Table 2. Treatment response and quality-adjusted life-year (QALY) outcomes and group differences at
6-month follow up.
ACTonPain guided
(n = 100)
ACTonPain unguided
(n = 101)
WLC group
(n = 101)
Test statistic
Mean (SD) Mean (SD) Mean (SD) χ2 (df=2) Post-hoc test
c: p
Treatment response
(pain interference)
0.44 (0.05)
0.277 (0.04)
0.158 (0.04)
19.44 a
<001
ACTonPain guided vs. WLC group t(1)=4.52 <.001
ACTonPain unguided vs. WLC group t(1)=1.91 .17
ACTonPain guided vs. unguided t(1)=2.61 .03
QALY
AQoL-8D
0.280 (0.08)
0.266 (0.09)
0.244 (0.08)
9.45 b
.009
ACTonPain guided vs. WLC group Z=-3.07 .003
ACTonPain unguided vs. WLC group Z=-1.61 .16
ACTonPain guided vs. unguided Z=-1.47 .21
EQ5D-3L 0.274 (0.12) 0.255 (0.12) 0.253 (0.13) 2.17 b .34
WLC group, waitlist control group; SD, standard deviation; df, degrees of freedom; QALY, quality-adjusted life-
year a Chi-squared test b Kruskall-Wallis H test
c Post-hoc test for treatment response: Bonferroni pairwise comparison; Post-hoc test for QALY: Dunn´s test
Costs
At baseline, mean total costs were €3,233 in ACTonPainguided, €3,724 in ACTonPainunguided and €3,570
in the waitlist group. The 6-month accumulated per-participants costs by study condition are presented
in Table 3. ACTonPainguided showed the highest mean total costs (€6,945), followed by the waitlist
group (€6,908) and ACTonPainunguided (€6,560). Mean direct costs were the highest in the guided
group, followed by the unguided group and waitlist. The opposite order was found for the indirect
costs. Medication, domestic help and opportunity costs were major cost drivers. Productivity losses
produced the highest cost differences between the intervention groups and waitlist of -€871
(ACTonPainguided vs. waitlist) and -€721 (ACTonPainunguided vs. waitlist).
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Table 3. 6-month accumulated per-participants costs (in €) by condition (based on intention-to-treat
sample, N = 302).
ACTonPain guided
(n = 100)
ACTonPain unguided
(n = 101)
WLC group
(n = 101)
Incremental costs
Difference, €
Mean, €
(SD)
Mean, €
(SD)
Mean
, €
(SD)
ACTon
Pain guided
vs.
WLC
ACTon
Pain unguided
vs.
WLC
ACTon
Pain guided
vs. unguided
Intervention 299 (-) 69 (-) 0 (-) 299 69 230
Direct medical costs
Health care costs
Medical specialist 576 (478) 511 (381) 511 (382) 65 0 65
Mental health care 212 (431) 181 (397) 258 (455) -46 -77 31
Other medical
specialist a
369 (515) 357 (435) 406 (576) -37 -49 12
In-patient care
(hospital)
198 (479) 173 (369) 141 (420) 57 32 25
Day care 147 (687) 122 (381) 306 (1,584) -159 -184 25
Rehabilitation 190 (794) 134 (507) 191 (773) -1 -57 56
Medication 1,092 (2,748) 784 (1,438) 660 (1,638) 432 124 308
Therapeutic appliances 65 (139) 86 (222) 46 (96) 19 40 -21
Direct non-medical costs
Patient and family costs
Travel 131 (229) 105 (150) 101 (100) 30 4 26
Domestic help 1,297 (4,064) 1,147 (1,936) 840 (1,490) 457 307 150
Opportunity costs b 1,553 (1,965) 1,925 (3,251) 1,759 (3,116) -206 166 -372
Indirect costs
Productivity losses
Absenteeism 517 (1,647) 647 (1,979) 1,133 (3,333) -616 -486 -130
Presenteeism 300 (740) 320 (774) 555 (1,360) -255 -235 -20
Total direct costs 5,829 (7,129) 5,525 (4,959) 5,220 (5,133) 611 306 305
Total indirect costs 817 (1,978) 966 (2,283) 1,688 (3,735) -871 -721 -150
Total societal costs 6,945 (7,327) 6,560 (5,549) 6,908 (6,279) 39 -346 385
WLC group, waitlist control group a i.e. physiotherapist, occupational therapist
b i.e. for waiting time before treatment
Health-economic evaluation
Table 4 shows the incremental costs, effects and cost-effectiveness ratios for the main analysis and the
sensitivity analysis.
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Table 4. Results of the main and sensitivity analyses (based on 5,000 bootstrap simulations).
Analysis
ACTonPain guided vs.
WLC group
Incremental
costs, €
(95% CI)
Incremental
effects
(95% CI)
Mean
ICER
(95% CI)
Distribution over the ICER
plane
NE NW SE SW
Cost-effectiveness,
treatment response
(MPI and PGIC)
6
(-916-953)
0.14
(0.08-0.2)
171
(-6,671-8,260)
50% - 50% -
Cost-utility
AQoL QALYs
6
(-916-953)
0.01
(0.005- 0.015)
3,033
(-92,924-
114,325)
50%
-
50%
-
Sensitivity analysis
EQ5D QALYs 6
(-916-953)
0.014
(0.004- 0.024)
4726 (-69,407-
122,314)
50% - 50% -
Analysis
ACTonPain unguided vs.
WLC group
Incremental
costs, €
(95% CI)
Incremental
effects
(95% CI)
Mean
ICER
(95% CI)
Distribution over the ICER
plane
NE NW SE SW
Cost-effectiveness,
treatment response
(MPI and PGIC)
-352
(-1,968-
1,272)
0.12
(0.006-0.232)
ACTonPain unguided
dominates
WLC
32% 1% 66% 1%
Cost-utility
AQoL QALYs
-352
(-1,968-
1,272)
0.013
(0.002-0.024)
ACTonPain unguided
dominates
WLC
32%
1%
66%
1%
Sensitivity analysis
EQ5D QALYs -352
(-1,968-
1,272)
0.017
(-0.005- 0.04)
ACTonPain unguided
dominates
WLC
30% 4% 64% 3%
Analysis
ACTonPain guided vs.
ACTonPain unguided
Incremental
costs, €
(95% CI)
Incremental
effects
(95% CI)
Mean
ICER
(95% CI)
Distribution over the ICER
plane
NE NW SE SW
Cost-effectiveness,
treatment response
(MPI and PGIC)
388
(-1,416-
2,185)
0.164
(0.034-0.29)
2,949
(-11,097-
25,276)
65% - 35% -
Cost-utility
AQoL QALYs
388
(-1,416-
2,185)
0.008
(-0.003-0.019)
198,377 a
60%
5%
33%
2%
Sensitivity analysis
EQ5D QALYs 388
(-1,416-
2,158)
0.01
(-0.01- 0.031)
114,858 a
53% 12% 31% 4%
WLC group, waitlist control group; MPI, Pain Interference Scale of the Multidimensional Pain Inventory;
PGIC, Patient Global Impression of Change scale; 95% CI, 95% confidence interval; EQ-5D QALYs,
Quality-adjusted life years based on EuroQol; ICER, incremental cost-effectiveness ratio; NE, northeast
quadrant; NW, northwest quadrant; SE, southeast quadrant; SW, southwest quadrant. aA dependably accurate 95% confidence interval for this distribution cannot be defined because there is no line
through the origin that excludes α/2 of the distribution[53].
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Cost-effectiveness
The cost-effectiveness planes and acceptability curves, representing the 5,000 bootstrap replications,
are shown in Figure 1(a,b,c) and 2(a,b). ACTonPainguided showed the same and ACTonPainunguided a
higher potential of being cost-effective compared to waitlist at a WTP of €0 (ACTonPainguided 50%,
ACTonPainunguided 66%). The probability of ACTonPainguided being more cost-effective compared to
waitlist increased up to 70% at a WTP of €1,738 and to 95% at a WTP of €6,490 for an additional
treatment response, and for ACTonPainunguided to 70% at a WTP of €660 and to 95% at a WTP of
€13,460.
The probability that ACTonPainguided is more cost-effective than ACTonPainunguided was 35% at a WTP
of €0 for an additional treatment response. When society’s WTP increases up to €5,535 or €17,170
this probability rises to 70% or 95%, respectively. The break even point (where ACTonPainguided and
ACTonPainunguided have the same possibility of being cost-effective at same costs) is at €2,188 (see
Figure 2b).
- Figure 1-
- Figure 2-
Cost-utility
Cost-effectiveness planes and acceptability curves that refer to cost-utility are shown in figure 1(d,e,f)
and 2(c,d). ACTonPainguided showed the same and ACTonPainunguided a higher potential of being cost-
effective compared to waitlist at a WTP of €0 (50% and 66%, respectively). The interventions’
probability of being more cost-effective compared to waitlist increased up to 70% and to 95% at a
WTP of €24,415 and €91,000, respectively, in ACTonPainguided and €6,130 (70%) and €127,000 (95%)
in ACTonPainunguided for one additional QALY. The probability that ACTonPainguided is more cost-
effective than ACTonPainunguided was 31% at a WTP of €0 for one additional QALY. When society’s
WTP increases up to €113,550 this probability rises to 70% and stagnates on this level. The break-
even point is at €41,350 (see Figure 2d).
Sensitivity analysis
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After non-parametric bootstrapping, using the EQ-5D-3L resulted in smaller incremental QALY gains
in all comparisons compared to the results using the AQoL-8D (see table 4).
At a WTP of €0 the probability of ACTonPainguided of being cost-effective compared to waitlist was
50%. The probability of ACTonPainunguided of being cost-effective compared to waitlist was 64% at a
WTP of €0. ACTonPainguided vs. ACTonPainunguided resulted in a probability of being cost-effective of
31% at a WTP of €0.
DISCUSSION
Comparing both ACTonPain interventions to waitlist and by taking uncertainty into account,
ACTonPainunguided can be judged as a potentially cost-effective intervention as it dominates WLC by
leading to higher QALY gains and more individuals with a treatment response at lower costs.
ACTonPainguided also causes better results in the main outcome parameters, but at (slightly) higher
costs with ICERs of 171 (treatment response) and 3,033 (AQoL QALY gains). The probability of
being cost-effective at a WTP of €0 compared to waitlist is higher in ACTonPainunguided, for both,
treatment response and QALYs gained (66%) than in ACTonPainguided (50%).
However, when comparing the costs that would have to be invested by using ACTonPainguided
(compared to waitlist) for a QALY gained (€3,033) to the only official WTP threshold stated by the
National Institute for Health and Clinical Excellence (NICE) of £20,000 to £30,000 [54] (~ €22,647 -
€33,971; conversion according to the European Central bank [55]), this intervention would also be
categorized as a potentially cost-effective treatment, whereas again uncertainty has to be considered.
The direct comparison of ACTonPainguided and ACTonPainunguided shows more treatment responders
and higher QALY gains for the guided version, but at higher costs. According to the NICE guidelines
costs are far above the WTP threshold for a QALY gain and would thus be judged as probably not
cost-effective. In terms of QALYs gained, the guided version only reaches a probability of 31% of
being cost-effective at a WTP of €0 and even with rising WTP threshold, the probability does not
increase much (e.g. at a WTP of €50,000 to about 53%).
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The results of the sensitivity analyses revealed slightly higher incremental QALY gains by using the
EQ5D-3L compared to the AQoL-8D but overall conclusions are the same as in the main analyses.
Estimated EQ-5D utility scores for one year ranged from 0.50 to 0.54, what appears rather low
compared to national EQ-5D estimates for (back) pain from other countries (e.g. 0.74-0.79 [56, 57]).
Lower estimates in the current study could have occurred due to the sociodemographic properties of
this study sample, as participants were predominately women (84%), reported comorbid medical or
mental conditions (57% and 39%, respectively) and the back was the most often reported pain location
(34%) [25]. Several studies showed that the mentioned characteristics (female sex, musculoskeletal
and mental disorders) are associated with lower quality of life scores [56–58]. Furthermore, Burström
et al. (2001) reported in their study that participants with low back pain showed quality of life weights
of 0.55 [58], what is comparable to the sample in the current study.
The conclusion of ACTonPain being cost-effective are in line with a recent study and a review about
the cost-effectiveness of IMIs for depression [23, 59]. The guided IMI for chronic pain of Boer and
colleagues revealed an ICER of 40 (defined as cost savings of €40) for an one-point improvement in a
pain catastrophizing scale compared to a face-to-face group intervention, while QALYs were not
reported [23]. ACTonPainguided reached higher ICERs for the clinical outcome pain interference (171
compared to waitlist group and 2,949 compared to the unguided group). However, these values were
calculated for treatment response in terms of pain interference and therefore, a meaningful change and
not for a one-point improvement on the scale. In a systematic review, IMIs that were classified as cost-
effective were all guided and showed probabilities of being cost-effective between 28% and 49% at a
WTP of €0 for a QALY gained, whereas ACTonPainguided and the unguided version even reached
higher probabilities at this WTP level (50% and 66%, respectively). Thus, integrating psychological e-
health approaches in pain management programs might even be more promising from an economical
point of view when compared to the well-established area of depression e-health care.
The higher direct costs over a 6-month period in both intervention groups compared to waitlist might
be explained by higher or stable health care utilization similar to findings in a previous study on the
costs of established depression treatments [60]. However, research indicates that indirect rather than
direct costs represent the majority of overall costs [61, 62], where ACTonPain seemingly has its core
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advantage. Mean indirect costs over the 6-month period were almost half as high in the intervention
groups compared to waitlist, regarding both absenteeism and presenteeism.
Next to the questions of whether ACTonPain is cost-effective compared to waitlist and whether it
should rather be provided guided or unguided with possible answers such as “both interventions are
potentially cost-effective, but uncertainties have to be taken into account” and “in terms of cost-
effectiveness, the unguided version should be preferred”, it would be of interest how ACTonPain
performs compared to established medical, psychological, physiotherapeutical, and surgical treatments
that result in high direct costs [63–66]. However, surprisingly little is known about the cost-
effectiveness of these established pain treatments. In two reviews it was highlighted, that
interdisciplinary pain rehabilitation programs are more cost-effective or produce lower costs than
interventions such as surgery and conservative care [67, 68]. For individuals with low back pain it was
concluded that interdisciplinary rehabilitation, exercise, acupuncture, spinal manipulation and CBT are
potentially cost-effective [69]. A further systematic review focused on economic evaluations of third-
wave CBT therapies (including ACT), were available ICERs ranged from -€19,300 (National Health
Service perspective, converted into Euro [55]) to €56,637 (societal perspective) per QALY gained
[13]. When compared to waitlist the ICERs based on the AQoL-8D in this study were €3,033 and a
negative ICER (indicating dominance of the unguided intervention over WLC) per QALY gained.
Thus, it seems safe to argue that ACTonPain, as an example of an innovative IMI for the treatment of
chronic pain, is effective [25] and can be an cost-effective intervention. A comparison across treatment
approaches for chronic pain, however, cannot be provided as the evidence base for the cost-
effectiveness of established pain treatments is rather weak and the comparability of results across
studies is limited due to very heterogeneous methods across trials [70].
Limitations
First, when interpreting the results, it has to be considered that the study was not powered to
statistically test health economic differences. Second, the costs and effects were evaluated over six
months. Therefore, no conclusions regarding the long-term cost-effectiveness can be drawn. Third,
costs were assessed via self-report. However, as the questionnaire used in this study is a valid
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instrument to recall periods up to three months [71], the impact of this bias on results is limited.
Finally, the usage of multiple imputation techniques is frequently recommended (e.g. predictive mean
matching [72]. We used a single imputation approach as it was done in the main (effectiveness)
analysis [25] that might not truly reflect missing data uncertainty. However, the comparison with cost
and QALY outcomes of complete case analysis revealed only small differences, indicating that the risk
of implausible values due to single imputation in this evaluation is low [73]. Furthermore, by using the
non-parametric bootstrapping, sampling was considered.
Implications and future research
For patients with chronic pain, IMIs might become an important alternative to established
interventions. IMIs can expand treatment options for people, whose physical impairment or location
makes access to relevant care difficult [19]. Findings from this health economic evaluation study show
that both versions of ACTonPain have the potential of being cost-effective, with the unguided version
even leading to lower costs (compared to WLC). The decision whether to choose the guided or
unguided version is a public health issue and strongly depends on whether to mainly focus on patients´
health or societies´ resources. Under health economic aspects ACTonPainunguided should be the
preferred intervention, especially when considering the intention of treatment implementation into the
health care system and scaling up mental health care for pain patients.
Future research should especially focus on conducting methodologically sound studies that are
powered to statistically test health economic differences. Furthermore, long-term follow-up studies
and evaluation of (comparative) cost-effectiveness of different guidance formats of IMIs, particularly
of ACTonPain, and established pain treatments are needed. Moreover, future studies should examine
ACTonPain as integrated part of multi-component pain programs and aim to dismantle the ingredients
that are effective and cost-effective in those complex approaches.
DECLARATIONS
Funding
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This research received no specific grant from any funding agency in the public, commercial or not-for-
profit sectors. The article processing charge was funded by the German Research Foundation (DFG)
and the Albert-Ludwigs University Freiburg in the funding programme Open Access Publishing.
Competing interests
Two of the authors of the manuscript were involved in the development of ACTonPain (JL and HB).
HB and DDE are consultants for several stakeholders (insurance companies, ministries, psychotherapy
chambers, companies). DDE is part of the GET.ON Institut GmbH, which aims at implementing
evidence-based internet- and mobile based interventions into routine care. SP, CB, FK and DL declare
that they have no competing interests.
Data sharing statement
The datasets used and/or analyzed during the current study are available from the corresponding
author on reasonable request.
Authors’ contributions
JL and HB initiated the randomized control trial for this health economic evaluation. SP, FK, CB, DL
and DDE contributed to the design of this health economic evaluation. SP, DL, FK and CB
contributed to the data analysis. SP had full access to all the data in the study and had responsibility
for the decision to submit for publication. SP wrote the draft of the manuscript. All authors contributed
to the further writing and approved the final version of the manuscript.
Acknowledgements
We would like to thank Yannik Terhorst and Nelli Hirschauer for their assistance in data processing.
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Figure Legends
Figure 1. Cost-effectiveness planes of all group comparisons based on 5,000 replicates of the
incremental cost-effectiveness ratio using mean differences in costs from a societal perspective and
mean incremental effects (treatment response: a, b, c; QALYs: d, e, f)
Figure 2. Cost-effectiveness acceptability curves of all group comparisons based on 5,000 replicates
of the incremental cost-effectiveness ratio using mean differences in costs from a societal
perspective and mean incremental effects (treatment response: a, b; QALYs: c, d). For the
comparison of ACTonPain guided vs. ACTonPain unguided the inverse function (ACTonPain
unguided vs. ACTonPain guided) was included.
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73. Vroomen JM, Eekhout I, Dijkgraaf MG, van Hout H, Rooij SE de, Heymans MW, Bosmans JE.
Multiple imputation strategies for zero-inflated cost data in economic evaluations: which
method works best? The European Journal of Health Economics. 2016;17:939–50.
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Figure 1. Cost-effectiveness planes of all group comparisons based on 5,000 replicates of the incremental cost-effectiveness ratio using mean differences in costs from a societal perspective and mean incremental
effects (treatment response: a, b, c; QALYs: d, e, f).
122x63mm (300 x 300 DPI)
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Figure 2. Cost-effectiveness acceptability curves of all group comparisons based on 5,000 replicates of the incremental cost-effectiveness ratio using mean differences in costs from a societal perspective and mean incremental effects (treatment response: a, b; QALYs: c, d). For the comparison of ACTonPain guided vs.
ACTonPain unguided the inverse function (ACTonPain unguided vs. ACTonPain guided) was included.
422x274mm (300 x 300 DPI)
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Additional file 1 – CHEERS checklist
Section/item Item
No
Recommendation Reported on page
No
Title and abstract
Title 1 Identify the study as an economic evaluation or
use more specific terms such as “cost-
effectiveness analysis”, and describe the
interventions compared.
Page 1
Abstract 2 Provide a structured summary of objectives,
perspective, setting, methods (including study
design and inputs), results (including base case
and uncertainty analyses), and conclusions.
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sensitivity analysis
is not mentioned
in the abstract
due to limited
words)
Introduction
Background and
objectives
3 Provide an explicit statement of the broader
context for the study.
Present the study question and its relevance for
health policy or practice decisions.
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Methods
Target population
and subgroups
4 Describe characteristics of the base case
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why they were chosen.
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the decision(s) need(s) to be made.
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Study perspective 6 Describe the perspective of the study and relate
this to the costs being evaluated.
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Comparators 7 Describe the interventions or strategies being
compared and state why they were chosen.
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Time horizon 8 State the time horizon(s) over which costs and
consequences are being evaluated and say why
appropriate.
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Discount rate 9 Report the choice of discount rate(s) used for
costs and outcomes and say why appropriate.
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Choice of health
outcomes
10 Describe what outcomes were used as the
measure(s) of benefit in the evaluation and their
relevance for the type of analysis performed.
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Measurement of
effectiveness
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design features of the single effectiveness study
and why the single study was a sufficient source
of clinical effectiveness data.
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11b Synthesis-based estimates: Describe fully the
methods used for identification of included
studies and synthesis of clinical effectiveness
data.
N/A
Measurement and
valuation of
preference based
outcomes
12 If applicable, describe the population and
methods used to elicit preferences for outcomes.
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No
Estimating costs and
resources
13a Single study-based economic evaluation:
Describe approaches used to estimate resource
use associated with the alternative
interventions. Describe primary or secondary
research methods for valuing each resource item
in terms of its unit cost. Describe any
adjustments made to approximate to
opportunity costs.
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Table 1
13b Model-based economic evaluation: Describe
approaches and data sources used to estimate
resource use associated with model health
states. Describe primary or secondary research
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to approximate to opportunity costs.
N/A
Currency, price date
and conversion
14 Report the dates of the estimated resource
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adjusting estimated unit costs to the year of
reported costs if necessary. Describe methods for
converting costs into a common currency base
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decision-analytical model used. Providing a figure
to show model structure is strongly
recommended.
N/A
Assumptions 16 Describe all structural or other assumptions
underpinning the decision-analytical model.
N/A
Analytical methods 17 Describe all analytical methods supporting the
evaluation. This could include methods for
dealing with skewed, missing, or censored data;
extrapolation methods; methods for pooling
data; approaches to validate or make
adjustments (such as half cycle corrections) to a
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heterogeneity and uncertainty.
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Results
Study parameters 18 Report the values, ranges, references, and, if
used, probability distributions for all parameters.
Report reasons or sources for distributions used
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Providing a table to show the input values is
strongly recommended.
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2 and 4
Incremental costs
and outcomes
19 For each intervention, report mean values for the
main categories of estimated costs and outcomes
of interest, as well as mean differences between
the comparator groups. If applicable, report
incremental cost-effectiveness ratios.
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Table 3
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Characterising
uncertainty
20a Single study-based economic evaluation:
Describe the effects of sampling uncertainty for
the estimated incremental cost and
incremental effectiveness parameters, together
with the impact of methodological assumptions
(such as discount rate, study
perspective).
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parameters, and uncertainty related to the
structure of the model and assumptions.
N/A
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outcomes, or cost-effectiveness that can be
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current knowledge
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For peer review onlyA guided and unguided internet- and mobile-based
intervention for chronic pain: Health economic evaluation alongside a randomized controlled trial
Journal: BMJ Open
Manuscript ID bmjopen-2018-023390.R2
Article Type: Research
Date Submitted by the Author: 22-Oct-2018
Complete List of Authors: Paganini, Sarah; Albert-Ludwigs University Freiburg, Department of Sports and Sport Science, Sport Psychology; Albert-Ludwigs University Freiburg, Department of Rehabilitation Psychology and Psychotherapy, Institute of PsychologyLin, Jiaxi; Albert-Ludwigs University Freiburg, Department of Sports and Sport Science, Sport PsychologyKählke, Fanny; Friedrich-Alexander University of Erlangen-Nuremberg, Department of Clinical Psychology and PsychotherapyBuntrock, Claudia; Friedrich-Alexander-Universitat Erlangen-Nurnberg, Clinical Psychology and PsychotherapyLeiding, Delia; RWTH Aachen University, Department of Psychiatry, Psychotherapy and PsychosomaticsEbert, David; Friedrich-Alexander University Erlangen Nuremberg, Clinical Psychology and PsychotherapyBaumeister, Harald; Universitat Ulm, Institut of Psychology and Education, Department of Clinical Psychology and Psychotherapy
<b>Primary Subject Heading</b>: Mental health
Secondary Subject Heading: Health economics, Mental health
Keywords: Chronic pain, Internet-and mobile-based intervention, Health economic evaluation, Cost-effectiveness, Cost-utility
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A guided and unguided internet- and mobile-based intervention for chronic pain: Health economic evaluation alongside a randomized controlled trial
S. Paganini 1, 2a, J. Lin1, F. Kählke3, C. Buntrock3, D. Leiding4, D.D. Ebert3, H. Baumeister5
1Department of Sports and Sport Science, Sport Psychology, University of Freiburg, Germany, [email protected], [email protected]
2Department of Rehabilitation Psychology and Psychotherapy, Institute of Psychology, University of Freiburg, Germany
3Department of Clinical Psychology and Psychotherapy, Friedrich-Alexander University of Erlangen-Nuremberg, Germany, [email protected], [email protected], [email protected]
4Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany, [email protected]
5Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, University of Ulm, Germany, [email protected]
a Corresponding author: Sarah Paganini, Department of Sports and Sport Science, Sport Psychology, University of Freiburg, Germany, Schwarzwaldstr. 175, 79117 Freiburg, Phone: +49 (0)761 / 203-4514, Email: [email protected]
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ABSTRACT
Objective: This study aims at evaluating the cost-effectiveness/cost-utility of a guided and unguided
internet-based intervention for chronic pain patients (ACTonPainguided/ACTonPainunguided) compared to a
waitlist control(WLC) condition as well as the comparative cost-effectiveness of the interventions.
Design: This is a health-economic evaluation alongside a three-armed randomized controlled trial from a
societal perspective. Assessments were conducted at baseline, nine weeks and six months after
randomization.
Setting: Participants were recruited through online and offline strategies and in collaboration with a health
insurance company.
Participants: 302 adults (≥18 years, pain for at least six months) were randomly allocated to one of the
three groups(ACTonPainguided,ACTonPainunguided,WLC).
Interventions: ACTonPain consists of seven modules and is based on Acceptance and Commitment
Therapy. ACTonPainguided/ACTonPainunguided only differ in provision of human support.
Primary and secondary outcome measures: Main outcomes of the cost-effectiveness and the cost-utility
analyses were meaningful change in pain interference (treatment response) and quality-adjusted life years
(QALYs). Economic evaluation estimates were incremental cost-effectiveness/cost-utility ratios
(ICER/ICUR).
Results: At 6-month follow-up treatment response and QALYs were highest in ACTonPainguided(44% and
0.280; mean costs=€6,945), followed by ACTonPainunguided(28% and 0.266; mean costs=€6,560) and
WLC(16% and 0.244; mean costs=€6,908). ACTonPainguided vs. WLC revealed an ICER/ICUR of 171 and
3,033, respectively, while ACTonPainunguided dominated WLC. At a willingness-to-pay of €0 the
probability of being cost-effective was 50% for ACTonPainguided and 66% for ACTonPainunguided. This
probability rose to 95% when society´s willingness-to-pay is 91,000€(ACTonPainguided) and
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€127,000(ACTonPainunguided) per QALY. ACTonPainguided vs. ACTonPainunguided revealed an ICER/ICUR
of 2,949 and 198,377.
Conclusions:
Depending on society´s willingness-to-pay ACTonPain is a potentially cost-effective adjunct to
established pain treatment, with ACTonPainunguided (vs.WLC) even leading to lower costs at better health
outcomes. However, uncertainty has to be taken into account. Direct comparison of the two interventions
indicates a preference for ACTonPainunguided under health economic aspects.
Trial Registration: German Clinical Trial Registration:DRKS00006183,
URL:https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00006183
Keywords: Chronic pain; internet- and mobile-based intervention; health economic evaluation; cost-
effectiveness; cost-utility
Strengths and limitations of this study
This is the first study that evaluates the (comparative) cost-effectiveness of a guided and an
unguided internet-based intervention for individuals with chronic pain.
In this study state-of-the-art statistical methods such as seemingly unrelated regression equations
models or non-parametric bootstrapping techniques were applied.
Results should be interpreted cautiously, as the study was not powered to statistically test health
economic differences.
As the costs and effects were evaluated over six months, no conclusions regarding the long-term
cost-effectiveness can be drawn.
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BACKGROUND
Chronic pain is highly prevalent [1–4] and associated with substantial decreases in quality of life [1, 5, 6]
and high economic costs for society [3, 7–9]. Evidence supports psychological interventions as one
approach for effectively treating patients with chronic pain [10]. Treatment based on cognitive-behavioral
therapy (CBT) or third-wave therapies, like the Acceptance and Commitment Therapy (ACT, a particular
form of CBT) have been shown to be effective for chronic pain patients [11, 12] and could show
acceptable results concerning cost-effectiveness [13]. However, accessibility and availability of treatment
is often restricted and up to 40% of individuals with chronic pain do not receive adequate pain
management [1, 14]. Internet- and mobile- based interventions (IMIs) are an effective, acceptable and
feasible way for providing psychological interventions [15, 16]. IMIs for chronic pain have been shown to
effectively improve pain interference compared to different control groups, such as standard (medical)
care, text-based material and mostly waitlist control condition (standardized mean difference (SMD)=.4
[17], SMD=−0.50 [18]).
IMIs can not only facilitate the access to psychological treatment, they also have the potential to reduce
treatment costs [19, 20], particularly by saving therapist resources. IMIs can be delivered as guided or
unguided self-help interventions, with both versions usually necessitating less therapist time compared to
traditional on-site therapies [21]. A relevant health care policy question is what amount of professional
human guidance is necessary in order to improve patients´ health, with guided IMIs being seemingly more
effective than unguided IMIs [21, 22]. However, as unguided IMIs can be delivered at lower costs per
participant, they might as well be an attractive option particularly given their high scalability on a
population level.
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To the best of our knowledge no randomized controlled trial (RCT) has investigated the (comparative)
cost-effectiveness of a guided and unguided IMI for chronic pain. However, Boer and colleagues found
that an IMI for chronic pain was cost-effective compared to a face-to-face group intervention (concerning
a one-point-improvement in a pain catastrophizing scale) [23]. Lin and colleagues recently finalized a
three arm RCT comparing a guided and unguided version of an Acceptance and Commitment Therapy
based IMI for chronic pain (ACTonPain) against a waitlist control group [24, 25]. Compared to the
waitlist control condition, ACTonPainguided showed significantly lower pain interference at nine weeks and
six months after randomization (d=0.58). Differences between ACTonPainunguided and the control group
and between both ACTonPain groups were not statistically significant [25].
The present paper provides the cost-effectiveness and cost-utility of ACTonPainguided/unguided compared to
the waitlist control condition as well as the comparative cost-effectiveness of ACTonPainguided/unguided.
METHODS
Study design and sample
This health-economic evaluation was conducted with a 6-month time horizon from the societal perspective
alongside a three-armed RCT to investigate the cost-effectiveness and cost-utility of ACTonPain. Full
details of the trial design can be found in the study protocol and the main outcome paper of this trial [24,
25]. The economic evaluation was conducted and reported in agreement with the Consolidated Health
Economic Evaluation Reporting Standards (CHEERS) statement [26] and the International Society For
Pharmacoeconomics and Outcomes Research (ISPOR) guidelines [27].
The study has been registered in the German Clinical Trial Register (DRKS00006183) and was approved
by the ethics committee of the University of Freiburg (reference: 387/14). In total, 302 participants were
recruited from 10/2014 until 08/2015 in German pain clinics, largescale organizations for chronic pain
(e.g. self-help groups), on websites and with assistance of a German health insurance company. Inclusion
criteria were 1) age 18 years or older, 2) chronic pain for at least six months, with 3) considerable intensity
(=at least Grade II in the Chronic Pain Grade [28]), 4) being medically suitable for participation in a
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chronic pain IMI, 5) sufficient knowledge of the German language, 6) sufficient computer and internet
literacy, and 7) having internet access. Exclusion criteria were 1) cancer-related pain, 2) ongoing or
planned psychological pain intervention within the forthcoming three months and 3) elevated risk of
suicide.
Randomization
All eligible participants who provided informed consent were asked to fill out the baseline assessment and
were randomly allocated to one of the three conditions ACTonPainguided, ACTonPainunguided and
waitlist. Permuted block randomization with variable block sizes (6, 9, 12) was performed by an
independent researcher not otherwise involved in the study using an automated, web-based randomization
program.
Interventions
ACTonPain is a German adaption of an IMI by Buhrman and colleagues [29] for individuals suffering
from chronic pain. The intervention is based on ACT and consists of seven modules, which include
information, metaphors, assignments, and mindfulness exercises. Both treatment conditions differ only in
the provision of guidance. Participants were advised to work on one module every week (~60 minutes). In
both intervention groups, participants had the option to receive daily automated text messages that
repeated content, reminded and motivated participants.
In ACTonPainguided trained and supervised eCoaches (psychologists) provided written feedback for each
module, which aimed at increasing participants' motivation and adherence. The total time of an eCoach
spent per participant was approximately 1.75 hours. Participants in the waitlist condition received the offer
to use ACTonPainunguided after the last follow-up assessment. Participants of all three trial arms had
unrestricted access to care-as-usual.
Outcome measures
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Assessment took place at baseline (T0), post-treatment (T1; nine weeks after randomization) and 6-month
follow-up (T2; six months after randomization). Outcomes were assessed by means of an online self-
report assessment using a secured internet-based platform (AES, 256-bit encrypted).
Treatment response
Main clinical outcome in the cost-effectiveness analysis was treatment response. This outcome was not
defined in the protocol paper. However, it was chosen to calculate a reliable and meaningful change in
pain interference according to the recommendations of the Initiative on Methods, Measurement, and Pain
Assessment in Clinical Trials (IMMPACT) [30] instead of a one-point change on the MPI, that would be
difficult to interpret.
According to the IMMPACT recommendations clinically important changes were identified with a
combination of a distribution-based approach (Pain Interference Scale of the Multidimensional Pain
Inventory MPI [31, 32]) and an anchor-based approach (Patient Global Impression of Change scale PGIC
[33]) [30]. First, participants with a change of 0.6 points (based on the scale’s standard deviation) on the
Pain Interference Scale of the MPI (range of the scale: 0-6) were identified as having minimal clinically
important changes [30]. Second, participants were identified, that rated their global improvement in the
PGIC [33] as “minimally, much or very much improved”. Participants who fulfilled both criteria were
classified as having achieved a clinically important change [30], defined as “treatment response”.
Quality-adjusted life years
The clinical outcome in the cost-utility analysis was quality-adjusted life years (QALYs) based on the
AQoL-8D [34] in the main analysis and the EQ5D-3L [35] in the sensitivity analysis. Utility scores are a
preference-based measure of quality of life that is normed by the value 1 meaning complete health and 0
meaning death [36].
The AQoL-8D comprises 35 items, which load on three physical (independent living, pain, senses) and
five psycho-social (mental health, happiness, coping, relationships, self-worth) dimensions [34]. The
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utility scores are scaled by SPSS algorithm for AQoL-8D utility model [34]. The AQoL-8D has been
shown as a reliable and valid instrument, suitable when psychosocial elements of health are the focus of
research [34], whereas utility weights are derived from the Australian adult population [37].
The EQ-5D-3L consists of five dimensions (mobility, self-care, usual activities, pain/discomfort, and
anxiety/depression), each of which is rated as causing ‘no’, ‘some’ or ‘extreme problems,’ and is a well
validated instrument [35, 38, 39]. Theoretically, the EQ-5D-3L generates 243 different health states.
Utility scores were calculated using the UK tariffs [40].
The AQoL-8D covers more dimensions that might be affected by chronic pain and shows a higher
sensitivity to mental health-related quality of life dimensions [41] compared to the EQ5D-3L.
Subsequently, and different to our protocol, this instrument was chosen for the main analyses[24].
QALY health gains for the 6-months period were estimated by calculating the area under the curve (AUC)
of linearly interpolated AQoL-8D and EQ-5D-3L utility scores [42].
Resource use and costing
The Trimbos and iMTA questionnaire for costs associated with psychiatric illness (TiC-P) [43, 44] was
adapted to the German health care system and to the healthcare use of individuals with chronic pain. It
was used to assess the direct and indirect costs of the past three month at T0 and T2. Costs were expressed
in Euros (€) for the reference year 2015 (index factor 1.003 and 1.01 for outpatient medical service,
respectively) referring to the German consumer price index [45] (list of unit cost prices see Table 1). To
calculate the 6-month accumulated per-participants costs, the area under curve (AUC) method was used
by linearly interpolating 3-month costs (measured at T0 und T2) to cover the full period of six months
[42].
𝐴𝑈𝐶 = (𝐶𝑜𝑠𝑡𝑠 𝑇0
3 +𝐶𝑜𝑠𝑡𝑠 𝑇2
32 ) ∗ 3 + 𝐶𝑜𝑠𝑡𝑠 𝑇2
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Table 1: List of unit cost prices
Sector Unit Category 2015 (in Euro)
Out
patie
nt m
edic
al se
rvic
e /
outp
atie
nt se
ctor
Euro/contact
PhysicianGynecologistOrthopedistSpecialists for internal medicineOphthalmologistDermatologistETN specialistSurgeonUrologistNeurologistPsychotherapistDentist
20.81 31.62 25.82 64.25 36.96 19.58 28.12 44.59 25.20 47.02 79.42 55.24
remedies Logopedics / speech therapyPhysiotherapyErgotherapy / occupational therapyPodiatry / podologyMean remedies
41.02 17.50 39.45 29.13 31.77
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hospitals Euro/day
Completely stationary normal wardCompletely stationary intensive careCompletely stationary psychiatrySemi-stationary general hospitalSemi-stationary psychiatry
648.11 1,424.60 348.26 421.27 226.37
rehabilitation Euro/day OutpatientInpatient
49.43 138.19
opportunitiy costs Euro/houropportunity costs (free time) opportunity costs (work)substitution costs for informal care
21.77 31.89 18.97
Note: Prices for outpatient medical service/outpatient sector were calculated fort the year 2013; all other prices for the year 2014 [46, 47] and adjusted by the German consumer price index for 2015 [45]. ETN specialist, Ear, nose, and throat specialist.
Direct medical costs
Healthcare costs (e.g. out- and inpatient care) were calculated according to the German guideline of Bock
and colleagues [46, 47]. The costs of therapeutic appliances (that were not listed in Bock and colleagues
[46, 47]) and medication were obtained from the Lauer-Taxe [48].
Patient and family costs
Self-reported out-of-pocket expenses and direct non-medical costs (travel expenses, opportunity costs,
domestic help) were assessed. Participants reported the cost of travelling by bus or taxi. If not stated, each
kilometer was valued at €0.30. Opportunity costs (i.e., time spent at the practitioners waiting room) were
estimated at €21.77 per hour. Costs of informal care were valued using a shadow price of €18.97 per hour
[47].
Indirect costs
Indirect costs included productivity losses caused by absenteeism and presenteeism. Absenteeism costs
were calculated according to the human capital approach [49]. Self-reported lost work days were
multiplied by the corresponding gross average of participants’ income per day. To calculate presenteeism
costs, participants reported the number of days of reduced efficiency at work. These days were weighted
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by an inefficiency score. Productivity losses from unpaid work (i.e. domestic help from family members)
were valued using a shadow price of €18.97 per hour [47].
Intervention costs
Intervention costs of ACTonPainguided (€299) and ACTonPainunguided (€69) were based on actual market
prices for (un)guided interventions with a similar amount of modules that contain all costs for developing
and hosting the intervention (https://geton-institut.de/).
Statistical analysis
This study was not powered to statistically test differences in health economic outcomes. Therefore, we
took a probabilistic decision-making approach for health-economic inferences [50], that aims at informing
decision makers on probabilities rather than statistical significance. There was no need to discount costs or
outcomes as the time frame for the study was six months.
All analyses were conducted according to the intention-to-treat principle. All participants completed T0.
Missing clinical outcome data was imputed using the expectation maximization algorithm in Statistical
Package for the Social Sciences (SPSS, version 20). Analyses of clinical outcomes were conducted and
reported elsewhere [25] in accordance with the CONSORT 2010 Statement [51].
Missing cost data was imputed using the regression imputation procedure in Stata version 13 [52].
Predictors of cost data and dropout were identified by logistic regression analysis and were used to obtain
the most likely values of the missing cost data. At baseline, AQoL-utilities differed between groups
(ACTonPainguided: M=0.496, SD=0.16; ACTonPainunguided: M=0.485, SD=0.17; waitlist: M=0.463,
SD=0.14). Therefore, baseline adjustments were made in further calculations.
We tested group differences in treatment response using the chi-squared test and the Kruskall-Wallis test
for QALYs both followed by post-hoc comparisons (Bonferroni and Dunn´s test, respectively).
In the cost-effectiveness analyses, the outcome estimate is the incremental cost-effectiveness ratio (ICER),
where incremental costs over the 6-month period are divided by incremental effects (treatment response or
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QALYs): ICER=(CostsIG–CostsCG)/(EffectsIG–EffectsCG) subscripted with IG for the two intervention
groups and CG for the comparison groups. Different to the protocol [24], ICERs are reported for a 6-
month horizon (baseline data; T0 and 6-month follow-up; T2) and not based on pre-post (T0 and post-
treatment; T1). As participants are asked for their health care utilization during the last three months, the
TiC-P can only be evaluated appropriately at T0 and T2 (as T1 assessments are conducted nine weeks
after randomization).
Non-parametric bootstrapping by resampling patient-level data with 5,000 replications was used to take
into account the sampling uncertainty of the ICER estimates. Seemingly unrelated regression equations
models were bootstrapped to allow for correlated residuals of the cost and effect equations. Bootstrapping
was used to obtain 95% confidence intervals for the ICERs based on the percentile method, since
parametric techniques are inappropriate for use on skewed variables and ratios [50].
The bootstrapped ICERs were plotted on a cost-effectiveness plane. In addition, a cost-effectiveness
acceptability curve was graphed to assess the probability that the intervention is cost-effective relative to
the comparator condition given varying willingness-to-pay (WTP) ceilings. In order to increase readability
of the direct comparison ACTonPainguided vs. ACTonPainunguided the inverse cost-effectiveness acceptability
curve (ACTonPainunguided vs. ACTonPainguided) was additionally plotted. All analyses were performed using
Stata version 13 [52].
Sensitivity analysis
We tested the robustness of the outcomes of the main analysis in a sensitivity analysis. Therefore, we used
the EQ-5D-3L as a widely used instrument for calculating QALYs. As baseline EQ5D-utilities differed
between groups (ACTonPainguided: M=0.469, SD=0.32; ACTonPainunguided: M=0.436, SD=0.31; waitlist:
M=0.494, SD=0.3), baseline adjustment was made in the sensitivity analyses.
Patient and public involvement
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No patients or public were involved in developing the research question or the outcome measures, nor
were they involved in developing plans for design or implementation of the study. Possible negative
effects were assessed as well as the satisfaction with the intervention (for results, see [25]). The results of
the research will be disseminated to those study participants who wished to be notified.
RESULTS
Sample characteristics
The overall sample size was 302. Due to missing assessments the dropout rate was 25.8% at 6-month
follow-up (ACTonPainguided: 33/100; ACTonPainunguided: 35/101; waitlist: 10/101). At 6-month follow up,
dropout rates differed significantly between groups (χ2(2)=20.17, p<.001). Pairwise comparison revealed
significant differences for ACTonPainguided vs. waitlist (t(1)=-3.85, p<.001) and ACTonPainunguided vs.
waitlist (t(1)=-4.14, p<.001). Study dropout was not associated with baseline pain interference or socio-
demographic factors.
The average participant was female, 52 years of age, with an above average level of education, employed
and was already treated for chronic pain. Detailed participants’ characteristics and the CONSORT
flowchart have already been reported elsewhere [25].
Outcomes
Table 2 shows treatment response and QALY outcomes as well as group differences. At 6-month follow-
up, treatment response differed significantly between groups (ACTonPainguided: 44/100; ACTonPainunguided:
28/101; waitlist: 16/101). Pairwise comparison revealed significant differences for ACTonPainguided vs.
waitlist and ACTonPainguided vs. ACTonPainunguided but not for ACTonPainunguided vs. waitlist. Between-
group differences in AQoL-8D QALY gains were statistically significant. Pairwise comparison revealed
significant differences only for ACTonPainguided vs. waitlist. Incremental EQ5D-3L QALY gains did not
differ significantly between study groups.
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Table 2. Treatment response and quality-adjusted life-year (QALY) outcomes and group differences at 6-month follow up.
ACTonPain guided (n = 100)
ACTonPain unguided (n = 101)
WLC group (n = 101) Test statistic
Mean (SD) Mean (SD) Mean (SD) χ2 (df=2) Post-hoc test c: pTreatment response (pain interference) 0.44 (0.05) 0.277 (0.04) 0.158 (0.04) 19.44 a <001ACTonPain guided vs. WLC group t(1)=4.52 <.001ACTonPain unguided vs. WLC group t(1)=1.91 .17ACTonPain guided vs. unguided t(1)=2.61 .03QALYAQoL-8D 0.280 (0.08) 0.266 (0.09) 0.244 (0.08) 9.45 b .009ACTonPain guided vs. WLC group Z=-3.07 .003ACTonPain unguided vs. WLC group Z=-1.61 .16ACTonPain guided vs. unguided Z=-1.47 .21EQ5D-3L 0.274 (0.12) 0.255 (0.12) 0.253 (0.13) 2.17 b .34WLC group, waitlist control group; SD, standard deviation; df, degrees of freedom; QALY, quality-adjusted life-yeara Chi-squared test b Kruskall-Wallis H testc Post-hoc test for treatment response: Bonferroni pairwise comparison; Post-hoc test for QALY: Dunn´s test
Costs
At baseline, mean total costs were €3,233 in ACTonPainguided, €3,724 in ACTonPainunguided and €3,570 in
the waitlist group. The 6-month accumulated per-participants costs by study condition are presented in
Table 3. ACTonPainguided showed the highest mean total costs (€6,945), followed by the waitlist group
(€6,908) and ACTonPainunguided (€6,560). Mean direct costs were the highest in the guided group, followed
by the unguided group and waitlist. The opposite order was found for the indirect costs. Medication,
domestic help and opportunity costs were major cost drivers. Productivity losses produced the highest cost
differences between the intervention groups and waitlist of -€871 (ACTonPainguided vs. waitlist) and -€721
(ACTonPainunguided vs. waitlist).
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Table 3. 6-month accumulated per-participants costs (in €) by condition (based on intention-to-treat sample, N = 302).
ACTonPain guided (n = 100)
ACTonPain unguided (n = 101)
WLC group (n = 101)
Incremental costs
Difference, €
Mean, € (SD) Mean, € (SD) Mean, €
(SD)
ACTonPain guided vs. WLC
ACTonPain unguided vs. WLC
ACTonPain guided vs. unguided
Intervention 299 (-) 69 (-) 0 (-) 299 69 230Direct medical costsHealth care costs Medical specialist 576 (478) 511 (381) 511 (382) 65 0 65 Mental health care 212 (431) 181 (397) 258 (455) -46 -77 31 Other medical specialist a
369 (515) 357 (435) 406 (576) -37 -49 12
In-patient care (hospital)
198 (479) 173 (369) 141 (420) 57 32 25
Day care 147 (687) 122 (381) 306 (1,584) -159 -184 25 Rehabilitation 190 (794) 134 (507) 191 (773) -1 -57 56 Medication 1,092 (2,748) 784 (1,438) 660 (1,638) 432 124 308 Therapeutic appliances 65 (139) 86 (222) 46 (96) 19 40 -21Direct non-medical costs Patient and family costs Travel 131 (229) 105 (150) 101 (100) 30 4 26 Domestic help 1,297 (4,064) 1,147 (1,936) 840 (1,490) 457 307 150 Opportunity costs b 1,553 (1,965) 1,925 (3,251) 1,759 (3,116) -206 166 -372Indirect costsProductivity losses Absenteeism 517 (1,647) 647 (1,979) 1,133 (3,333) -616 -486 -130 Presenteeism 300 (740) 320 (774) 555 (1,360) -255 -235 -20
Total direct costs 5,829 (7,129) 5,525 (4,959) 5,220 (5,133) 611 306 305Total indirect costs 817 (1,978) 966 (2,283) 1,688 (3,735) -871 -721 -150Total societal costs 6,945 (7,327) 6,560 (5,549) 6,908 (6,279) 39 -346 385WLC group, waitlist control groupa i.e. physiotherapist, occupational therapistb i.e. for waiting time before treatment
Health-economic evaluation
Table 4 shows the incremental costs, effects and cost-effectiveness ratios for the main analysis and the
sensitivity analysis.
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Table 4. Results of the main and sensitivity analyses (based on 5,000 bootstrap simulations).
AnalysisACTonPain guided vs. WLC group
Incremental costs, €(95% CI)
Incremental effects(95% CI)
MeanICER(95% CI)
Distribution over the ICER planeNE NW SE SW
Cost-effectiveness, treatment response (MPI and PGIC)
6(-916-953)
0.14(0.08-0.2)
171(-6,671-8,260)
50% - 50% -
Cost-utilityAQoL QALYs
6(-916-953)
0.01(0.005- 0.015)
3,033(-92,924- 114,325)
50% - 50% -
Sensitivity analysis EQ5D QALYs 6
(-916-953)0.014(0.004- 0.024)
4726 (-69,407- 122,314)
50% - 50% -
AnalysisACTonPain unguided vs. WLC group
Incremental costs, €(95% CI)
Incremental effects(95% CI)
MeanICER(95% CI)
Distribution over the ICER planeNE NW SE SW
Cost-effectiveness, treatment response (MPI and PGIC)
-352(-1,968-1,272)
0.12(0.006-0.232)
ACTonPain unguided dominates WLC
32% 1% 66% 1%
Cost-utility AQoL QALYs
-352(-1,968-1,272)
0.013(0.002-0.024)
ACTonPain unguided dominates WLC
32% 1% 66% 1%
Sensitivity analysis EQ5D QALYs -352
(-1,968-1,272)
0.017 (-0.005- 0.04)
ACTonPain unguided dominates WLC
30% 4% 64% 3%
AnalysisACTonPain guided vs. ACTonPain unguided
Incremental costs, €(95% CI)
Incremental effects(95% CI)
MeanICER(95% CI)
Distribution over the ICER planeNE NW SE SW
Cost-effectiveness, treatment response (MPI and PGIC)
388(-1,416-2,185)
0.164(0.034-0.29)
2,949(-11,097-25,276)
65% - 35% -
Cost-utility AQoL QALYs
388(-1,416-2,185)
0.008(-0.003-0.019)
198,377a
60% 5% 33% 2%
Sensitivity analysis EQ5D QALYs 388
(-1,416-0.01 (-0.01- 0.031)
114,858 a
53% 12% 31% 4%
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2,158)WLC group, waitlist control group; MPI, Pain Interference Scale of the Multidimensional Pain Inventory; PGIC, Patient Global Impression of Change scale; 95% CI, 95% confidence interval; EQ-5D QALYs, Quality-adjusted life years based on EuroQol; ICER, incremental cost-effectiveness ratio; NE, northeast quadrant; NW, northwest quadrant; SE, southeast quadrant; SW, southwest quadrant.aA dependably accurate 95% confidence interval for this distribution cannot be defined because there is no line through the origin that excludes α/2 of the distribution[53].
Cost-effectiveness
The cost-effectiveness planes and acceptability curves, representing the 5,000 bootstrap replications, are
shown in Figure 1(a,b,c) and 2(a,b). ACTonPainguided showed the same and ACTonPainunguided a higher
potential of being cost-effective compared to waitlist at a WTP of €0 (ACTonPainguided 50%,
ACTonPainunguided 66%). The probability of ACTonPainguided being more cost-effective compared to
waitlist increased up to 70% at a WTP of €1,738 and to 95% at a WTP of €6,490 for an additional
treatment response, and for ACTonPainunguided to 70% at a WTP of €660 and to 95% at a WTP of €13,460.
The probability that ACTonPainguided is more cost-effective than ACTonPainunguided was 35% at a WTP of
€0 for an additional treatment response. When society’s WTP increases up to €5,535 or €17,170 this
probability rises to 70% or 95%, respectively. The break even point (where ACTonPainguided and
ACTonPainunguided have the same possibility of being cost-effective at same costs) is at €2,188 (see Figure
2b).
- Figure 1-
- Figure 2-
Cost-utility
Cost-effectiveness planes and acceptability curves that refer to cost-utility are shown in figure 1(d,e,f) and
2(c,d). ACTonPainguided showed the same and ACTonPainunguided a higher potential of being cost-effective
compared to waitlist at a WTP of €0 (50% and 66%, respectively). The interventions’ probability of being
more cost-effective compared to waitlist increased up to 70% and to 95% at a WTP of €24,415 and
€91,000, respectively, in ACTonPainguided and €6,130 (70%) and €127,000 (95%) in ACTonPainunguided for
one additional QALY. The probability that ACTonPainguided is more cost-effective than ACTonPainunguided
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was 31% at a WTP of €0 for one additional QALY. When society’s WTP increases up to €113,550 this
probability rises to 70% and stagnates on this level. The break-even point is at €41,350 (see Figure 2d).
Sensitivity analysis
After non-parametric bootstrapping, using the EQ-5D-3L resulted in larger incremental QALY gains in all
comparisons compared to the results using the AQoL-8D (see table 4).
At a WTP of €0 the probability of ACTonPainguided of being cost-effective compared to waitlist was 50%.
The probability of ACTonPainunguided of being cost-effective compared to waitlist was 64% at a WTP of
€0. ACTonPainguided vs. ACTonPainunguided resulted in a probability of being cost-effective of 31% at a
WTP of €0.
DISCUSSION
Comparing both ACTonPain interventions to waitlist and by taking uncertainty into account,
ACTonPainunguided can be judged as a potentially cost-effective intervention as it dominates WLC by
leading to higher QALY gains and more individuals with a treatment response at lower costs.
However, when assuming that an intervention should reach a likelihood of being cost-effective of 95% or
greater it has to be considered that the WTP would have to be €13,460 for treatment response and
€127,000 for a QALY gain. Therefore, the judgement of whether the intervention is cost-effective or not
ultimately depends on the society’s WTP for treatment response or a QALY gain, respectively.
ACTonPainguided also causes better results in the main outcome parameters, but at (slightly) higher costs
with ICERs of 171 (treatment response) and 3,033 (AQoL QALY gains). The probability of being cost-
effective at a WTP of €0 compared to waitlist is higher in ACTonPainunguided, for both, treatment response
and QALYs gained (66%) than in ACTonPainguided (50%).
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However, when comparing the costs that would have to be invested by using ACTonPainguided (compared
to waitlist) for a QALY gained (€3,033) to the only official WTP threshold stated by the National Institute
for Health and Clinical Excellence (NICE) of £20,000 to £30,000 [54] (~ €22,647 - €33,971; conversion
according to the European Central bank [55]), this intervention would also be categorized as a potentially
cost-effective treatment. Here again, uncertainty has to be considered as well as the required WTP for a
likelihood of being cost-effective of 95% of €6,490 (treatment response) and €91,000 (QALY gain).
The direct comparison of ACTonPainguided and ACTonPainunguided shows more treatment responders and
higher QALY gains for the guided version, but at higher costs. According to the NICE guidelines costs are
far above the WTP threshold for a QALY gain and would thus be judged as probably not cost-effective. In
terms of QALYs gained, the guided version only reaches a probability of 31% of being cost-effective at a
WTP of €0 and even with rising WTP threshold, the probability does not increase much.
The results of the sensitivity analyses revealed slightly higher incremental QALY gains by using the
EQ5D-3L compared to the AQoL-8D but overall conclusions are the same as in the main analyses.
Estimated EQ-5D utility scores for one year ranged from 0.50 to 0.54, what appears rather low compared
to national EQ-5D estimates for (back) pain from other countries (e.g. 0.74-0.79 [56, 57]). Lower
estimates in the current study could have occurred due to the sociodemographic properties of this study
sample, as participants were predominately women (84%), reported comorbid medical or mental
conditions (57% and 39%, respectively) and the back was the most often reported pain location (34%)
[25]. Several studies showed that the mentioned characteristics (female sex, musculoskeletal and mental
disorders) are associated with lower quality of life scores [56–58]. Furthermore, Burström et al. (2001)
reported in their study that participants with low back pain showed quality of life weights of 0.55 [58],
what is comparable to the sample in the current study.
The conclusion of ACTonPain being cost-effective are in line with a recent study and a review about the
cost-effectiveness of IMIs for depression [23, 59]. The guided IMI for chronic pain of Boer and colleagues
revealed an ICER of 40 (defined as cost savings of €40) for an one-point improvement in a pain
catastrophizing scale compared to a face-to-face group intervention, while QALYs were not reported [23].
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ACTonPainguided reached higher ICERs for the clinical outcome pain interference (171 compared to
waitlist group and 2,949 compared to the unguided group). However, these values were calculated for
treatment response in terms of pain interference and therefore, a meaningful change and not for a one-
point improvement on the scale. In a systematic review, IMIs that were classified as cost-effective were all
guided and showed probabilities of being cost-effective between 28% and 49% at a WTP of €0 for a
QALY gained, whereas ACTonPainguided and the unguided version even reached higher probabilities at
this WTP level (50% and 66%, respectively). Thus, integrating psychological e-health approaches in pain
management programs might even be more promising from an economical point of view when compared
to the well-established area of depression e-health care.
The higher direct costs over a 6-month period in both intervention groups compared to waitlist might be
explained by higher or stable health care utilization similar to findings in a previous study on the costs of
established depression treatments [60]. However, research indicates that indirect rather than direct costs
represent the majority of overall costs [61, 62], where ACTonPain seemingly has its core advantage. Mean
indirect costs over the 6-month period were almost half as high in the intervention groups compared to
waitlist, regarding both absenteeism and presenteeism.
Next to the questions of whether ACTonPain is cost-effective compared to waitlist and whether it should
rather be provided guided or unguided, it would be of interest how ACTonPain performs compared to
established medical, psychological, physiotherapeutical, and surgical treatments that result in high direct
costs [63–66]. However, surprisingly little is known about the cost-effectiveness of these established pain
treatments. In two reviews it was highlighted, that interdisciplinary pain rehabilitation programs are more
cost-effective or produce lower costs than interventions such as surgery and conservative care [67, 68].
For individuals with low back pain it was concluded that interdisciplinary rehabilitation, exercise,
acupuncture, spinal manipulation and CBT are potentially cost-effective [69]. A further systematic review
focused on economic evaluations of third-wave CBT therapies (including ACT), were available ICERs
ranged from -€19,300 (National Health Service perspective, converted into Euro [55]) to €56,637 (societal
perspective) per QALY gained [13]. When compared to waitlist the ICERs based on the AQoL-8D in this
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study were €3,033 and a negative ICER (indicating dominance of the unguided intervention over WLC)
per QALY gained. Thus, it seems safe to argue that ACTonPain, as an example of an innovative IMI for
the treatment of chronic pain, is effective [25] and could be an cost-effective intervention. A comparison
across treatment approaches for chronic pain, however, cannot be provided as the evidence base for the
cost-effectiveness of established pain treatments is rather weak and the comparability of results across
studies is limited due to very heterogeneous methods across trials [70].
Limitations
First, when interpreting the results, it has to be considered that the study was not powered to statistically
test health economic differences. Second, the costs and effects were evaluated over six months. Therefore,
no conclusions regarding the long-term cost-effectiveness can be drawn. Furthermore, costs between
randomization and three months after randomization were calculated with the area under the curve
method. This is just an estimate and not a representation of the actual costs incurred during this period.
Fourth, costs were assessed via self-report. However, as the questionnaire used in this study is a valid
instrument to recall periods up to three months [71], the impact of this bias on results is limited. Finally,
the usage of multiple imputation techniques is frequently recommended (e.g. predictive mean matching
[72]. We used a single imputation approach as it was done in the main (effectiveness) analysis [25] that
might not truly reflect missing data uncertainty. However, the comparison with cost and QALY outcomes
of complete case analysis revealed only small differences, indicating that the risk of implausible values
due to single imputation in this evaluation is low [73]. Furthermore, by using the non-parametric
bootstrapping, sampling was considered.
Implications and future research
For patients with chronic pain, IMIs might become an important alternative to established interventions.
IMIs can expand treatment options for people, whose physical impairment or location makes access to
relevant care difficult [19]. Findings from this health economic evaluation study show that both versions
of ACTonPain have the potential of being cost-effective, with the unguided version even leading to lower
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costs (compared to WLC). However, uncertainty should be taken into account. The decision whether to
choose the guided or unguided version is a public health issue and strongly depends on whether to mainly
focus on patients´ health or societies´ resources. Under health economic aspects ACTonPainunguided should
be the preferred intervention, especially when considering the intention of treatment implementation into
the health care system and scaling up mental health care for pain patients.
Future research should especially focus on conducting methodologically sound studies that are powered to
statistically test health economic differences. Furthermore, long-term follow-up studies and evaluation of
(comparative) cost-effectiveness of different guidance formats of IMIs, particularly of ACTonPain, and
established pain treatments are needed. Moreover, future studies should examine ACTonPain as integrated
part of multi-component pain programs and aim to dismantle the ingredients that are effective and cost-
effective in those complex approaches.
DECLARATIONS
Funding
This research received no specific grant from any funding agency in the public, commercial or not-for-
profit sectors. The article processing charge was funded by the German Research Foundation (DFG) and
the Albert-Ludwigs University Freiburg in the funding programme Open Access Publishing.
Competing interests
Two of the authors of the manuscript were involved in the development of ACTonPain (JL and HB). HB
and DDE are consultants for several stakeholders (insurance companies, ministries, psychotherapy
chambers, companies). DDE is part of the GET.ON Institut GmbH, which aims at implementing evidence-
based internet- and mobile based interventions into routine care. SP, CB, FK and DL declare that they
have no competing interests.
Data sharing statement
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The datasets used and/or analyzed during the current study are available from the corresponding author on
reasonable request.
Authors’ contributions
JL and HB initiated the randomized control trial for this health economic evaluation. SP, FK, CB, DL and
DDE contributed to the design of this health economic evaluation. SP, DL, FK and CB contributed to the
data analysis. SP had full access to all the data in the study and had responsibility for the decision to
submit for publication. SP wrote the draft of the manuscript. All authors contributed to the further writing
and approved the final version of the manuscript.
Acknowledgements
We would like to thank Yannik Terhorst and Nelli Hirschauer for their assistance in data processing.
Figure Legends
Figure 1. Cost-effectiveness planes of all group comparisons based on 5,000 replicates of the
incremental cost-effectiveness ratio using mean differences in costs from a societal perspective and
mean incremental effects (treatment response: a, b, c; QALYs: d, e, f)
Figure 2. Cost-effectiveness acceptability curves of all group comparisons based on 5,000 replicates
of the incremental cost-effectiveness ratio using mean differences in costs from a societal
perspective and mean incremental effects (treatment response: a, b; QALYs: c, d). For the
comparison of ACTonPain guided vs. ACTonPain unguided the inverse function (ACTonPain
unguided vs. ACTonPain guided) was included.
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60. Wang PS, Simon G, Kessler RC. The economic burden of depression and the cost-effectiveness of treatment. International journal of methods in psychiatric research. 2003;12:22–33.
61. Juniper M, Le TK, Mladsi D. The epidemiology, economic burden, and pharmacological treatment of chronic low back pain in France, Germany, Italy, Spain and the UK: a literature-based review. Expert opinion on pharmacotherapy. 2009;10:2581–92.
62. Dagenais S, Caro J, Haldeman S. A systematic review of low back pain cost of illness studies in the United States and internationally. The spine journal. 2008;8:8–20.
63. Druss BG, Marcus SC, Olfson M, Pincus HA. The Most Expensive Medical Conditions In America. Health Affairs. 2002;21:105–11. doi:10.1377/hlthaff.21.4.105.
64. Katz JN. Lumbar disc disorders and low-back pain: socioeconomic factors and consequences. JBJS. 2006;88:21–4.
65. Smith M, Davis MA, Stano M, Whedon JM. Aging baby boomers and the rising cost of chronic back pain: secular trend analysis of longitudinal Medical Expenditures Panel Survey data for years 2000 to 2007. J Manipulative Physiol Ther. 2013;36:2–11. doi:10.1016/j.jmpt.2012.12.001.
66. Ma VY, Chan L, Carruthers KJ. Incidence, prevalence, costs, and impact on disability of common conditions requiring rehabilitation in the United States: stroke, spinal cord injury, traumatic brain injury, multiple sclerosis, osteoarthritis, rheumatoid arthritis, limb loss, and back pain. Arch Phys Med Rehabil. 2014;95:986-995.e1. doi:10.1016/j.apmr.2013.10.032.
67. Turk DC. Clinical Effectiveness and Cost-Effectiveness of Treatments for Patients With Chronic Pain. The Clinical Journal of Pain. 2002;18:355–65. doi:10.1097/00002508-200211000-00003.
68. Phillips CJ. Economic burden of chronic pain. Expert Rev Pharmacoecon Outcomes Res. 2006;6:591–601. doi:10.1586/14737167.6.5.591.
69. Lin C-WC, Haas M, Maher CG, Machado LAC, van Tulder MW. Cost-effectiveness of guideline-endorsed treatments for low back pain: a systematic review. Eur Spine J. 2011;20:1024–38. doi:10.1007/s00586-010-1676-3.
70. Furlan AD, Yazdi F, Tsertsvadze A, Gross A, van Tulder M, Santaguida L, et al. A systematic review and meta-analysis of efficacy, cost-effectiveness, and safety of selected complementary and alternative medicine for neck and low-back pain. Evid Based Complement Alternat Med. 2012;2012:953139. doi:10.1155/2012/953139.
71. van den Brink M, van den Hout WB, Stiggelbout AM, Putter H, van de Velde CJH, Kievit J. Self-reports of health-care utilization: diary or questionnaire? International journal of technology assessment in health care. 2005;21:298–304.
72. Faria R, Gomes M, Epstein D, White IR. A guide to handling missing data in cost-effectiveness analysis conducted within randomised controlled trials. Pharmacoeconomics. 2014;32:1157–70. doi:10.1007/s40273-014-0193-3.
73. Vroomen JM, Eekhout I, Dijkgraaf MG, van Hout H, Rooij SE de, Heymans MW, Bosmans JE. Multiple imputation strategies for zero-inflated cost data in economic evaluations: which method works best? The European Journal of Health Economics. 2016;17:939–50.
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Figure 1. Cost-effectiveness planes of all group comparisons based on 5,000 replicates of the incremental cost-effectiveness ratio using mean differences in costs from a societal perspective and mean incremental
effects (treatment response: a, b, c; QALYs: d, e, f).
122x63mm (300 x 300 DPI)
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Figure 2. Cost-effectiveness acceptability curves of all group comparisons based on 5,000 replicates of the incremental cost-effectiveness ratio using mean differences in costs from a societal perspective and mean incremental effects (treatment response: a, b; QALYs: c, d). For the comparison of ACTonPain guided vs.
ACTonPain unguided the inverse function (ACTonPain unguided vs. ACTonPain guided) was included.
422x274mm (300 x 300 DPI)
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Additional file 1 – CHEERS checklist Section/item Item
No Recommendation Reported on page
No
Title and abstract
Title 1 Identify the study as an economic evaluation or use more specific terms such as “cost-effectiveness analysis”, and describe the interventions compared.
Page 1
Abstract 2 Provide a structured summary of objectives, perspective, setting, methods (including study design and inputs), results (including base case and uncertainty analyses), and conclusions.
Page 2 and 3 (the sensitivity analysis is not mentioned in the abstract due to limited words)
Introduction
Background and objectives
3 Provide an explicit statement of the broader context for the study. Present the study question and its relevance for health policy or practice decisions.
Page 4 and 5
Methods
Target population and subgroups
4 Describe characteristics of the base case population and subgroups analysed, including why they were chosen.
Page 5
Setting and location 5 State relevant aspects of the system(s) in which the decision(s) need(s) to be made.
Page 5
Study perspective 6 Describe the perspective of the study and relate this to the costs being evaluated.
Page 5, 8, 9 and 10
Comparators 7 Describe the interventions or strategies being compared and state why they were chosen.
Page 6
Time horizon 8 State the time horizon(s) over which costs and consequences are being evaluated and say why appropriate.
Page 6 and 7
Discount rate 9 Report the choice of discount rate(s) used for costs and outcomes and say why appropriate.
Page 10
Choice of health outcomes
10 Describe what outcomes were used as the measure(s) of benefit in the evaluation and their relevance for the type of analysis performed.
Page 6, 7 and 8
Measurement of effectiveness
11a Single study-based estimates: Describe fully the design features of the single effectiveness study and why the single study was a sufficient source of clinical effectiveness data.
Page 4 and 5
11b Synthesis-based estimates: Describe fully the methods used for identification of included studies and synthesis of clinical effectiveness data.
N/A
Measurement and valuation of preference based outcomes
12 If applicable, describe the population and methods used to elicit preferences for outcomes.
Page 7
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Section/item Item No
Recommendation Reported on page No
Estimating costs and resources
13a Single study-based economic evaluation: Describe approaches used to estimate resource use associated with the alternative interventions. Describe primary or secondary research methods for valuing each resource item in terms of its unit cost. Describe any adjustments made to approximate to opportunity costs.
Page 8, 9 and 10, Table 1
13b Model-based economic evaluation: Describe approaches and data sources used to estimate resource use associated with model health states. Describe primary or secondary research methods for valuing each resource item in terms of its unit cost. Describe any adjustments made to approximate to opportunity costs.
N/A
Currency, price date and conversion
14 Report the dates of the estimated resource quantities and unit costs. Describe methods for adjusting estimated unit costs to the year of reported costs if necessary. Describe methods for converting costs into a common currency base and the exchange rate.
Page 8
Choice of model 15 Describe and give reasons for the specific type of decision-analytical model used. Providing a figure to show model structure is strongly recommended.
N/A
Assumptions 16 Describe all structural or other assumptions underpinning the decision-analytical model.
N/A
Analytical methods 17 Describe all analytical methods supporting the evaluation. This could include methods for dealing with skewed, missing, or censored data; extrapolation methods; methods for pooling data; approaches to validate or make adjustments (such as half cycle corrections) to a model; and methods for handling population heterogeneity and uncertainty.
Page 10, 11 and 12
Results
Study parameters 18 Report the values, ranges, references, and, if used, probability distributions for all parameters. Report reasons or sources for distributions used to represent uncertainty where appropriate. Providing a table to show the input values is strongly recommended.
Page 12-17, Table 2 and 4
Incremental costs and outcomes
19 For each intervention, report mean values for the main categories of estimated costs and outcomes of interest, as well as mean differences between the comparator groups. If applicable, report incremental cost-effectiveness ratios.
Page 13; Table 3
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Section/item Item No
Recommendation Reported on page No
Characterising uncertainty
20a Single study-based economic evaluation: Describe the effects of sampling uncertainty for the estimated incremental cost and incremental effectiveness parameters, together with the impact of methodological assumptions (such as discount rate, study perspective).
Page 16 and 17 and Figure 1 and 2
20b Model-based economic evaluation: Describe the effects on the results of uncertainty for all input parameters, and uncertainty related to the structure of the model and assumptions.
N/A
Characterising heterogeneity
21 If applicable, report differences in costs, outcomes, or cost-effectiveness that can be explained by variations between subgroups of patients with different baseline characteristics or other observed variability in effects that are not reducible by more information.
N/A
Discussion
Study findings, limitations, generalisability, and current knowledge
22 Summarise key study findings and describe how they support the conclusions reached. Discuss limitations and the generalisability of the findings and how the findings fit with current knowledge.
Page 17-21
Other
Source of funding 23 Describe how the study was funded and the role of the funder in the identification, design, conduct, and reporting of the analysis. Describe other non-monetary sources of support.
Page 21
Conflicts of interest 24 Describe any potential for conflict of interest of study contributors in accordance with journal policy. In the absence of a journal policy, we recommend authors comply with International Committee of Medical Journal Editors recommendations.
Page 21
N/A, Not applicable
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For peer review onlyA guided and unguided internet- and mobile-based
intervention for chronic pain: Health economic evaluation alongside a randomized controlled trial
Journal: BMJ Open
Manuscript ID bmjopen-2018-023390.R3
Article Type: Research
Date Submitted by the Author: 19-Dec-2018
Complete List of Authors: Paganini, Sarah; Albert-Ludwigs University Freiburg, Department of Sports and Sport Science, Sport Psychology; Albert-Ludwigs University Freiburg, Department of Rehabilitation Psychology and Psychotherapy, Institute of PsychologyLin, Jiaxi; Albert-Ludwigs University Freiburg, Department of Sports and Sport Science, Sport PsychologyKählke, Fanny; Friedrich-Alexander University of Erlangen-Nuremberg, Department of Clinical Psychology and PsychotherapyBuntrock, Claudia; Friedrich-Alexander-Universitat Erlangen-Nurnberg, Clinical Psychology and PsychotherapyLeiding, Delia; RWTH Aachen University, Department of Psychiatry, Psychotherapy and PsychosomaticsEbert, David; Friedrich-Alexander University Erlangen Nuremberg, Clinical Psychology and PsychotherapyBaumeister, Harald; Universitat Ulm, Institut of Psychology and Education, Department of Clinical Psychology and Psychotherapy
<b>Primary Subject Heading</b>: Mental health
Secondary Subject Heading: Health economics, Mental health
Keywords: Chronic pain, Internet-and mobile-based intervention, Health economic evaluation, Cost-effectiveness, Cost-utility, eHealth
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A guided and unguided internet- and mobile-based intervention for chronic pain: Health economic evaluation alongside a randomized controlled trial
S. Paganini 1, 2a, J. Lin1, F. Kählke3, C. Buntrock3, D. Leiding4, D.D. Ebert3, H. Baumeister5
1Department of Sports and Sport Science, Sport Psychology, University of Freiburg, Germany, [email protected], [email protected]
2Department of Rehabilitation Psychology and Psychotherapy, Institute of Psychology, University of Freiburg, Germany
3Department of Clinical Psychology and Psychotherapy, Friedrich-Alexander University of Erlangen-Nuremberg, Germany, [email protected], [email protected], [email protected]
4Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany, [email protected]
5Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, University of Ulm, Germany, [email protected]
a Corresponding author: Sarah Paganini, Department of Sports and Sport Science, Sport Psychology, University of Freiburg, Germany, Schwarzwaldstr. 175, 79117 Freiburg, Phone: +49 (0)761 / 203-4514, Email: [email protected]
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ABSTRACT
Objective: This study aims at evaluating the cost-effectiveness/cost-utility of a guided and unguided
internet-based intervention for chronic pain patients (ACTonPainguided/ACTonPainunguided) compared to
a waitlist control(WLC) condition as well as the comparative cost-effectiveness of the interventions.
Design: This is a health-economic evaluation alongside a three-armed randomized controlled trial
from a societal perspective. Assessments were conducted at baseline, nine weeks and six months after
randomization.
Setting: Participants were recruited through online and offline strategies and in collaboration with a
health insurance company.
Participants: 302 adults (≥18 years, pain for at least six months) were randomly allocated to one of
the three groups(ACTonPainguided,ACTonPainunguided,WLC).
Interventions: ACTonPain consists of seven modules and is based on Acceptance and Commitment
Therapy. ACTonPainguided/ACTonPainunguided only differ in provision of human support.
Primary and secondary outcome measures: Main outcomes of the cost-effectiveness and the cost-
utility analyses were meaningful change in pain interference (treatment response) and quality-adjusted
life years (QALYs). Economic evaluation estimates were incremental cost-effectiveness/cost-utility
ratios (ICER/ICUR).
Results: At 6-month follow-up treatment response and QALYs were highest in ACTonPainguided(44%
and 0.280; mean costs=€6,945), followed by ACTonPainunguided(28% and 0.266; mean costs=€6,560)
and WLC(16% and 0.244; mean costs=€6,908). ACTonPainguided vs. WLC revealed an ICER/ICUR of
45 and 604, respectively, while ACTonPainunguided dominated WLC. At a willingness-to-pay of €0 the
probability of being cost-effective was 50% for ACTonPainguided and 66% for ACTonPainunguided. This
probability rose to 95% when society´s willingness-to-pay is 91,000€(ACTonPainguided) and
€127,000(ACTonPainunguided) per QALY. ACTonPainguided vs. ACTonPainunguided revealed an
ICER/ICUR of 2,374 and 45,993.
Conclusions:
Depending on society´s willingness-to-pay ACTonPain is a potentially cost-effective adjunct to
established pain treatment, with ACTonPainunguided (vs.WLC) even leading to lower costs at better
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health outcomes. However, uncertainty has to be taken into account. Direct comparison of the two
interventions indicates a preference for ACTonPainunguided under health economic aspects.
Trial Registration: German Clinical Trial Registration:DRKS00006183,
URL:https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00006
183
Keywords: Chronic pain; internet- and mobile-based intervention; eHealth; health economic
evaluation; cost-effectiveness; cost-utility
Strengths and limitations of this study
This is the first study that evaluates the (comparative) cost-effectiveness of a guided and an
unguided internet-based intervention for individuals with chronic pain.
In this study state-of-the-art statistical methods such as seemingly unrelated regression
equations models or non-parametric bootstrapping techniques were applied.
Results should be interpreted cautiously, as the study was not powered to statistically test
health economic differences.
As the costs and effects were evaluated over six months, no conclusions regarding the long-
term cost-effectiveness can be drawn.
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BACKGROUND
Chronic pain is highly prevalent [1–4] and associated with substantial decreases in quality of life [1, 5,
6] and high economic costs for society [3, 7–9]. Evidence supports psychological interventions as one
approach for effectively treating patients with chronic pain [10]. Treatment based on cognitive-
behavioral therapy (CBT) or third-wave therapies, like the Acceptance and Commitment Therapy
(ACT, a particular form of CBT) have been shown to be effective for chronic pain patients [11, 12]
and could show acceptable results concerning cost-effectiveness [13]. However, accessibility and
availability of treatment is often restricted and up to 40% of individuals with chronic pain do not
receive adequate pain management [1, 14]. Internet- and mobile- based interventions (IMIs) are an
effective, acceptable and feasible way for providing psychological interventions [15, 16]. IMIs for
chronic pain have been shown to effectively improve pain interference compared to different control
groups, such as standard (medical) care, text-based material and mostly waitlist control condition
(standardized mean difference (SMD)=.4 [17], SMD=−0.50 [18]).
IMIs can not only facilitate the access to psychological treatment, they also have the potential to
reduce treatment costs [19, 20], particularly by saving therapist resources. IMIs can be delivered as
guided or unguided self-help interventions, with both versions usually necessitating less therapist time
compared to traditional on-site therapies [21]. A relevant health care policy question is what amount of
professional human guidance is necessary in order to improve patients´ health, with guided IMIs being
seemingly more effective than unguided IMIs [21, 22]. However, as unguided IMIs can be delivered at
lower costs per participant, they might as well be an attractive option particularly given their high
scalability on a population level.
To the best of our knowledge no randomized controlled trial (RCT) has investigated the (comparative)
cost-effectiveness of a guided and unguided IMI for chronic pain. However, Boer and colleagues
found that an IMI for chronic pain was cost-effective compared to a face-to-face group intervention
(concerning a one-point-improvement in a pain catastrophizing scale) [23]. Lin and colleagues
recently finalized a three arm RCT comparing a guided and unguided version of an Acceptance and
Commitment Therapy based IMI for chronic pain (ACTonPain) against a waitlist control group [24,
25]. Compared to the waitlist control condition, ACTonPainguided showed significantly lower pain
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interference at nine weeks and six months after randomization (d=0.58). Differences between
ACTonPainunguided and the control group and between both ACTonPain groups were not statistically
significant [25].
The present paper provides the cost-effectiveness and cost-utility of ACTonPainguided/unguided compared
to the waitlist control condition as well as the comparative cost-effectiveness of
ACTonPainguided/unguided.
METHODS
Study design and sample
This health-economic evaluation was conducted with a 6-month time horizon from the societal
perspective alongside a three-armed RCT to investigate the cost-effectiveness and cost-utility of
ACTonPain. Full details of the trial design can be found in the study protocol and the main outcome
paper of this trial [24, 25]. The economic evaluation was conducted and reported in agreement with
the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement [26] and the
International Society For Pharmacoeconomics and Outcomes Research (ISPOR) guidelines [27].
The study has been registered in the German Clinical Trial Register (DRKS00006183) and was
approved by the ethics committee of the University of Freiburg (reference: 387/14). In total, 302
participants were recruited from 10/2014 until 08/2015 in German pain clinics, largescale
organizations for chronic pain (e.g. self-help groups), on websites and with assistance of a German
health insurance company. Inclusion criteria were 1) age 18 years or older, 2) chronic pain for at least
six months, with 3) considerable intensity (=at least Grade II in the Chronic Pain Grade [28]), 4) being
medically suitable for participation in a chronic pain IMI, 5) sufficient knowledge of the German
language, 6) sufficient computer and internet literacy, and 7) having internet access. Exclusion criteria
were 1) cancer-related pain, 2) ongoing or planned psychological pain intervention within the
forthcoming three months and 3) elevated risk of suicide.
Randomization
All eligible participants who provided informed consent were asked to fill out the baseline assessment
and were randomly allocated to one of the three conditions ACTonPainguided, ACTonPainunguided and
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waitlist. Permuted block randomization with variable block sizes (6, 9, 12) was performed by an
independent researcher not otherwise involved in the study using an automated, web-based
randomization program.
Interventions
ACTonPain is a German adaption of an IMI by Buhrman and colleagues [29] for individuals suffering
from chronic pain. The intervention is based on ACT and consists of seven modules, which include
information, metaphors, assignments, and mindfulness exercises. Both treatment conditions differ only
in the provision of guidance. Participants were advised to work on one module every week (~60
minutes). In both intervention groups, participants had the option to receive daily automated text
messages that repeated content, reminded and motivated participants.
In ACTonPainguided trained and supervised eCoaches (psychologists) provided written feedback for
each module, which aimed at increasing participants' motivation and adherence. The total time of an
eCoach spent per participant was approximately 1.75 hours. Participants in the waitlist condition
received the offer to use ACTonPainunguided after the last follow-up assessment. Participants of all three
trial arms had unrestricted access to care-as-usual.
Outcome measures
Assessment took place at baseline (T0), post-treatment (T1; nine weeks after randomization) and 6-
month follow-up (T2; six months after randomization). Outcomes were assessed by means of an
online self-report assessment using a secured internet-based platform (AES, 256-bit encrypted).
Treatment response
Main clinical outcome in the cost-effectiveness analysis was treatment response. This outcome was
not defined in the protocol paper. However, it was chosen to calculate a reliable and meaningful
change in pain interference according to the recommendations of the Initiative on Methods,
Measurement, and Pain Assessment in Clinical Trials (IMMPACT) [30] instead of a one-point change
on the MPI, that would be difficult to interpret.
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According to the IMMPACT recommendations clinically important changes were identified with a
combination of a distribution-based approach (Pain Interference Scale of the Multidimensional Pain
Inventory MPI [31, 32]) and an anchor-based approach (Patient Global Impression of Change scale
PGIC [33]) [30]. First, participants with a change of 0.6 points (based on the scale’s standard
deviation) on the Pain Interference Scale of the MPI (range of the scale: 0-6) were identified as having
minimal clinically important changes [30]. Second, participants were identified, that rated their global
improvement in the PGIC [33] as “minimally, much or very much improved”. Participants who
fulfilled both criteria were classified as having achieved a clinically important change [30], defined as
“treatment response”.
Quality-adjusted life years
The clinical outcome in the cost-utility analysis was quality-adjusted life years (QALYs) based on the
AQoL-8D [34] in the main analysis and the EQ5D-3L [35] in the sensitivity analysis. Utility scores
are a preference-based measure of quality of life that is normed by the value 1 meaning complete
health and 0 meaning death [36].
The AQoL-8D comprises 35 items, which load on three physical (independent living, pain, senses)
and five psycho-social (mental health, happiness, coping, relationships, self-worth) dimensions [34].
The utility scores are scaled by SPSS algorithm for AQoL-8D utility model [34]. The AQoL-8D has
been shown as a reliable and valid instrument, suitable when psychosocial elements of health are the
focus of research [34], whereas utility weights are derived from the Australian adult population [37].
The EQ-5D-3L consists of five dimensions (mobility, self-care, usual activities, pain/discomfort, and
anxiety/depression), each of which is rated as causing ‘no’, ‘some’ or ‘extreme problems,’ and is a
well validated instrument [35, 38, 39]. Theoretically, the EQ-5D-3L generates 243 different health
states. Utility scores were calculated using the UK tariffs [40].
The AQoL-8D covers more dimensions that might be affected by chronic pain and shows a higher
sensitivity to mental health-related quality of life dimensions [41] compared to the EQ5D-3L.
Subsequently, and different to our protocol, this instrument was chosen for the main analyses[24].
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QALY health gains for the 6-months period were estimated by calculating the area under the curve
(AUC) of linearly interpolated AQoL-8D and EQ-5D-3L utility scores [42].
Resource use and costing
The Trimbos and iMTA questionnaire for costs associated with psychiatric illness (TiC-P) [43, 44]
was adapted to the German health care system and to the healthcare use of individuals with chronic
pain. It was used to assess the direct and indirect costs of the past three month at T0 and T2. Costs
were expressed in Euros (€) for the reference year 2015 (index factor 1.003 and 1.01 for outpatient
medical service, respectively) referring to the German consumer price index [45] (list of unit cost
prices see Table 1). To calculate the 6-month accumulated per-participants costs, the area under curve
(AUC) method was used by linearly interpolating 3-month costs (measured at T0 und T2) to cover the
full period of six months [42].
𝐴𝑈𝐶 = (𝐶𝑜𝑠𝑡𝑠 𝑇0
3 +𝐶𝑜𝑠𝑡𝑠 𝑇2
32 ) ∗ 3 + 𝐶𝑜𝑠𝑡𝑠 𝑇2
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Table 1: List of unit cost prices
Sector Unit Category 2015 (in Euro)
Out
patie
nt m
edic
al se
rvic
e /
outp
atie
nt se
ctor
Euro/contact
PhysicianGynecologistOrthopedistSpecialists for internal medicineOphthalmologistDermatologistETN specialistSurgeonUrologistNeurologistPsychotherapistDentist
20.81 31.62 25.82 64.25 36.96 19.58 28.12 44.59 25.20 47.02 79.42 55.24
remedies Logopedics / speech therapyPhysiotherapyErgotherapy / occupational therapyPodiatry / podologyMean remedies
41.02 17.50 39.45 29.13 31.77
hospitals Euro/day
Completely stationary normal wardCompletely stationary intensive careCompletely stationary psychiatrySemi-stationary general hospitalSemi-stationary psychiatry
648.11 1,424.60 348.26 421.27 226.37
rehabilitation Euro/day OutpatientInpatient
49.43 138.19
opportunitiy costs Euro/houropportunity costs (free time) opportunity costs (work)substitution costs for informal care
21.77 31.89 18.97
Note: Prices for outpatient medical service/outpatient sector were calculated fort the year 2013; all other prices for the year 2014 [46, 47] and adjusted by the German consumer price index for 2015 [45]. ETN specialist, Ear, nose, and throat specialist.
Direct medical costs
Healthcare costs (e.g. out- and inpatient care) were calculated according to the German guideline of
Bock and colleagues [46, 47]. The costs of therapeutic appliances (that were not listed in Bock and
colleagues [46, 47]) and medication were obtained from the Lauer-Taxe [48].
Patient and family costs
Self-reported out-of-pocket expenses and direct non-medical costs (travel expenses, opportunity costs,
domestic help) were assessed. Participants reported the cost of travelling by bus or taxi. If not stated,
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each kilometer was valued at €0.30. Opportunity costs (i.e., time spent at the practitioners waiting
room) were estimated at €21.77 per hour. Costs of informal care were valued using a shadow price of
€18.97 per hour [47].
Indirect costs
Indirect costs included productivity losses caused by absenteeism and presenteeism. Absenteeism
costs were calculated according to the human capital approach [49]. Self-reported lost work days were
multiplied by the corresponding gross average of participants’ income per day. To calculate
presenteeism costs, participants reported the number of days of reduced efficiency at work. These days
were weighted by an inefficiency score. Productivity losses from unpaid work (i.e. domestic help from
family members) were valued using a shadow price of €18.97 per hour [47].
Intervention costs
Intervention costs of ACTonPainguided (€299) and ACTonPainunguided (€69) were based on actual
market prices for (un)guided interventions with a similar amount of modules that contain all costs for
developing and hosting the intervention (https://geton-institut.de/).
Statistical analysis
This study was not powered to statistically test differences in health economic outcomes. Therefore,
we took a probabilistic decision-making approach for health-economic inferences [50], that aims at
informing decision makers on probabilities rather than statistical significance. There was no need to
discount costs or outcomes as the time frame for the study was six months.
All analyses were conducted according to the intention-to-treat principle. All participants completed
T0. Missing clinical outcome data was imputed using the expectation maximization algorithm in
Statistical Package for the Social Sciences (SPSS, version 20). Analyses of clinical outcomes were
conducted and reported elsewhere [25] in accordance with the CONSORT 2010 Statement [51].
Missing cost data was imputed using the regression imputation procedure in Stata version 13 [52].
Predictors of cost data and dropout were identified by logistic regression analysis and were used to
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obtain the most likely values of the missing cost data. At baseline, AQoL-utilities differed between
groups (ACTonPainguided: M=0.496, SD=0.16; ACTonPainunguided: M=0.485, SD=0.17; waitlist:
M=0.463, SD=0.14). Therefore, baseline adjustments were made in further calculations.
We tested group differences in treatment response using the chi-squared test and the Kruskall-Wallis
test for QALYs both followed by post-hoc comparisons (Bonferroni and Dunn´s test, respectively).
In the cost-effectiveness analyses, the outcome estimate is the incremental cost-effectiveness ratio
(ICER), where incremental costs over the 6-month period are divided by incremental effects
(treatment response or QALYs): ICER=(CostsIG–CostsCG)/(EffectsIG–EffectsCG) subscripted with IG
for the two intervention groups and CG for the comparison groups. Different to the protocol [24],
ICERs are reported for a 6-month horizon (baseline data; T0 and 6-month follow-up; T2) and not
based on pre-post (T0 and post-treatment; T1). As participants are asked for their health care
utilization during the last three months, the TiC-P can only be evaluated appropriately at T0 and T2 (as
T1 assessments are conducted nine weeks after randomization).
Non-parametric bootstrapping by resampling patient-level data with 5,000 replications was used to
take into account the sampling uncertainty of the ICER estimates. Seemingly unrelated regression
equations models were bootstrapped to allow for correlated residuals of the cost and effect equations.
Bootstrapping was used to obtain 95% confidence intervals for the ICERs based on the percentile
method, since parametric techniques are inappropriate for use on skewed variables and ratios [50].
The bootstrapped ICERs were plotted on a cost-effectiveness plane. In addition, a cost-effectiveness
acceptability curve was graphed to assess the probability that the intervention is cost-effective relative
to the comparator condition given varying willingness-to-pay (WTP) ceilings. In order to increase
readability of the direct comparison ACTonPainguided vs. ACTonPainunguided the inverse cost-
effectiveness acceptability curve (ACTonPainunguided vs. ACTonPainguided) was additionally plotted. All
analyses were performed using Stata version 13 [52].
Sensitivity analysis
We tested the robustness of the outcomes of the main analysis in a sensitivity analysis. Therefore, we
used the EQ-5D-3L as a widely used instrument for calculating QALYs. As baseline EQ5D-utilities
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differed between groups (ACTonPainguided: M=0.469, SD=0.32; ACTonPainunguided: M=0.436,
SD=0.31; waitlist: M=0.494, SD=0.3), baseline adjustment was made in the sensitivity analyses.
Patient and public involvement
No patients or public were involved in developing the research question or the outcome measures, nor
were they involved in developing plans for design or implementation of the study. Possible negative
effects were assessed as well as the satisfaction with the intervention (for results, see [25]). The results
of the research will be disseminated to those study participants who wished to be notified.
RESULTS
Sample characteristics
The overall sample size was 302. Due to missing assessments the dropout rate was 25.8% at 6-month
follow-up (ACTonPainguided: 33/100; ACTonPainunguided: 35/101; waitlist: 10/101). At 6-month follow
up, dropout rates differed significantly between groups (χ2(2)=20.17, p<.001). Pairwise comparison
revealed significant differences for ACTonPainguided vs. waitlist (t(1)=-3.85, p<.001) and
ACTonPainunguided vs. waitlist (t(1)=-4.14, p<.001). Study dropout was not associated with baseline
pain interference or socio-demographic factors.
The average participant was female, 52 years of age, with an above average level of education,
employed and was already treated for chronic pain. Detailed participants’ characteristics and the
CONSORT flowchart have already been reported elsewhere [25].
Outcomes
Table 2 shows treatment response and QALY outcomes as well as group differences. At 6-month
follow-up, treatment response differed significantly between groups (ACTonPainguided: 44/100;
ACTonPainunguided: 28/101; waitlist: 16/101). Pairwise comparison revealed significant differences for
ACTonPainguided vs. waitlist and ACTonPainguided vs. ACTonPainunguided but not for ACTonPainunguided
vs. waitlist. Between-group differences in AQoL-8D QALY gains were statistically significant.
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Pairwise comparison revealed significant differences only for ACTonPainguided vs. waitlist. Incremental
EQ5D-3L QALY gains did not differ significantly between study groups.
Table 2. Treatment response and quality-adjusted life-year (QALY) outcomes and group differences at 6-month follow up.
ACTonPain guided (n = 100)
ACTonPain unguided (n = 101)
WLC group (n = 101) Test statistic
Mean (SD) Mean (SD) Mean (SD) χ2 (df=2) Post-hoc test c: pTreatment response (pain interference) 0.44 (0.05) 0.277 (0.04) 0.158 (0.04) 19.44 a <001ACTonPain guided vs. WLC group t(1)=4.52 <.001ACTonPain unguided vs. WLC group t(1)=1.91 .17ACTonPain guided vs. unguided t(1)=2.61 .03QALYAQoL-8D 0.280 (0.08) 0.266 (0.09) 0.244 (0.08) 9.45 b .009ACTonPain guided vs. WLC group Z=-3.07 .003ACTonPain unguided vs. WLC group Z=-1.61 .16ACTonPain guided vs. unguided Z=-1.47 .21EQ5D-3L 0.274 (0.12) 0.255 (0.12) 0.253 (0.13) 2.17 b .34WLC group, waitlist control group; SD, standard deviation; df, degrees of freedom; QALY, quality-adjusted life-yeara Chi-squared test b Kruskall-Wallis H testc Post-hoc test for treatment response: Bonferroni pairwise comparison; Post-hoc test for QALY: Dunn´s test
Costs
At baseline, mean total costs were €3,233 in ACTonPainguided, €3,724 in ACTonPainunguided and €3,570
in the waitlist group. The 6-month accumulated per-participants costs by study condition are presented
in Table 3. ACTonPainguided showed the highest mean total costs (€6,945), followed by the waitlist
group (€6,908) and ACTonPainunguided (€6,560). Mean direct costs were the highest in the guided
group, followed by the unguided group and waitlist. The opposite order was found for the indirect
costs. Medication, domestic help and opportunity costs were major cost drivers. Productivity losses
produced the highest cost differences between the intervention groups and waitlist of -€871
(ACTonPainguided vs. waitlist) and -€721 (ACTonPainunguided vs. waitlist).
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Table 3. 6-month accumulated per-participants costs (in €) by condition (based on intention-to-treat sample, N = 302).
ACTonPain guided (n = 100)
ACTonPain unguided (n = 101)
WLC group (n = 101)
Incremental costs
Difference, €
Mean, € (SD) Mean, € (SD) Mean, €
(SD)
ACTonPain guided vs. WLC
ACTonPain unguided vs. WLC
ACTonPain guided vs. unguided
Intervention 299 (-) 69 (-) 0 (-) 299 69 230Direct medical costsHealth care costs Medical specialist 576 (478) 511 (381) 511 (382) 65 0 65 Mental health care 212 (431) 181 (397) 258 (455) -46 -77 31 Other medical specialist a
369 (515) 357 (435) 406 (576) -37 -49 12
In-patient care (hospital)
198 (479) 173 (369) 141 (420) 57 32 25
Day care 147 (687) 122 (381) 306 (1,584) -159 -184 25 Rehabilitation 190 (794) 134 (507) 191 (773) -1 -57 56 Medication 1,092 (2,748) 784 (1,438) 660 (1,638) 432 124 308 Therapeutic appliances 65 (139) 86 (222) 46 (96) 19 40 -21Direct non-medical costs Patient and family costs Travel 131 (229) 105 (150) 101 (100) 30 4 26 Domestic help 1,297 (4,064) 1,147 (1,936) 840 (1,490) 457 307 150 Opportunity costs b 1,553 (1,965) 1,925 (3,251) 1,759 (3,116) -206 166 -372Indirect costsProductivity losses Absenteeism 517 (1,647) 647 (1,979) 1,133 (3,333) -616 -486 -130 Presenteeism 300 (740) 320 (774) 555 (1,360) -255 -235 -20
Total direct costs 5,829 (7,129) 5,525 (4,959) 5,220 (5,133) 611 306 305Total indirect costs 817 (1,978) 966 (2,283) 1,688 (3,735) -871 -721 -150Total societal costs 6,945 (7,327) 6,560 (5,549) 6,908 (6,279) 39 -346 385WLC group, waitlist control groupa i.e. physiotherapist, occupational therapistb i.e. for waiting time before treatment
Health-economic evaluation
Table 4 shows the incremental costs, effects and cost-effectiveness ratios for the main analysis and the
sensitivity analysis.
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Table 4. Results of the main and sensitivity analyses (based on 5,000 bootstrap simulations).
AnalysisACTonPain guided vs. WLC group
Incremental costs, €(95% CI)
Incremental effects(95% CI)
MeanICER(95% CI)
Distribution over the ICER planeNE NW SE SW
Cost-effectiveness, treatment response (MPI and PGIC)
6(-916-953)
0.14(0.08-0.2)
45(-6,671-8,260)
50% - 50% -
Cost-utilityAQoL QALYs
6(-916-953)
0.01(0.005- 0.015)
604(-92,924- 114,325)
50% - 50% -
Sensitivity analysis EQ5D QALYs 6
(-916-953)0.014(0.004- 0.024)
438 (-69,407- 122,314)
50% - 50% -
AnalysisACTonPain unguided vs. WLC group
Incremental costs, €(95% CI)
Incremental effects(95% CI)
MeanICER(95% CI)
Distribution over the ICER planeNE NW SE SW
Cost-effectiveness, treatment response (MPI and PGIC)
-352(-1,968-1,272)
0.12(0.006-0.232)
ACTonPain unguided dominates WLC
32% 1% 66% 1%
Cost-utility AQoL QALYs
-352(-1,968-1,272)
0.013(0.002-0.024)
ACTonPain unguided dominates WLC
32% 1% 66% 1%
Sensitivity analysis EQ5D QALYs -352
(-1,968-1,272)
0.017 (-0.005- 0.04)
ACTonPain unguided dominates WLC
30% 4% 64% 3%
AnalysisACTonPain guided vs. ACTonPain unguided
Incremental costs, €(95% CI)
Incremental effects(95% CI)
MeanICER(95% CI)
Distribution over the ICER planeNE NW SE SW
Cost-effectiveness, treatment response (MPI and PGIC)
388(-1,416-2,185)
0.164(0.034-0.29)
2,374 (-11,097-25,276)
65% - 35% -
Cost-utility AQoL QALYs
388(-1,416-2,185)
0.008(-0.003-0.019)
45,993a 60% 5% 33% 2%
Sensitivity analysis EQ5D QALYs 388
(-1,416-2,158)
0.01 (-0.01- 0.031)
37,327a 53% 12% 31% 4%
WLC group, waitlist control group; MPI, Pain Interference Scale of the Multidimensional Pain Inventory; PGIC, Patient Global Impression of Change scale; 95% CI, 95% confidence interval; EQ-5D QALYs, Quality-adjusted life years based on EuroQol; ICER, incremental cost-effectiveness ratio; NE, northeast quadrant; NW, northwest quadrant; SE, southeast quadrant; SW, southwest quadrant.
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aA dependably accurate 95% confidence interval for this distribution cannot be defined because there is no line through the origin that excludes α/2 of the distribution[53].
Cost-effectiveness
The cost-effectiveness planes and acceptability curves, representing the 5,000 bootstrap replications,
are shown in Figure 1 (a, b, c) and 2 (a, b). ACTonPainguided showed the same and ACTonPainunguided a
higher potential of being cost-effective compared to waitlist at a WTP of €0 (ACTonPainguided 50%,
ACTonPainunguided 66%). The probability of ACTonPainguided being more cost-effective compared to
waitlist increased up to 70% at a WTP of €1,738 and to 95% at a WTP of €6,490 for an additional
treatment response, and for ACTonPainunguided to 70% at a WTP of €660 and to 95% at a WTP of
€13,460.
The probability that ACTonPainguided is more cost-effective than ACTonPainunguided was 35% at a WTP
of €0 for an additional treatment response. When society’s WTP increases up to €5,535 or €17,170
this probability rises to 70% or 95%, respectively. The break even point (where ACTonPainguided and
ACTonPainunguided have the same possibility of being cost-effective at same costs) is at €2,188 (see
Figure 2b).
- Figure 1-
- Figure 2-
Cost-utility
Cost-effectiveness planes and acceptability curves that refer to cost-utility are shown in figure 1 (d, e,
f) and 2 (c, d). ACTonPainguided showed the same and ACTonPainunguided a higher potential of being
cost-effective compared to waitlist at a WTP of €0 (50% and 66%, respectively). The interventions’
probability of being more cost-effective compared to waitlist increased up to 70% and to 95% at a
WTP of €24,415 and €91,000, respectively, in ACTonPainguided and €6,130 (70%) and €127,000 (95%)
in ACTonPainunguided for one additional QALY. The probability that ACTonPainguided is more cost-
effective than ACTonPainunguided was 31% at a WTP of €0 for one additional QALY. When society’s
WTP increases up to €113,550 this probability rises to 70% and stagnates on this level. The break-
even point is at €41,350 (see Figure 2 d).
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Sensitivity analysis
After non-parametric bootstrapping, using the EQ-5D-3L resulted in larger incremental QALY gains
in all comparisons compared to the results using the AQoL-8D (see table 4).
At a WTP of €0 the probability of ACTonPainguided of being cost-effective compared to waitlist was
50%. The probability of ACTonPainunguided of being cost-effective compared to waitlist was 64% at a
WTP of €0. ACTonPainguided vs. ACTonPainunguided resulted in a probability of being cost-effective of
31% at a WTP of €0.
DISCUSSION
Comparing both ACTonPain interventions to waitlist and by taking uncertainty into account,
ACTonPainunguided can be judged as a potentially cost-effective intervention as it dominates WLC by
leading to higher QALY gains and more individuals with a treatment response at lower costs.
However, when assuming that an intervention should reach a likelihood of being cost-effective of 95%
or greater it has to be considered that the WTP would have to be €13,460 for treatment response and
€127,000 for a QALY gain. Therefore, the judgement of whether the intervention is cost-effective or
not ultimately depends on the society’s WTP for treatment response or a QALY gain, respectively.
ACTonPainguided also causes better results in the main outcome parameters, but at (slightly) higher
costs with ICERs of 45 (treatment response) and 604 (AQoL QALY gains). The probability of being
cost-effective at a WTP of €0 compared to waitlist is higher in ACTonPainunguided, for both, treatment
response and QALYs gained (66%) than in ACTonPainguided (50%).
However, when comparing the costs that would have to be invested by using ACTonPainguided
(compared to waitlist) for a QALY gained (€604) to the only official WTP threshold stated by the
National Institute for Health and Clinical Excellence (NICE) of £20,000 to £30,000 [54] (~ €22,647 -
€33,971; conversion according to the European Central bank [55]), this intervention would be
categorized as a potentially cost-effective treatment (with a probability of around 70%). This threshold
might serve as a reference, but it has to be considered, that it might differ for the German population.
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Here again, uncertainty has to be considered as well as the required WTP for a likelihood of being
cost-effective of 95% of €6,490 (treatment response) and €91,000 (QALY gain).
The direct comparison of ACTonPainguided and ACTonPainunguided shows more treatment responders
and (slightly) higher QALY gains for the guided version, but at higher costs. In terms of QALYs
gained, the guided version only reaches a probability of 31% of being cost-effective at a WTP of €0
and even with rising WTP threshold, the probability does not increase much.
The results of the sensitivity analyses revealed slightly higher incremental QALY gains by using the
EQ5D-3L compared to the AQoL-8D but overall conclusions are the same as in the main analyses.
Estimated EQ-5D utility scores for one year ranged from 0.50 to 0.54, what appears rather low
compared to national EQ-5D estimates for (back) pain from other countries (e.g. 0.74-0.79 [56, 57]).
Lower estimates in the current study could have occurred due to the sociodemographic properties of
this study sample, as participants were predominately women (84%), reported comorbid medical or
mental conditions (57% and 39%, respectively) and the back was the most often reported pain location
(34%) [25]. Several studies showed that the mentioned characteristics (female sex, musculoskeletal
and mental disorders) are associated with lower quality of life scores [56–58]. Furthermore, Burström
et al. (2001) reported in their study that participants with low back pain showed quality of life weights
of 0.55 [58], what is comparable to the sample in the current study.
The conclusion that ACTonPain has the potential of being cost-effective are in line with a recent study
and a review about the cost-effectiveness of IMIs for depression [23, 59]. The guided IMI for chronic
pain of Boer and colleagues revealed an ICER of 40 (defined as cost savings of €40) for an one-point
improvement in a pain catastrophizing scale compared to a face-to-face group intervention, while
QALYs were not reported [23]. ACTonPainguided reached (slightly) higher ICERs for the clinical
outcome pain interference (45 compared to waitlist group and 2,374 compared to the unguided group).
However, these values were calculated for treatment response in terms of pain interference and
therefore, a meaningful change and not for a one-point improvement on the scale. In a systematic
review, IMIs for depression that were classified as cost-effective were all guided and showed
probabilities of being cost-effective between 28% and 49% at a WTP of €0 for a QALY gained,
whereas ACTonPainguided and ACTonPainunguided even reached higher probabilities at this WTP level
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(50% and 66%, respectively). However, it has to be considered that in terms of QALY gain society has
to invest quite high sums of money for high probabilities (95%) of being cost-effectiveness.
Nevertheless, integrating psychological e-health approaches in pain management programs might be
promising from an economical point of view when compared to the well-established area of
depression e-health care.
The higher direct costs over a 6-months period in both intervention groups compared to waitlist might
be explained by higher or stable health care utilization similar to findings in a previous study on the
costs of established depression treatments [60]. However, research indicates that indirect rather than
direct costs represent the majority of overall costs [61, 62], where ACTonPain seemingly has its core
advantage. Mean indirect costs over the 6-month period were almost half as high in the intervention
groups compared to waitlist, regarding both absenteeism and presenteeism.
Next to the questions of whether ACTonPain is cost-effective compared to waitlist and whether it
should rather be provided guided or unguided, it would be of interest how ACTonPain performs
compared to established medical, psychological, physiotherapeutical, and surgical treatments that
result in high direct costs [63–66]. However, surprisingly little is known about the cost-effectiveness
of these established pain treatments. In two reviews it was highlighted, that interdisciplinary pain
rehabilitation programs are more cost-effective or produce lower costs than interventions such as
surgery and conservative care [67, 68]. For individuals with low back pain it was concluded that
interdisciplinary rehabilitation, exercise, acupuncture, spinal manipulation and CBT are potentially
cost-effective [69]. A further systematic review focused on economic evaluations of third-wave CBT
therapies (including ACT), were available ICERs ranged from negative ICERs indicating dominance
over the control group (National Health Service perspective) to €56,637 (societal perspective) per
QALY gained [13]. When compared to waitlist the ICERs based on the AQoL-8D in this study were
604 and a negative ICER (indicating dominance of the unguided intervention over WLC) per QALY
gained. Thus, it can be concluded that ACTonPain, as an example of an innovative IMI for the
treatment of chronic pain, is effective [25] and could be a cost-effective intervention. A comparison
across treatment approaches for chronic pain, however, cannot be provided as the evidence base for
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the cost-effectiveness of established pain treatments is rather weak and the comparability of results
across studies is limited due to very heterogeneous methods across trials [70].
Limitations
First, when interpreting the results, it has to be considered that the study was not powered to
statistically test health economic differences. Second, the costs and effects were evaluated over six
months. Therefore, no conclusions regarding the long-term cost-effectiveness can be drawn.
Furthermore, costs between randomization and three months after randomization were calculated with
the area under the curve method. This is just an estimate and not a representation of the actual costs
incurred during this period. Fourth, costs were assessed via self-report. However, as the questionnaire
used in this study is a valid instrument to recall periods up to three months [71], the impact of this bias
on results is limited. Finally, the usage of multiple imputation techniques is frequently recommended
(e.g. predictive mean matching [72]. We used a single imputation approach as it was done in the main
(effectiveness) analysis [25] that might not truly reflect missing data uncertainty. However, the
comparison with cost and QALY outcomes of complete case analysis revealed only small differences,
indicating that the risk of implausible values due to single imputation in this evaluation is low [73].
Implications and future research
For patients with chronic pain, IMIs might become an important alternative to established
interventions. IMIs can expand treatment options for people, whose physical impairment or location
makes access to relevant care difficult [19]. Findings from this health economic evaluation study show
that depending on the society´s willingness-to-pay, both versions of ACTonPain have the potential of
being cost-effective, with the unguided version even leading to lower costs (compared to WLC).
However, uncertainty has to be taken into account. The decision whether to choose the guided or
unguided version is a public health issue and strongly depends on whether to mainly focus on patients´
health or society´s resources. Under health economic aspects ACTonPainunguided should be the preferred
intervention, especially when considering the intention of treatment implementation into the health
care system and scaling up mental health care for pain patients.
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Future research should especially focus on conducting methodologically sound studies that are
powered to statistically test health economic differences. Furthermore, long-term follow-up studies
and evaluation of the (comparative) cost-effectiveness of different guidance formats of IMIs,
particularly of ACTonPain, and established pain treatments are needed. Moreover, future studies
should examine ACTonPain as integrated part of multi-component pain programs and aim to
dismantle the ingredients that are effective and cost-effective in those complex approaches.
DECLARATIONS
Funding
This research received no specific grant from any funding agency in the public, commercial or not-for-
profit sectors. The article processing charge was funded by the German Research Foundation (DFG)
and the Albert-Ludwigs University Freiburg in the funding programme Open Access Publishing.
Competing interests
Two of the authors of the manuscript were involved in the development of ACTonPain (JL and HB).
HB and DDE are consultants for several stakeholders (insurance companies, ministries, psychotherapy
chambers, companies). DDE is part of the GET.ON Institut GmbH, which aims at implementing
evidence-based internet- and mobile based interventions into routine care. SP, CB, FK and DL declare
that they have no competing interests.
Data sharing statement
The datasets used and/or analyzed during the current study are available from the corresponding
author on reasonable request.
Authors’ contributions
JL and HB initiated the randomized control trial for this health economic evaluation. SP, FK, CB, DL
and DDE contributed to the design of this health economic evaluation. SP, DL, FK and CB
contributed to the data analysis. SP had full access to all the data in the study and had responsibility
for the decision to submit for publication. SP wrote the draft of the manuscript. All authors contributed
to the further writing and approved the final version of the manuscript.
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Acknowledgements
We would like to thank Yannik Terhorst and Nelli Hirschauer for their assistance in data processing.
Figure Legends
Figure 1. Cost-effectiveness planes of all group comparisons based on 5,000 replicates of the
incremental cost-effectiveness ratio using mean differences in costs from a societal perspective and
mean incremental effects (treatment response: a, b, c; QALYs: d, e, f)
Figure 2. Cost-effectiveness acceptability curves of all group comparisons based on 5,000 replicates
of the incremental cost-effectiveness ratio using mean differences in costs from a societal
perspective and mean incremental effects (treatment response: a, b; QALYs: c, d). For the
comparison of ACTonPain guided vs. ACTonPain unguided the inverse function (ACTonPain
unguided vs. ACTonPain guided) was included.
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63. Druss BG, Marcus SC, Olfson M, Pincus HA. The Most Expensive Medical Conditions In America. Health Affairs. 2002;21:105–11. doi:10.1377/hlthaff.21.4.105.
64. Katz JN. Lumbar disc disorders and low-back pain: socioeconomic factors and consequences. JBJS. 2006;88:21–4.
65. Smith M, Davis MA, Stano M, Whedon JM. Aging baby boomers and the rising cost of chronic back pain: secular trend analysis of longitudinal Medical Expenditures Panel Survey data for years 2000 to 2007. J Manipulative Physiol Ther. 2013;36:2–11. doi:10.1016/j.jmpt.2012.12.001.
66. Ma VY, Chan L, Carruthers KJ. Incidence, prevalence, costs, and impact on disability of common conditions requiring rehabilitation in the United States: stroke, spinal cord injury, traumatic brain injury, multiple sclerosis, osteoarthritis, rheumatoid arthritis, limb loss, and back pain. Arch Phys Med Rehabil. 2014;95:986-995.e1. doi:10.1016/j.apmr.2013.10.032.
67. Turk DC. Clinical Effectiveness and Cost-Effectiveness of Treatments for Patients With Chronic Pain. The Clinical Journal of Pain. 2002;18:355–65. doi:10.1097/00002508-200211000-00003.
68. Phillips CJ. Economic burden of chronic pain. Expert Rev Pharmacoecon Outcomes Res. 2006;6:591–601. doi:10.1586/14737167.6.5.591.
69. Lin C-WC, Haas M, Maher CG, Machado LAC, van Tulder MW. Cost-effectiveness of guideline-endorsed treatments for low back pain: a systematic review. Eur Spine J. 2011;20:1024–38. doi:10.1007/s00586-010-1676-3.
70. Furlan AD, Yazdi F, Tsertsvadze A, Gross A, van Tulder M, Santaguida L, et al. A systematic review and meta-analysis of efficacy, cost-effectiveness, and safety of selected complementary and alternative medicine for neck and low-back pain. Evid Based Complement Alternat Med. 2012;2012:953139. doi:10.1155/2012/953139.
71. van den Brink M, van den Hout WB, Stiggelbout AM, Putter H, van de Velde CJH, Kievit J. Self-reports of health-care utilization: diary or questionnaire? International journal of technology assessment in health care. 2005;21:298–304.
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72. Faria R, Gomes M, Epstein D, White IR. A guide to handling missing data in cost-effectiveness analysis conducted within randomised controlled trials. Pharmacoeconomics. 2014;32:1157–70. doi:10.1007/s40273-014-0193-3.
73. Vroomen JM, Eekhout I, Dijkgraaf MG, van Hout H, Rooij SE de, Heymans MW, Bosmans JE. Multiple imputation strategies for zero-inflated cost data in economic evaluations: which method works best? The European Journal of Health Economics. 2016;17:939–50.
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Figure 1. Cost-effectiveness planes of all group comparisons based on 5,000 replicates of the incremental cost-effectiveness ratio using mean differences in costs from a societal perspective and mean incremental
effects (treatment response: a, b, c; QALYs: d, e, f).
122x63mm (300 x 300 DPI)
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Figure 2. Cost-effectiveness acceptability curves of all group comparisons based on 5,000 replicates of the incremental cost-effectiveness ratio using mean differences in costs from a societal perspective and mean incremental effects (treatment response: a, b; QALYs: c, d). For the comparison of ACTonPain guided vs.
ACTonPain unguided the inverse function (ACTonPain unguided vs. ACTonPain guided) was included.
422x274mm (300 x 300 DPI)
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Additional file 1 – CHEERS checklist Section/item Item
No Recommendation Reported on page
No
Title and abstract
Title 1 Identify the study as an economic evaluation or use more specific terms such as “cost-effectiveness analysis”, and describe the interventions compared.
Page 1
Abstract 2 Provide a structured summary of objectives, perspective, setting, methods (including study design and inputs), results (including base case and uncertainty analyses), and conclusions.
Page 2 and 3 (the sensitivity analysis is not mentioned in the abstract due to limited words)
Introduction
Background and objectives
3 Provide an explicit statement of the broader context for the study. Present the study question and its relevance for health policy or practice decisions.
Page 4 and 5
Methods
Target population and subgroups
4 Describe characteristics of the base case population and subgroups analysed, including why they were chosen.
Page 5
Setting and location 5 State relevant aspects of the system(s) in which the decision(s) need(s) to be made.
Page 5
Study perspective 6 Describe the perspective of the study and relate this to the costs being evaluated.
Page 5, 8, 9 and 10
Comparators 7 Describe the interventions or strategies being compared and state why they were chosen.
Page 6
Time horizon 8 State the time horizon(s) over which costs and consequences are being evaluated and say why appropriate.
Page 6 and 7
Discount rate 9 Report the choice of discount rate(s) used for costs and outcomes and say why appropriate.
Page 10
Choice of health outcomes
10 Describe what outcomes were used as the measure(s) of benefit in the evaluation and their relevance for the type of analysis performed.
Page 6, 7 and 8
Measurement of effectiveness
11a Single study-based estimates: Describe fully the design features of the single effectiveness study and why the single study was a sufficient source of clinical effectiveness data.
Page 4 and 5
11b Synthesis-based estimates: Describe fully the methods used for identification of included studies and synthesis of clinical effectiveness data.
N/A
Measurement and valuation of preference based outcomes
12 If applicable, describe the population and methods used to elicit preferences for outcomes.
Page 7
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Section/item Item No
Recommendation Reported on page No
Estimating costs and resources
13a Single study-based economic evaluation: Describe approaches used to estimate resource use associated with the alternative interventions. Describe primary or secondary research methods for valuing each resource item in terms of its unit cost. Describe any adjustments made to approximate to opportunity costs.
Page 8, 9 and 10, Table 1
13b Model-based economic evaluation: Describe approaches and data sources used to estimate resource use associated with model health states. Describe primary or secondary research methods for valuing each resource item in terms of its unit cost. Describe any adjustments made to approximate to opportunity costs.
N/A
Currency, price date and conversion
14 Report the dates of the estimated resource quantities and unit costs. Describe methods for adjusting estimated unit costs to the year of reported costs if necessary. Describe methods for converting costs into a common currency base and the exchange rate.
Page 8
Choice of model 15 Describe and give reasons for the specific type of decision-analytical model used. Providing a figure to show model structure is strongly recommended.
N/A
Assumptions 16 Describe all structural or other assumptions underpinning the decision-analytical model.
N/A
Analytical methods 17 Describe all analytical methods supporting the evaluation. This could include methods for dealing with skewed, missing, or censored data; extrapolation methods; methods for pooling data; approaches to validate or make adjustments (such as half cycle corrections) to a model; and methods for handling population heterogeneity and uncertainty.
Page 10, 11 and 12
Results
Study parameters 18 Report the values, ranges, references, and, if used, probability distributions for all parameters. Report reasons or sources for distributions used to represent uncertainty where appropriate. Providing a table to show the input values is strongly recommended.
Page 12-17, Table 2 and 4
Incremental costs and outcomes
19 For each intervention, report mean values for the main categories of estimated costs and outcomes of interest, as well as mean differences between the comparator groups. If applicable, report incremental cost-effectiveness ratios.
Page 13; Table 3
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Section/item Item No
Recommendation Reported on page No
Characterising uncertainty
20a Single study-based economic evaluation: Describe the effects of sampling uncertainty for the estimated incremental cost and incremental effectiveness parameters, together with the impact of methodological assumptions (such as discount rate, study perspective).
Page 16 and 17 and Figure 1 and 2
20b Model-based economic evaluation: Describe the effects on the results of uncertainty for all input parameters, and uncertainty related to the structure of the model and assumptions.
N/A
Characterising heterogeneity
21 If applicable, report differences in costs, outcomes, or cost-effectiveness that can be explained by variations between subgroups of patients with different baseline characteristics or other observed variability in effects that are not reducible by more information.
N/A
Discussion
Study findings, limitations, generalisability, and current knowledge
22 Summarise key study findings and describe how they support the conclusions reached. Discuss limitations and the generalisability of the findings and how the findings fit with current knowledge.
Page 17-21
Other
Source of funding 23 Describe how the study was funded and the role of the funder in the identification, design, conduct, and reporting of the analysis. Describe other non-monetary sources of support.
Page 21
Conflicts of interest 24 Describe any potential for conflict of interest of study contributors in accordance with journal policy. In the absence of a journal policy, we recommend authors comply with International Committee of Medical Journal Editors recommendations.
Page 21
N/A, Not applicable
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