AssessmentofHealthCareUtilizationandCostofTargetedDrug ......2014 54 (14.4) 790 (16.3) 39 (14.6) 44 (16.4) 2015 6 (1.6) 382 (7.9) 5 (1.9) 16 (6.0) No. of inpatient hospital visits,

Original Investigation | Health Policy

Assessment of Health Care Utilization and Cost of Targeted DrugDelivery and Conventional Medical Management vs ConventionalMedical Management Alone for Patients With Cancer-Related PainLisa J. Stearns, MD; Sanjeet Narang, MD; Robert E. Albright Jr, MD; Krisstin Hammond, BS; Ying Xia, PhD; Heather Basara Richter, PhD; Gobi K. Paramanandam, MD;Kelly K. Haagenson, PhD; Alissa H. Doth, BS

Abstract

IMPORTANCE Targeted drug delivery (TDD) has potential for cost savings compared withconventional medical management (CMM). Despite positive clinical and economic evidence, TDDremains underused to treat cancer pain.

OBJECTIVE To assess the cost of TDD and CMM in treating cancer-related pain.

DESIGN, SETTING, AND PARTICIPANTS This retrospective economic evaluation using propensityscore–matched analysis was conducted using MarketScan commercial claims data on beneficiariesreceiving TDD and CMM or CMM only for cancer pain from January 1, 2009, to September 30, 2015.Participants were matched on age, sex, cancer type, comorbidity score, and pre-enrollmentcharacteristics. Data analysis was performed from June 1 to September 30, 2017.

MAIN OUTCOMES AND MEASURES Total 2-, 6-, and 12-month costs, number of health careencounters, length of hospital stay, additional components of cost, and health care utilization.

RESULTS A total of 376 TDD and CMM patients (mean [SD] age, 51.88 [9.98] years; 216 [57.5%]female) and 4839 CMM only patients (mean [SD] age, 51.52 [11.16] years; 3005 [62.1%] female) wereidentified for study inclusion. After matching, 536 patients were included in the study: 268 patientsin the TDD and CMM group and 268 in the CMM only group. Compared with CMM only, TDD andCMM was associated with mean total cost savings of $15 142 (95% CI, $3690 to $26 594; P = .01) at2 months and $63 498 (95% CI, $4620 to $122 376; P = .03) at 12 months; cost savings at 6 monthswere not statistically different ($19 577; 95% CI, −$12 831 to $51 984; P = .24). The TDD and CMMgroup had fewer inpatient visits (2-month mean difference [MD], 1.0; 95% CI, 0.8-1.2; P < .001;6-month MD, 1.3; 95% CI, 0.8-1.7; P < .001; 12-month MD, 2.3; 95% CI, 1.2-3.4; P < .001) and shorterhospital stays (2-month MD, 6.8 days; 95% CI, 5.0-8.7 days; P < .001; 6-month MD, 6.8 days; 95% CI,3.1-10.5 days; P < .001; 12-month MD, 10.6 days; 95% CI, 2.9-18.3 days; P = .007). Use of CMM onlywas associated with greater opioid use at 12 months (MD, 3.2; 95% CI, 0.4-6.0; P = .03).

CONCLUSIONS AND RELEVANCE Compared with CMM alone, TDD and CMM together wereassociated with significantly lower cost and health care utilization. The findings suggest that TDD is acost-saving therapy that should be considered in patients with cancer for whom oral opioids areinadequate or produce intolerable adverse effects and should be expanded as health care systemstransition to value-based models.

JAMA Network Open. 2019;2(4):e191549.

Corrected on May 17, 2019. doi:10.1001/jamanetworkopen.2019.1549

Key PointsQuestion What are the cost and health

care utilization for pain relief using fully

implantable targeted drug delivery

therapy with conventional medical

management vs conventional medical

management alone in patients

with cancer?

Findings In this economic evaluation of

claims data on 536 patients from a large

US payer database, use of targeted drug

delivery and conventional medical

management was associated with a

significant overall cost savings of

$63 498 in the 12 months after the index

date and with significantly fewer

inpatient visits, shorter inpatient length

of stay, and fewer emergency

department visits. In the short term, use

of targeted drug delivery and

conventional medical management was

associated with significantly higher

outpatient and lower inpatient costs.

Meaning The findings suggest that use

of targeted drug delivery and

conventional medical management to

treat cancer pain is associated with cost

savings and should be considered in

patients for whom oral opioids are

inadequate or produce intolerable

adverse effects.

+ Invited Commentary

+ Supplemental content

Author affiliations and article information arelisted at the end of this article.

Open Access. This article is published under the JN-OA license and is free to read on the day of publication.

JAMA Network Open. 2019;2(4):e191549. doi:10.1001/jamanetworkopen.2019.1549 (Reprinted) April 5, 2019 1/14

Copyright 2019 American Medical Association. All Rights Reserved.

Downloaded From: https://jamanetwork.com/ by a Non-Human Traffic (NHT) User on 02/20/2021

https://jama.jamanetwork.com/article.aspx?doi=10.1001/jamanetworkopen.2019.1549&utm_campaign=articlePDF%26utm_medium=articlePDFlink%26utm_source=articlePDF%26utm_content=jamanetworkopen.2019.1549



Introduction

In 2010, the National Cancer Institute estimated the yearly cost of cancer treatment in the UnitedStates at $125 billion, with a projected cost of $157 billion in 2020.1 The increase in projected costsreflects the aging US population and a 30% increase in cancer survivorship.2 To address this, theCenters for Medicare & Medicaid Services developed alternative oncology payment models toprovide high-value care.3

Patients most frequently report pain, fatigue, and emotional distress as adverse effects ofcancer.4 Pain is prevalent throughout the cancer life cycle and has been identified as a preventablereason for hospital admission.5 Pain was reported in 55.0% of patients undergoing active treatment,39.3% of patients with cancer in remission, and 66.4% of patients with advanced, metastatic, orterminal disease.6 A previous study5 identified pain diagnoses as associated with 41.4% ofemergency department (ED) visits by patients with cancer. Liberal systemic opioid use for cancerpain remains the standard of care despite increased health care utilization secondary to frequentadverse effects.7-10

Another treatment option is targeted drug delivery (TDD), which provides improved pain reliefand reduced toxic effects at lower cost compared with systemic opioid therapy.11-13 Targeted drugdelivery provides an alternate route of opioid administration, delivering a fraction of the systemicdose directly to the intrathecal space via an implanted infusion system. Randomized trial datashowed that TDD provides better pain relief with fewer adverse effects compared with conventionalmedical management (CMM).12 The National Comprehensive Cancer Network recommends TDD asan option for patients who experience intolerable adverse effects or in whom systemic opioids arenot effective.10 Most patients receiving TDD have previously been treated with CMM; however, notevery patient treated with CMM is an appropriate TDD candidate. In addition, TDD does not replaceall pain-related CMM but enables reduction or elimination of systemic opioids.14

A prior analysis13 of cost data from 2006 to 2010 compared TDD and CMM for cancer-relatedpain in 146 patients and found lower medical care utilization and total payments for patients whoreceived TDD. Since that time, TDD administration has shifted from an inpatient to an outpatientsetting. This shift may result in lower initial cost to implant a TDD system, which has the potential toincrease long-term cost savings and warrants a new analysis of available cost data. In this study, wecompared the cost and health care utilization of treating cancer-related pain with TDD and CMM vsCMM only using data from a large US claims database.

Methods

Data SourceThis study used the Truven Health MarketScan Commercial Claims and Encounters Database fromJanuary 1, 2009, to September 30, 2015; data analysis was conducted from June 1 to September 30,2017. This database captures deidentified, patient-level health data, including health care utilization,health care cost from a payer perspective, enrollment information, inpatient service, outpatientservice, and outpatient prescriptions.15,16 Disease-related factors, such as cancer stage or pain scores,are not available in the data set and were therefore not included in the model used in this analysis.Patients were identified using Current Procedural Terminology (CPT) procedure codes andInternational Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis andprocedure codes available in the database. According to the US Department of Health and HumanServices Office for Human Research Protections, institutional review board oversight was notnecessary because the study did not involve interaction or intervention with individuals, and thedatabase was deidentified in compliance with the Health Insurance Portability and AccountabilityAct.17 Therefore, no informed consent was required from the patients. The data include employer-and health plan–sourced administrative claims from more than 99 million individuals, includingemployees, spouses, and dependents covered by employer-sponsored private health care

JAMA Network Open | Health Policy Health Care Utilization and Cost of Targeted Drug Delivery vs Conventional Management for Cancer Pain



insurance.15,18 The data reflect actual treatment patterns and costs by linking paid claims andencounter data to detailed patient information across sites and types of practitioners nationwide.15

The study followed the Consolidated Health Economic Evaluation Reporting Standards (CHEERS)reporting guideline.

Study PopulationAs mentioned earlier, TDD is not a first-line treatment option. Patients identified in claims data asreceiving TDD were considered to have severe uncontrolled pain, which is a payer coverage conditionfor this treatment. The selection criteria for the CMM group included codes for the diagnosis ortreatment of uncontrolled pain or codes associated with opioid toxicity in an attempt to identifypatients with a similar level of pain. Patients in the TDD and CMM group and the CMM only groupwere mutually exclusive.

Patients in the TDD and CMM group were included if (1) they had an inpatient or outpatientclaim with the presence of a TDD system implantation (CPT code 62362) between January 1, 2009,and September 30, 2015 (the first observed TDD pump implant service date or replacementprocedure in this period was the index date) and (2) a cancer diagnosis code was present (ICD-9-CMcodes 140.xx-209.xx, 230.xx-234.xx, or 235.xx-239.xx) on a claim within 3 months before or on theindex date. Patients receiving TDD were excluded if they had (1) a history of TDD, including pumpprogramming, analysis, refill, or removal codes (CPT codes 62367, 62368, 62365, 62369, 62370,95990, or 95991) occurring before the index date or (2) at least 1 diagnosis code of spasticity within3 months before or on the index date. This exclusion was made based on the assumption thatpatients received TDD therapy for spasticity.

Patients receiving CMM were included if (1) they had an inpatient hospital claim, includingcancer diagnosis codes, in any position on the claim (ICD-9-CM codes 140.xx-209.xx, 230.xx-234.xx,or 235.xx-239.xx) between January 1, 2009, and September 30, 2015 (the inpatient visit admissiondate was the index date); (2) the index inpatient hospital visit included at least 2 additional diagnosiscodes for symptoms associated with uncontrolled cancer pain, including nausea and/or vomiting(ICD-9-CM codes 787.01-787.03), anorexia (ICD-9-CM code 783.0), cachexia (ICD-9-CM code 799.4),somnolence (ICD-9-CM code 780.09), constipation (ICD-9-CM code 564.0), fecal impaction (ICD-9-CM code 560.32), bowel obstruction (ICD-9-CM code 560.9), or decreased mental status (ICD-9-CM code 780.97); and (3) they had at least 1 opioid prescription filled in the 6 months before or onthe index date. Patients receiving CMM were excluded if they had any evidence of TDD during theanalysis period (CPT codes 62362, 62367, 62368, 62365, 62369, 62370, 95990, 95991, 62350,62351, or 62355). All patients had continuous health care plan enrollment with drug coverage for aminimum of 6 months before and 2 months after the index date.

Study DesignA matched retrospective cohort study was conducted to analyze cost from the payer perspective.The baseline period was defined as the 6-month period before but not including the index date.

The follow-up periods were defined as 2, 6, and 12 months after and including the index date.These periods were selected to mirror the time points studied in the initial analysis performed with2006 to 2010 cost data and another previous cost analysis.13 The health care utilization andpayments for the matched pairs were compared for patients who had continuous health planenrollment at each time point. Total insurer cumulative costs associated with all-cause health careutilization were calculated at 2, 6, and 12 months. All paid insurer costs were included regardless ofassociated health care utilization itemization. Inpatient hospital, outpatient hospital, ED, office,home, and other service visits were recorded. Length of stay was calculated. Number of prescriptionsfilled for select medications associated with pain relief or opioid-related complications was alsoreported.

A series of variables were measured during the baseline period for consideration in thematching process. Covariates included in the final model (Table 1) were chosen to maximize sample




http://www.equator-network.org/reporting-guidelines/cheers/

Table 1. Patient Characteristics During Baseline Perioda

Characteristic

Before Propensity Score Matching After Propensity Score Matching

TDD and CMM Group(n = 376)

CMM Only Group(n = 4839) P Value



Age, mean (SD), y 51.88 (9.98) 51.52 (11.16) .50 51.91 (10.20) 52.27 (11.19) .70

Sex

Male 160 (42.6) 1834 (37.9).07

115 (42.9) 116 (43.3).93

Female 216 (57.5) 3005 (62.1) 153 (57.1) 152 (56.7)

Region

Northeast 40 (10.6) 605 (12.5)

<.001

30 (11.2) 25 (9.3)

.90

North Central 132 (35.1) 1248 (25.8) 87 (32.5) 88 (32.8)

South 112 (29.8) 2100 (43.4) 83 (31.0) 79 (29.5)

West 90 (23.9) 852 (17.6) 67 (25.0) 75 (28.0)

Unknown 2 (0.5) 34 (0.7) 1 (0.4) 1 (0.4)

Charlson Comorbidity Index

0-2 88 (23.4) 2105 (43.5)

<.001

75 (28.0) 88 (32.8)

.663-7 41 (10.9) 736 (15.2) 35 (13.1) 35 (13.1)

8 156 (41.5) 1316 (27.2) 106 (39.6) 97 (36.2)

>8 91 (24.2) 682 (14.1) 52 (19.4) 48 (17.9)

Index year

2009 28 (7.5) 431 (8.9)

<.001

21 (7.8) 23 (8.6)

.25

2010 59 (15.7) 779 (16.1) 42 (15.7) 41 (15.3)

2011 80 (21.3) 858 (17.7) 57 (21.3) 45 (16.8)

2012 84 (22.3) 871 (18.0) 60 (22.4) 59 (22.0)

2013 65 (17.3) 728 (15.0) 44 (16.4) 40 (14.9)

2014 54 (14.4) 790 (16.3) 39 (14.6) 44 (16.4)

2015 6 (1.6) 382 (7.9) 5 (1.9) 16 (6.0)

No. of inpatient hospital visits, mean (SD) 1.30 (1.55) 0.28 (0.73) <.001 0.93 (1.21) 0.86 (2.00) .66

Time in hospital, mean (SD), d 9.84 (15.60) 0.81 (4.04) <.001 5.80 (9.81) 4.90 (13.22) .37

No. of emergency department visits, mean (SD) 1.23 (2.27) 0.90 (1.88) .007 1.10 (2.42) 0.90 (2.18) .32

No. of outpatient visits, mean (SD) 14.81 (12.62) 11.08 (11.43) <.001 13.46 (12.16) 11.48 (11.75) .06

Total payment, $ 110 835 52 938 <.001 86 008 75 375 .17

Chemotherapy 153 (40.7) 2057 (42.5) .50 114 (38.4) 102 (38.1) .93

Radiotherapy 117 (31.1) 1065 (22.0) <.001 66 (24.6) 57 (21.3) .36

Tumor treatmentsb 33 (8.8) 455 (9.4) .71 18 (6.7) 21 (7.8) .62

Biopsy 136 (36.2) 2642 (54.6) <.001 97 (36.2) 107 (39.9) .37

Oncologist visits 176 (46.8) 1771 (36.6) <.001 117 (43.7) 111 (41.4) .60

Pain specialist visits 132 (35.1) 121 (2.5) <.001 62 (23.1) 70 (26.1) .42

Certain drug usec 258 (68.6) 3189 (65.9) .28 171 (63.8) 169 (63.1) .86

Anticonvulsant use 151 (40.2) 653 (13.5) <.001 97 (36.2) 104 (38.8) .53

Antidepressant use 200 (53.2) 1452 (30.0) <.001 139 (51.9) 145 (54.1) .60

Anxiolytic drug use 230 (61.2) 2342 (48.4) <.001 158 (59.0) 155 (57.8) .79

Corticosteroid use 156 (41.5) 1834 (37.9) .17 109 (40.7) 92 (34.3) .13

Opioid or tramadol use 354 (94.2) 4815 (99.5) <.001 253 (94.4) 251 (93.7) .72

Hypertension drugs 140 (37.2) 1412 (29.2) .001 97 (36.2) 97 (36.2) 1.0

Diabetes drugs 53 (14.1) 571 (11.8) .18 39 (14.6) 47 (17.5) .35

Psychostimulants 22 (5.9) 97 (2.0) <.001 15 (5.6) 13 (4.9) .70

Metastatic disease 239 (63.6) 1907 (39.4) <.001 151 (56.3) 139 (51.9) .30

Multiple cancer diagnostic codes(not multiple primary cancers)

274 (72.9) 2797 (57.8) <.001 177 (66.0) 160 (59.7) .13

(continued)




size while accounting for imbalances in patient characteristics. This approach allowed for betterassessment of the treatment effect between TDD and CMM and CMM only and further controlled forpain severity, given the lack of pain scores in claims data. Matching characteristics were selected tobest identify patients with similar demographics, cancer type, and treatment patterns for cancer andpain before the index date. Baseline variables included demographics, total payment, cancer type(eAppendix 1 in the Supplement), Charlson Comorbidity Index (eTable in the Supplement), physicianspecialties, chemotherapy and radiotherapy (eAppendix 2 in the Supplement), health care utilization,prescription drug use, and tumor treatment (eAppendix 3 in the Supplement).

Statistical AnalysisDescriptive analyses were performed to compare costs between TDD and CMM and CMM onlyduring the baseline and follow-up periods. Patient demographics, comorbidities, clinicalcharacteristics, health care utilization, payment, and prescription drug use were examined using thet test, χ2 test, or Fisher exact test. The t test was selected for data analysis because cost analysis isfocused on assessing mean costs rather than medians; this approach for analyzing large public healthdata sets, even in cases of nonnormally distributed data, is supported in the published literature.19-22

Propensity score matching balanced the baseline characteristics between the 2 groups forpatients with 2 months or more of postindex follow-up. A logistic regression model was used toestimate propensity scores for each patient; 32 baseline characteristic variables were included in themodel. Matching on a large number of characteristics resulted in many patients being excluded fromthe analysis but ensured that comparisons made between the groups were appropriate. Variableswere selected to best match patients receiving TDD and CMM and those receiving CMM only forsimilar treatments and health care utilization for cancer and pain care in the baseline period.Characteristics associated with cost, health care utilization, or pain treatment were selected based onour clinical experience. A sensitivity analysis was performed with a 20-characteristic model. Thismodel resulted in unbalanced patient characteristics at some time points; according to the studyprotocol, the matching method used resulted in balanced characteristics at all periods. Patientsreceiving TDD and CMM and patients receiving CMM only were matched based on their propensityscores using the caliper criteria. A 1:1 propensity score matching without replacement algorithm wasused. The t test was used to compare matched pairs for cost and health care utilization.

Patient attrition was expected given the cancer diagnosis and the nature of the data set; patientenrollment in the data set may be affected by insurance changes, employment changes, or death. Asa result of patient attrition, baseline characteristics of the remaining postmatch study populationwere retested by group for patients who also had 6 and 12 months of follow-up data. No statistically

Table 1. Patient Characteristics During Baseline Perioda (continued)

Characteristic

Before Propensity Score Matching After Propensity Score Matching





Cancer

Oral 15 (4.0) 368 (7.6) .01 11 (4.1) 8 (3.0) .48

Skin 45 (12.0) 373 (7.7) .003 30 (11.2) 27 (10.1) .67

Bone or bony 168 (44.7) 866 (17.9) <.001 99 (37.0) 89 (33.2) .37

Colorectal 60 (16.0) 498 (10.3) <.001 37 (13.8) 31 (11.6) .44

Pancreatic 41 (10.9) 276 (5.7) <.001 27 (10.1) 28 (10.5) .89

Digestive system 168 (44.7) 1403 (29.0) <.001 105 (39.2) 99 (37.0) .59

Abbreviations: CMM, conventional medical management; TDD, targeted drug delivery.a Data are presented as number (percentage) of patients unless otherwise indicated.b Tumor treatment indicates whether patients have evidence of tumor ablation, excision,

resection, or destruction during the baseline period, indicating active tumor treatment.

c The patient was receiving prescription medication that is commonly used to addressthe adverse effects of long-term opioid use. For match purposes, these were combinedinto 1 variable (appetite enhancer, antiemetic, and laxative use).








significant differences were found between the 2 groups at any point; follow-up comparisons wereappropriate.

The mean health services payments and utilization for the matched pairs were calculated andcompared at 2, 6, and 12 months. All payer expenditures were adjusted to 2015 US dollars using theMedical Care Consumer Price Index.23 These cost estimates are inclusive of the cost of TDD implanton the index date.

All statistical tests used a 2-sided significance level of P < .05. All analyses were performed usingSAS statistical software, version 9.2 (SAS Institute Inc).

Results

Patient PopulationA total of 376 TDD and CMM patients (mean [SD] age, 51.88 [9.98] years; 216 [57.5%] female) and4839 CMM only patients (mean [SD] age, 51.52 [11.16] years; 3005 [62.1%] female) were identifiedfor study inclusion. The patient selection strategy is shown in Figure 1. A TDD system was implantedin 1251 patients with a cancer diagnosis within 3 months before or on their index date betweenJanuary 1, 2009, and September 30, 2015. Of these, 376 patients met the inclusion criteria for theTDD and CMM population before matching (Table 1).

Figure 1. Patient Selection Strategy

>99 Million unique patients in MarketScan Commercial Claims Database (2009-2015)

6494 Selected patients with certain types of cancer

9499 With implanted pump to treat severeuncontrolled pain

8248 Excluded (without cancer)

682 Excluded (without continuoushealth plan enrollment) 4630 Excluded (without continuous

health plan enrollment)

190 Excluded123 With history of pump

programming, analysis,refill, or removal beforeindex date

67 Received treatment withintrathecal baclofen(spasticity diagnosis code≤3 mo before or on indexdate)

86 Excluded(Receiving TDD for spasticity or non-malignant pain and history of pumpimplant programming, analysis, refill,or removal during study period)

569 Remaining in data set through baselineand follow-up periodsa

376 With TDD and CMM before matching

28 857 With cancer and uncontrolled pain

18 026 Excluded (without opioidprescription during baseline or onindex date)

10 831 With severe uncontrolled pain(≥1 opioid presciption in baselineperiod or on index date)

1251 With cancer diagnosis ≤3 mo beforeor on index date

6201 Remaining in data set through baselineand follow-up periodsa

4839 With CMM before matching

3 Excluded (without cancer typesof interest)

1276 Excluded (without cancer types ofinterest)

Patients in the targeted drug delivery (TDD) and conventional medical management(CMM) and CMM only groups before matching were selected according to the criteriadescribed in the Study Population subsection of the Methods section.

a At least 6 months continuous health plan enrollment before the index date and at least2 months after the index date with prescription drug coverage.




A total of 710 637 patients were hospitalized with a cancer diagnosis between January 1, 2009,and September 30, 2015. A total of 10 831 patients (1.5%) had at least 2 additional diagnosis codesassociated with uncontrolled pain on the index date and 1 or more opioid prescriptions in the baselineperiod. A total of 4839 patients met all inclusion criteria for the CMM population before matching(Table 1).

Prematch and Postmatch Baseline Characteristics and Study PopulationA total of 5215 patients met the inclusion criteria before matching (376 in the TDD and CMM groupand 4839 in the CMM group); baseline characteristics were not balanced (Table 1). Compared withthe unmatched CMM population, the TDD and CMM population had statistically higher health careutilization and cost during the baseline period. After matching, 536 patients were identified (268 inthe TDD and CMM group and 268 in the CMM only group); baseline characteristics werestatistically similar.

During our study, 268 matched pairs were identified at the 2-month follow-up period. At 6months, 151 patients receiving TDD and CMM and 162 receiving CMM only remained. At 12 months,90 patients were receiving TDD and CMM and 98 were receiving CMM only.

Postmatch Follow-up OutcomesCostsThe TDD and CMM group had lower total costs than the CMM only group at 2 and 12 months. Themean cost difference at 2 months was $15 142 (95% CI, $3690-$26 594; P = .01), with a meandifference (MD) of $63 498 (95% CI, $4620-$122 376; P = .03) at 12 months. The cost difference at6 months ($19 577; 95% CI, −$12 831 to $51 984; P = .24) was not statistically different. Comparedwith the CMM only group, the TDD and CMM group had significantly lower inpatient hospital costs(2-month MD, $25 479; 95% CI, $15 041 to $35 917; P < .001; 6-month MD, $19 820; 95% CI, −$8912to $48 552; P = .18; 12-month MD, $49 104; 95% CI, −$1322 to $99 530; P = .06) (Table 2).Conversely, the patients receiving TDD and CMM had significantly higher outpatient hospital costs(2-month MD, $10 130; 95% CI, $6175-$14 086; P < .001) and other medical costs (2-month MD,$1735; 95% CI, $394-$3076; P = .01) than patients receiving CMM only at 2 months, although thesecosts were not significantly different subsequently. Office, home, ED, and outpatient pharmacy costswere not statistically different at any time point. Most all-cause costs occurred in the inpatient andoutpatient hospital settings for both groups (Figure 2).

Medical Service UtilizationPatients receiving TDD and CMM had a significantly lower mean number of inpatient hospital visits(2-month MD, 1.0; 95% CI, 0.8-1.2; P < .001; 6-month MD, 1.3; 95% CI, 0.8-1.7; P < .001; 12-monthMD, 2.3; 95% CI, 1.2-3.4; P < .001), shorter length of stay (2-month MD, 6.8 days; 95% CI, 5.0-8.7days; P < .001; 6-month MD, 6.8 days; 95% CI, 3.1-10.5 days; P < .001; 12-month MD, 10.6 days; 95%CI, 2.9-18.3 days; P = .007), and fewer ED visits (2-month MD, 0.3; 95% CI, 0.2-0.5; P < .001)compared with those receiving CMM only (Figure 3A).

Pharmacy UtilizationThe TDD and CMM group had a significantly lower mean number of corticosteroid (6-month MD, 0.5,95% CI, 0.1-0.9; P = .006), antiemetic (2-month MD, 0.4; 95% CI, 0.1-0.7; P = .003; 6-month MD,0.9; 95% CI, 0.1-1.7; P = .02), and opioid (12-month MD, 3.2; 95% CI, 0.4-6.0; P = .03) prescriptionscompared with the CMM only group (Figure 3B). Conversely, the TDD and CMM group had astatistically higher mean number of anticonvulsant prescriptions (2-month MD, 0.2; 95% CI, 0.04-0.4; P = .02).




Discussion

Health care utilization and costs in the MarketScan database from 2009 to 2015 were analyzed for536 patients with cancer-related pain. The TDD and CMM group had significant cost savings at 2 and12 months and significantly lower total health care utilization than the CMM group at 2, 6, and 12months. Important shifts in cancer care have occurred since 2006, when an earlier pilot study13

found lower utilization and costs for patients receiving TDD and CMM compared with patientsreceiving CMM only. Of note, the volume of inpatient services decreased, whereas the volume oflower-acuity services increased.24,25 Decreased inpatient hospitalizations for both groups mayreflect overall changes in health care utilization since 2006 but still favored TDD and CMM overCMM only.

Table 2. Payments by Treatment Group During 12 Monthsa

Payment Typeand Month

Payment, $ (2015)

P Value

TDD and CMM GroupCMM Only Group,Median (IQR)

Mean Difference(95% CI)Mean (SD) Median (IQR) Mean (SD)

Inpatient hospital

2 22 268 (51 667) 3127 (20 638) 47 747 (47 747) 22 801 (41 828) 25 479 (15 041 to 35 917) <.001

6 42 436 (150 614) 9899 (32 364) 62 256 (100 759) 33 176 (64 719) 19 820 (−8912 to 48 552) .18

12 45 741 (173 371) 10 612 (36 160) 94 845 (176 626) 41 786 (88 586) 49 104 (−1322 to 99 530) .06

Outpatienthospital

2 22 073 (25 538) 13 109 (31 449) 11 943 (20 841) 3841 (11 620) 10 130 (6175 to 14 086) <.001

6 35 978 (42 157) 19 359 (39 798) 33 005 (54 200) 10 989 (30 329) 2974 (−7788 to 13 745) .59

12 40 417 (41 149) 29 463 (36 545) 48 596 (79 724) 19 786 (35 796) 8180 (−9896 to 26 256) .37

Office

2 3031 (6444) 880 (2085) 4294 (9216) 669 (3746) 1263 (−86 to 2613) .07

6 7840 (14 336) 2889 (5799) 11 490 (22 562) 2545 (9445) 3650 (−528 to 7828) .09

12 14 319 (28 494) 5679 (9418) 21 098 (36 651) 5498 (12 370) 6780 (−2627 to 16 187) .16

Home

2 1 041(1041) 0 (531) 1302 (1302) 0 (700) 261 (−691 to 1213) .59

6 1450 (2993) 0 (1577) 2446 (8738) 0 (1333) 996 (−441 to 2432) .17

12 1836 (1836) 183 (1808) 3864 (3864) 306 (2188) 2028 (−644 to 4699) .14

Emergencydepartment

2 470 (1909) 0 (167) 678 (1835) 0 (597) 208 (−110 to 525) .20

6 1414 (6906) 0 (735) 1442 (3407) 250 (1441) 28 (−1199 to 1255) .96

12 1391 (2898) 0 (967) 2189 (6383) 311 (1441)) 798 (−613 to 2209) .27

Outpatientpharmacy

2 2926 (4671) 970 (2828) 2723 (4682) 989 (2587) 204 (−590 to 998) .61

6 9278 (14 445) 3969 (8594) 8106 (13 390) 3053 (6928) 1172 (−1924 to 4267) .46

12 18 039 (29 334) 7563 (15 913) 13 333 (21 472) 6654 (12 176) 4706 (−2752 to 12 164) .21

Other medicalcosts

2 3544 (3544) 0 (1121) 1809 (1809) 36 (1049) 1735 (394 to 3076) .01

6 3982 (9306) 213 (2136) 3210 (9547) 124 (1990) 772 (−1328 to 2871) .47

12 4469 (8218) 851 (2959) 5784 (20 000) 506 (3098) 1315 (−3034 to 5664) .55

Total medical andpharmacy costs

2 55 353 (58 610) 39 097 (45 309) 70 495 (75 307) 48 757 (61 356) 15 142 (3690 to 26 594) .01

6 102 377 (164 124) 65 876 (94 526) 121 954 (122 492) 93 226 (117 399) 19 577 (−12 831 to 51 984) .24

12 126 211 (187 581) 80 491 (122 852) 189 709 (218 735) 136 620 (158 267) 63 498 (4620 to 122 376) .03

Abbreviations: CMM, conventional medical management; IQR, interquartile range; TDD,targeted drug delivery.

a The TDD sample sizes were 268 at 2 months, 151 at 6 months, and 90 at 12 months. TheCMM sample sizes were 268 at 2 months, 162 at 6 months, and 98 at 12 months.




This matched retrospective analysis of a large payer database found that use of TDD and CMMwas associated with a mean cost savings of $63 498 (P = .03) at 12 months. The primary cost driversfor both groups were hospital inpatient and outpatient categories.

At 2 months, TDD and CMM was already associated with an overall mean cost savings ($15 142,P = .01), with significantly lower inpatient hospital costs (mean cost difference, $25 479; 95% CI,$15 041-$35 917; P < .001) compared with CMM only (Table 2). Even with a significant total costsavings for TDD and CMM at 2 months, outpatient cost was significantly greater for TDD and CMM,suggesting that TDD implants were more likely administered in an outpatient service on the indexdate; no significant cost difference was found for hospital outpatient services at 6 or 12 months.

A previous study26 found that high-cost end-of-life cancer expenditures are primarily associatedwith emergency and inpatient care. In 2010, the United States had the highest incidence of intensivecare unit admissions and hospital expenditures for patients with cancer older than 65 years who diedof cancer across 7 developed countries.27 In our study, TDD and CMM had significantly lowerutilization, with fewer inpatient hospital visits and shorter hospital stays at 2, 6, and 12 months. Thenumber of visits to oncology and pain physicians, as well as the number of visits performed in thehospital outpatient or home health setting, were not significantly different between the matchedgroups at any period after the index date.

Cancer pain has been associated with high prescriptive opioid and adjuvant medication use.28

This study assessed pharmaceutical use by drug class and found that patients receiving TDD andCMM were prescribed fewer medications typically used to treat pain and opioid-inducedcomplications. Data analysis and knowledge of physician prescribing patterns allowed us to assumethat anticonvulsant use was higher at 2 months in the TDD and CMM group because of earlierintroduction by pain management physicians. Corticosteroid use was higher in the CMM group at 6months, possibly reflecting prescribing by oncology and palliative medicine physicians to treat painand nausea and increase appetite. Opioid use was greater for CMM at 12 months, suggesting thatTDD is associated with decreased systemic opioid use in surviving patients. Antidepressant andanxiolytic use increased in both groups over time, likely in association with worsening pain oremotional distress over diminished function, disease progression, and poor prognosis.

Smith et al12 found that patients receiving TDD and CMM had fewer medication-inducedadverse effects than patients receiving CMM only. Rapid titration and low medication tolerance in theCMM group may result in adverse effects, which may require increased ED or hospital visits andfrequent or long inpatient stays to control pain.

Figure 2. All-Cause Costs for the Targeted Drug Delivery (TDD) and Conventional Medical Management (CMM) Group and the CMM Only Group

70 000

80 000

90 000

100 000

60 000

50 000

40 000

30 000

20 000

10 000

0

Cost

s, $

(201

5)

Treatment Group and Time Point

TDD and CMM2 mo

CMM2 mo

a

a

a

TDD and CMM6 mo

CMM6 mo

TDD and CMM12 mo

CMM12 mo

EDInpatient hospital OfficeOutpatient hospital OtherHome health Pharmacy

a

ED indicates emergency department; IP, inpatient; and OP, outpatient.a Statistically significant differences for TDD and CMM compared with CMM only.




Cancer treatment improvements in the past 2 decades have been associated with increasedsurvivorship, further compounding health care costs. In 2020, there will be an estimated 18 millioncancer survivors.29 Opioids have many long-term health risks.9 Continued use of opioids isassociated with increased health care cost and utilization. A previous study30 found that the opioid

Figure 3. Medical Service and Pharmacy Utilization for the Targeted Drug Delivery (TDD) and Conventional Medical Management (CMM) Group and the CMM Only Group

Medical servicesA 2 Months

6 Months

12 Months

2 Months

6 Months

12 Months

Serv

ice

Type

Ther

apeu

tic C

lass

0 5 10 15 20 25 30 35

Mean No. of Visits or Services

Antidepressant(TDD and CMM)

Antidepressant(CMM)

Anticonvulsant(TDD and CMM)

Anticonvulsant(CMM)

Anxiolytic(TDD and CMM)

Anxiolytic(CMM)

Corticosteroid(TDD and CMM)

Corticosteroid(CMM)

Appetite Enhancer(TDD and CMM)

Appetite Enhancer(CMM)

Antiemetic(TDD and CMM)

Antiemetic(CMM)

Laxative(TDD and CMM)

Laxative(CMM)

Opioids(TDD and CMM)

Opioids(CMM)

Tramadol(TDD and CMM)

Tramadol(CMM)

Psychostimulant(TDD and CMM)

Psychostimulant(CMM)

Pharmacy servicesB

0 1 2 3 4 5 6 7 8 9 10 11 12

Mean No. of Visits or Services

Inpatient Hospital(TDD and CMM)

Inpatient Hospital(CMM)

LOS(TDD and CMM)

LOS(CMM)

ED(TDD and CMM)

ED(CMM)

Outpatient Hospital(TDD and CMM)

Outpatient Hospital(CMM)

Office(CMM)

Office(TDD and CMM)

Home Health(TDD)

Home Health(TDD and CMM)

a

a

a

a

a

a

a

a

a

a

a

a

ED indicates emergency department; LOS, length of stay.a Statistically significant differences for TDD and CMM compared with CMM only.




prescription rate among cancer survivors at least 5 years after diagnosis was 1.22 times higher thanfor matched patients without cancer. Worsening disability, loss of independence, or diminishedintellectual and mental processing are associated with long-term systemic opioid therapy.9 Targeteddrug delivery provides an alternative option for pain control in cancer survivors.

This study presents a direct medical cost assessment from the payer perspective. In addition todirect patient care costs, additional costs associated with subsequent informal care and productivityare relevant to considering the total cost of any therapy.31 Caregivers assume substantial personal,economic, and psychological burdens and are critically important partners for patients with cancerand practitioners. Access to and expense of clinical treatment, along with care beyond the clinicalenvironment, prove to be substantial whether a patient lives independently or with their primarycaregiver. Costs to consider include home care or caregiver support, lost wages, travel cost, anddependent care arrangements for other family members.32

The decision criteria for managing cancer pain are complicated because treatment planning forthe best medical outcome includes assessment of patient and caregiver capacity to logistically,psychologically, and economically facilitate ongoing care access.33 Targeted drug delivery should beconsidered as an option to alleviate caregiver burden and limit societal cost.

The safety and efficacy of TDD for cancer pain treatment should also be considered. Resultsfrom a large multicenter registry study demonstrated that TDD was significantly associated withrelieved baseline pain at 6 and 12 months after implantation, and quality of life (EQ-5D Index)significantly improved at 6 months.34 Long-term survivors demonstrated sustained quality-of-lifeimprovement, with EQ-5D scores greater than 0.6 (with 1 indicating best health state) at 5 and 10years after implantation. These clinical outcomes, combined with the robust financial savings,demonstrated within a year of starting therapy suggest that TDD offers clinical and economic value.

Society is faced with balancing costs and patient quality of life. This study highlights thechallenges faced by payers and oncology practices managing patients with terminal, treatable, andtreated cancers who have pain. Limited health care funds will increasingly affect medical decisionmaking as the aging US and global populations continue to increase.

LimitationsThis study has limitations. Mainly, MarketScan data are collected for billing purposes; informationthat does not influence reimbursement and coverage may not be reported. For example, cancerseverity, quality-of-life scores, and death-related variables are not captured in claims data. However,based on patient characteristics and treatment patterns, we believe that this would not affect ourresults. In addition, it was unclear whether enrollment decline after index was attributable to deathor a change in health care plans. It is also possible that propensity score matching did not account forunobserved selection bias because it can only control for the observed differences between groups.Factors such as pain scores and other multifactorial differences in both groups were not able to beanalyzed with this data set. Also, this study used commercial insurance participants, which allowsgeneralization to the larger US commercially insured population; further research is needed toexplore other populations or health care systems.

Conclusions

Our study suggests that TDD is associated with reduced health care utilization and cost for patientswith cancer pain. Increased use of TDD may also have the potential to reduce future health care costand utilization associated with the expected incidence and survivorship of cancer in the UnitedStates. In addition, TDD may reduce long-term systemic opioid use and associated inherent risksamong cancer survivors and society. Consideration of TDD for more patients with significant cancer-related pain may be associated with robust financial savings and improved quality of life.




ARTICLE INFORMATIONAccepted for Publication: February 5, 2019.

Published: April 5, 2019. doi:10.1001/jamanetworkopen.2019.1549

Correction: This article was corrected on May 17, 2019, to fix an error in Figure 2.

Open Access: This article is published under the JN-OA license and is free to read on the day of publication.

Corresponding Author: Lisa J. Stearns, MD, Center for Pain and Supportive Care, 4611 E Shea Blvd, Bldg 3, Ste 190,Phoenix, AZ 85028 ([email protected]).

Author Affiliations: Center for Pain and Supportive Care, Phoenix, Arizona (Stearns, Hammond); Department ofAnesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Hospital, Boston, Massachusetts(Narang); Department of Anesthesiology, Harvard Medical School, Boston, Massachusetts (Narang); Provectus,Knoxville, Tennessee (Albright); Health Economics and Outcomes Research, Medtronic, Minneapolis, Minnesota(Xia, Doth); Geomedicus LLC, New Orleans, Louisiana (Richter); Arizona Palliative Home Care, Phoenix(Paramanandam); Medical and Scientific Affairs, Medtronic, Minneapolis, Minnesota (Haagenson).

Author Contributions: Dr Stearns had full access to all the data in the study and takes responsibility for theintegrity of the data and the accuracy of the data analysis.

Concept and design: Stearns, Albright, Hammond, Xia, Richter, Haagenson, Doth.

Acquisition, analysis, or interpretation of data: Stearns, Narang, Albright, Xia, Richter, Paramanandam, Doth.

Drafting of the manuscript: Stearns, Narang, Albright, Hammond, Xia, Richter, Haagenson, Doth.

Critical revision of the manuscript for important intellectual content: Stearns, Narang, Albright, Hammond, Richter,Paramanandam, Haagenson, Doth.

Statistical analysis: Narang, Xia, Richter, Doth.

Administrative, technical, or material support: Stearns, Narang, Albright, Hammond, Xia, Doth.

Supervision: Stearns, Narang, Richter, Doth.

Conflict of Interest Disclosures: Drs Xia and Haagenson and Ms Doth reported being employees of Medtronic. DrStearns reported being a paid consultant for Medtronic, Flowonix, and Spinal Modulation and receiving researchsupport from the Alfred Mann Foundation, Mallinckrodt Pharmaceuticals, Medallion Therapeutics Inc, Medtronic,Piramal, Nevro, and Boston Scientific for services unrelated to the current research. Dr Narang reported being apaid consultant for Medtronic for services unrelated to the current research. Dr Albright reported being a paidconsultant for Medtronic for services unrelated to the current research. Dr Richter reported receiving grants fromMedtronic outside the submitted work. No other disclosures were reported.

Funding/Support: This project was sponsored by Medtronic.

Role of the Funder/Sponsors: Medtronic was involved in the design and conduct of the study; collection,management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; anddecision to submit the manuscript for publication.

Additional Contributions: Linda Holtzman, MHA, RHIA, CCS, CCS-P, CPC, COC, Clarity Coding Inc, providedsupport in developing the International Classification of Diseases, Ninth Revision, Clinical Modification diagnosiscode list used in this research and was compensated by Medtronic for her work. Xinling (Claire) Xu, PhD, Brighamand Women’s Hospital, provided statistical assessment. She was not compensated for her work. Sarah Staples, MA,ELS, Staples, Etc, provided medical writing support with formatting and incorporation of comments from allauthors and was compensated by Medtronic for her assistance.

REFERENCES1. Mariotto AB, Yabroff KR, Shao Y, Feuer EJ, Brown ML. Projections of the cost of cancer care in the United States:2010-2020. J Natl Cancer Inst. 2011;103(2):117-128. doi:10.1093/jnci/djq495

2. Bluethmann SM, Mariotto AB, Rowland JH. Anticipating the “silver tsunami”: prevalence trajectories andcomorbidity burden among older cancer survivors in the United States. Cancer Epidemiol Biomarkers Prev. 2016;25(7):1029-1036. doi:10.1158/1055-9965.EPI-16-0133

3. Kline RM, Bazell C, Smith E, Schumacher H, Rajkumar R, Conway PH. Centers for Medicare and MedicaidServices: using an episode-based payment model to improve oncology care. J Oncol Pract. 2015;11(2):114-116. doi:10.1200/JOP.2014.002337

4. Patrick DL, Ferketich SL, Frame PS, et al. National Institutes of Health State-of-the-Science Conferencestatement: symptom management in cancer: pain, depression, and fatigue, July 15-17, 2002. J Natl Cancer InstMonogr. 2004(32):9-16.





https://jamanetwork.com/journals/jamanetworkopen/pages/instructions-for-authors#SecOpenAccess/?utm_campaign=articlePDF%26utm_medium=articlePDFlink%26utm_source=articlePDF%26utm_content=jamanetworkopen.2019.1549

mailto:[email protected]

https://dx.doi.org/10.1093/jnci/djq495

https://dx.doi.org/10.1158/1055-9965.EPI-16-0133

https://dx.doi.org/10.1200/JOP.2014.002337

5. Panattoni LE, Fedorenko CR, Kreizenbeck KL, et al. The role of chronic disease in the costs of potentiallypreventable emergency department use during treatment: a regional study. J Clin Oncol. 2017;35(15):6505. doi:10.1200/JCO.2017.35.15_suppl.6505

6. van den Beuken-van Everdingen MH, Hochstenbach LM, Joosten EA, Tjan-Heijnen VC, Janssen DJ. Update onprevalence of pain in patients with cancer: systematic review and meta-analysis. J Pain Symptom Manage. 2016;51(6):1070-1090, e1079.

7. Paice JA, Ferrell B. The management of cancer pain. CA Cancer J Clin. 2011;61(3):157-182. doi:10.3322/caac.20112

8. Cancer Pain Relief With A Guide to Opioid Availability. 2nd ed. Geneva, Switzerland: World Health Organization;1996. http://apps.who.int/iris/bitstream/10665/37896/1/9241544821.pdf. Accessed January 31, 2018.

9. Chou R, Turner JA, Devine EB, et al. The effectiveness and risks of long-term opioid therapy for chronic pain:a systematic review for a National Institutes of Health Pathways to Prevention Workshop. Ann Intern Med. 2015;162(4):276-286. doi:10.7326/M14-2559

10. Swarm R, Abernethy AP, Anghelescu DL, et al; NCCN Adult Cancer Pain. Adult cancer pain. J Natl Compr CancNetw. 2010;8(9):1046-1086. doi:10.6004/jnccn.2010.0076

11. Brogan SE, Winter NB, Abiodun A, Safarpour R. A cost utilization analysis of intrathecal therapy for refractorycancer pain: identifying factors associated with cost benefit. Pain Med. 2013;14(4):478-486. doi:10.1111/pme.12060

12. Smith TJ, Staats PS, Deer T, et al; Implantable Drug Delivery Systems Study Group. Randomized clinical trial ofan implantable drug delivery system compared with comprehensive medical management for refractory cancerpain: impact on pain, drug-related toxicity, and survival. J Clin Oncol. 2002;20(19):4040-4049. doi:10.1200/JCO.2002.02.118

13. Stearns LJ, Hinnenthal JA, Hammond K, Berryman E, Janjan NA. Health services utilization and payments inpatients with cancer pain: a comparison of intrathecal drug delivery vs. conventional medical management.Neuromodulation. 2016;19(2):196-205. doi:10.1111/ner.12384

14. Caraway D, Walker V, Becker L, Hinnenthal J. Successful discontinuation of systemic opioids after implantationof an intrathecal drug delivery system. Neuromodulation. 2015;18(6):508-515. doi:10.1111/ner.12318

15. Truven Heakth Analytics. Health Research Data for the Real World: The MarketScan Database (White Paper).Ann Arbor, MI: Truven Health Analytics; 2011. http://truvenhealth.com/portals/0/assets/PH_11238_0612_TEMP_MarketScan_WP_FINAL.pdf. Accessed August 21, 2017.

16. Truven Health Analytics. Commercial Claims and Encounters Medicare Supplemental (User Guide). Ann Arbor,MI: Truven Health Analytics; 2015. https://marketscan.truvenhealth.com/marketscanuniversity/userguide/2015%20MarketScanCCAE-MDCRUserGuide.pdf. Accessed August 21, 2017.

17. US Department of Health and Human Services Office for Human Research Protections. Human subjectregulations decision charts. 2016. https://www.hhs.gov/ohrp/regulations-and-policy/decision-charts/index.html#c1.Accessed January 17, 2019.

18. Hansen L. The Truven Health MarketScan databases for life sciences researchers. 2017. https://truvenhealth.com/Portals/0/Assets/2017-MarketScan-Databases-Life-Sciences-Researchers-WP.pdf. Accessed August 21, 2017.

19. Thompson SG, Barber JA. How should cost data in pragmatic randomised trials be analysed? BMJ. 2000;320(7243):1197-1200. doi:10.1136/bmj.320.7243.1197

20. Poncet A, Courvoisier DS, Combescure C, Perneger TV. Normality and sample size do not matter for theselection of an appropriate statistical test for two-group comparisons. Methodology. 2016;12:61-71.

21. Lumley T, Diehr P, Emerson S, Chen L. The importance of the normality assumption in large public health datasets. Annu Rev Public Health. 2002;23:151-169. doi:10.1146/annurev.publhealth.23.100901.140546

22. Fagerland MW. t-Tests, non-parametric tests, and large studies: a paradox of statistical practice? BMC Med ResMethodol. 2012;12:78. doi:10.1186/1471-2288-12-78

23. Medical care in U.S. city average, all urban consumers, not seasonally adjusted. 2017. https://data.bls.gov/timeseries/CUUR0000SAM?output_view=pct_12mths. Accessed February 27, 2019.

24. Report to the Congress: Medicare Payment Policy. Washington, DC: Medicare Payment Advisory Commission;March 13, 2015. http://www.medpac.gov/-documents-/reports. Accessed February 27, 2019.

25. Health Care Cost and Utilization Report: 2015. Washington, DC: Health Care Cost Institute; 2016. http://www.healthcostinstitute.org/report/2015-health-care-cost-utilization-report/. Accessed February 27, 2019.

26. Walsh B, Laudicella M. Disparities in cancer care and costs at the end of life: evidence from England’s NationalHealth Service. Health Aff (Millwood). 2017;36(7):1218-1226. doi:10.1377/hlthaff.2017.0167




https://dx.doi.org/10.1200/JCO.2017.35.15_suppl.6505


https://dx.doi.org/10.3322/caac.20112


http://apps.who.int/iris/bitstream/10665/37896/1/9241544821.pdf

https://dx.doi.org/10.7326/M14-2559

https://dx.doi.org/10.6004/jnccn.2010.0076

https://dx.doi.org/10.1111/pme.12060

https://dx.doi.org/10.1111/pme.12060

https://dx.doi.org/10.1200/JCO.2002.02.118

https://dx.doi.org/10.1200/JCO.2002.02.118

https://dx.doi.org/10.1111/ner.12384

https://dx.doi.org/10.1111/ner.12318

http://truvenhealth.com/portals/0/assets/PH_11238_0612_TEMP_MarketScan_WP_FINAL.pdf

http://truvenhealth.com/portals/0/assets/PH_11238_0612_TEMP_MarketScan_WP_FINAL.pdf

https://marketscan.truvenhealth.com/marketscanuniversity/userguide/2015%20MarketScanCCAE-MDCRUserGuide.pdf

https://marketscan.truvenhealth.com/marketscanuniversity/userguide/2015%20MarketScanCCAE-MDCRUserGuide.pdf

https://www.hhs.gov/ohrp/regulations-and-policy/decision-charts/index.html#c1

https://truvenhealth.com/Portals/0/Assets/2017-MarketScan-Databases-Life-Sciences-Researchers-WP.pdf

https://truvenhealth.com/Portals/0/Assets/2017-MarketScan-Databases-Life-Sciences-Researchers-WP.pdf

https://dx.doi.org/10.1136/bmj.320.7243.1197

https://dx.doi.org/10.1146/annurev.publhealth.23.100901.140546

https://dx.doi.org/10.1186/1471-2288-12-78

https://data.bls.gov/timeseries/CUUR0000SAM?output_view=pct_12mths

https://data.bls.gov/timeseries/CUUR0000SAM?output_view=pct_12mths

http://www.medpac.gov/-documents-/reports

http://www.healthcostinstitute.org/report/2015-health-care-cost-utilization-report/

http://www.healthcostinstitute.org/report/2015-health-care-cost-utilization-report/

https://dx.doi.org/10.1377/hlthaff.2017.0167

27. Bekelman JE, Halpern SD, Blankart CR, et al; International Consortium for End-of-Life Research (ICELR).Comparison of site of death, health care utilization, and hospital expenditures for patients dying with cancer in 7developed countries. JAMA. 2016;315(3):272-283. doi:10.1001/jama.2015.18603

28. Zuckerman IH, Davidoff AJ, Erten MZ, et al. Use of and spending on supportive care medications amongMedicare beneficiaries with cancer. Support Care Cancer. 2014;22(8):2185-2195. doi:10.1007/s00520-014-2187-2

29. Siegel R, DeSantis C, Virgo K, et al. Cancer treatment and survivorship statistics, 2012. CA Cancer J Clin. 2012;62(4):220-241. doi:10.3322/caac.21149

30. Sutradhar R, Lokku A, Barbera L. Cancer survivorship and opioid prescribing rates: a population-basedmatched cohort study among individuals with and without a history of cancer. Cancer. 2017;123(21):4286-4293.doi:10.1002/cncr.30839

31. Haltia O, Färkkilä N, Roine RP, et al. The indirect costs of palliative care in end-stage cancer: a real-lifelongitudinal register- and questionnaire-based study. Palliat Med. 2018;32(2):493-499. doi:10.1177/0269216317729789

32. Lambert SD, Girgis A. Unmet supportive care needs among informal caregivers of patients with cancer:opportunities and challenges in informing the development of interventions. Asia Pac J Oncol Nurs. 2017;4(2):136-139. doi:10.4103/2347-5625.204485

33. Gonzalo MB, House L, Santiago K, Buzaglo JS, Zaleta AK, Gupta NK. Access to care in cancer: barriers andchallenges. J Clin Oncol. 2017;35(8):33. doi:10.1200/JCO.2017.35.8_suppl.33

34. Stearns L. Targeted drug delivery (TDD) as a cancer-pain therapy option: registry safety and patient outcomes(ID 13337). Poster presented at: 22nd Annual Meeting of the North American Neuromodulation Society; January17-20, 2019; Las Vegas, Nevada.

SUPPLEMENT.eAppendix 1. Cancer Diagnosis CodeseAppendix 2. Chemotherapy and Radiation TherapyeAppendix 3. Tumor Ablation, Biopsy, Tumor Destruction, Tumor Excision, and Tumor ResectioneTable. Charlson Comorbidity Index




https://jama.jamanetwork.com/article.aspx?doi=10.1001/jama.2015.18603&utm_campaign=articlePDF%26utm_medium=articlePDFlink%26utm_source=articlePDF%26utm_content=jamanetworkopen.2019.1549

https://dx.doi.org/10.1007/s00520-014-2187-2


https://dx.doi.org/10.1002/cncr.30839

https://dx.doi.org/10.1177/0269216317729789

https://dx.doi.org/10.1177/0269216317729789

https://dx.doi.org/10.4103/2347-5625.204485


Documents

AssessmentofHealthCareUtilizationandCostofTargetedDrug ......2014 54 (14.4) 790 (16.3) 39 (14.6) 44 (16.4) 2015 6 (1.6) 382 (7.9) 5 (1.9) 16 (6.0) No. of inpatient hospital visits,