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S Bertel Squire, Anne Detjen, Pren Naidoo, Afranio Kritski, & Ivor Langley
Xpert MTB/RIF: a patient cost perspective
2 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Overview 1. Possible reasons why patient costs have been
ignored in the policy formulation and implementation for Xpert MTB/RIF
2. Current evidence for the effect of Xpert MTB/RIF on patient costs
• Presumptive / general TB cases • Presumptive MDR-TB cases
3. How Xpert MTB/RIF policy and implementation will change when we take patient costs more seriously
4. Conclusions
3 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Possible reasons why patient costs have been ignored in policy formulation and implementation for Xpert MTB/RIF
1. We don’t care about patient costs 2. There is no evidence that patient costs are
important in relation to TB diagnosis 3. Policy formulation and implementation is
currently unable to systematically assess evidence on patient costs in relation to other evidence
4 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Possible reasons why patient costs have been ignored in policy formulation and implementation for Xpert MTB/RIF
1. We don’t care about patient costs 2. There is no evidence that patient costs are
important in relation to TB diagnosis 3. Policy formulation and implementation is
currently unable to systematically assess evidence on patient costs in relation to other evidence
5 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Targets in the draft post-2015 TB Strategy
Indicator Milestone 2020
Target 2035
% reduction in deaths due to TB
35% 95%
% and absolute reduction in TB incidence rate
20% 90%
% families facing catastrophic costs due to TB
Zero Zero
6 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Possible reasons why patient costs have been ignored in policy formulation and implementation for Xpert MTB/RIF
1. We don’t care about patient costs 2. There is no evidence that patient costs are
important in relation to TB diagnosis 3. Policy formulation and implementation is
currently unable to systematically assess evidence on patient costs in relation to other evidence
7 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Three systematic reviews
• Ukwaja et al: The economic burden of tuberculosis care for patients and households in Africa: a systematic review. IJTLD 2012
• Barter et al: Tuberculosis and poverty: the contribution of patient costs in sub-Saharan Africa-- a systematic review, BMC Public Health 2012
• Tanimura et al Financial burden for tuberculosis patients in low- and middle-income countries: a systematic review. ERJ 2014
8 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Tanimura et al Financial burden for tuberculosis patients in low- and middle-income countries: a systematic review. ERJ 2014
1. 49 studies met inclusion criteria
2. Stratified costs into • Direct medical costs
– (consultations, tests, medicines & hospitalisation etc.) • Direct non-medical costs
– (transport & food during health care visits etc.) • Indirect costs
– (lost income)
3. Reported costs as a percentage of annual income
4. Extracted cost components separately for pre- and post-TB treatment periods
9 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Costs as a percentage of annual income (average of mean)
Studies n Direct costs %
Lost income %
Total costs %
Individual Reported
income 22 21 37 58
Annual Wage
35 9 21 30
Wage of lowest 20%
34 25 64 89
Reported household income
7 16 22 39
10 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Distribution of costs Before & After Diagnosis (8 studies)
11 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Possible reasons why patient costs have been ignored in policy formulation and implementation for Xpert MTB/RIF
1. We don’t care about patient costs 2. There is no evidence that patient costs are
important in relation to TB diagnosis 3. Policy formulation and implementation is
currently unable to systematically assess evidence on patient costs in relation to other evidence
12 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Active TB
Symptoms recognised
Health care utilisation
Diagnosis
Notification Infected
Patient delay
GRADE considers sensitivity and specificity, not the place of the test in the overall diagnostic process
13 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Economic Hurdles faced by an average rural resident accessing TB treatment in Malawi: 2004-5
Source: Gillian Mann PhD Thesis LSTM 2008
NB: no user fees in public health facilities
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
US$
Total Income
Food
Transport
Drugs
Fees
14 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Potential effect on patients costs of frontloading (2 specimens) with same-day issue of results
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
US$
Total Income
Food
Transport
Drugs
Fees
15 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Ø Many visits required • to provide
sputum samples • receive results • go for X-‐ray • commence
treatment Ø Each visit is costly
for the pa:ent
Home
TB Diagnostic
Centre
Becomes Sick with cough
TB Suspect
Provide Sputum
Sample 1
Health Clinic
Home
TB Diagnostic
CentreHome
TB Diagnostic
Centre
Home
ProvideSputum
Sample 2
Return Home
Receive Diagnosis
TB Diagnostic
Centre
ReceiveTreatmentMedicine
Home
TB Diagnostic
Centre
Treatment Monitoring
Return Home
Return Home
Return Home Returning
Every 2 wks for Medicines
At end of intermediate
phases if smear negative
SmearPositive
TB Diagnostic
Centre
Smear Negative
TB Diagnosed
At end of intermediatephases if smear Positive – TestFor Drug Resistance and put on
MDR -TB Treatment if found
Home
No TB Found
TB Cure
But pa:ent pathways are not linear
16 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Opera:onal Modelling -‐ capturing complex pathways -‐ Opera(onal model of TB diagnos(c centre in Tanzania
17 Postgraduate Course, Kuala Lumpur 14th Nov 2012
OPERATIONAL MODEL Patient & Health System Effects
TRANSMISSION MODEL Community & Disease Transmission Impacts
Lin HH, Langley I, et al. (2011), A modelling framework to support the selection and implementation of new tuberculosis diagnostic tools. Int J Tuberc Lung Dis 15(8):996–1004, doi:10.5588/ijtld.11.0062
Time to start treatment Diagnostic LTFU rate Output Input
Incremental Costs
TB Incidence rate Input Output
Combining the outputs to calculate the Incremental Cost Effectiveness Ratio (ICER)
Incremental DALY’s averted
Virtual Implementa:on -‐ A comprehensive approach
18 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Why don’t we stick with our current plans
for front-loaded LED?
Replace all microscopy with
Xpert this would save money which would offset the additional
cost per test for Xpert
Xpert should be focussed on MDR-TB, HIV+, & new smear negative
suspects
• When, where and how should Xpert MTB/RIF be used in Tanzania and why?
PuBng different op:ons into the Models
19 Postgraduate Course, Kuala Lumpur 14th Nov 2012
A -‐ SameDay LED
B Roll-‐outXpert
C-‐TargettedXpert
-‐$200
$0
$200
$400
$600
$800
$1,000
$1,200
$1,400
$0 $5 $10 $15 $20 $25 $30 $35 $40 $45 $50
Increase required in health system budget over 10 years ($m) -‐ SUSTAINABILITY
Cost per add
itional D
ALY averted
COST
EFFECTIVEN
ESS
Area of the circle represents the benefits of the intervention in DALY's averted over 10 years relative to LED
fluorescence microscopy
GDP per capita -‐ Tanzania -‐ $599
Results – Health system impacts -‐ Cost to the health system vs. ICER vs. DALY’s averted
But, what about the patient?
20 Postgraduate Course, Kuala Lumpur 14th Nov 2012
C -‐ TargettedXpert -‐$0.24
B -‐Roll-‐outXpert-‐$3.02
A -‐ Same Day LED,-‐$2.13
-‐1
1
3
5
7
9
11
-‐0.5 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5Increase required in health system budget for TB in Year 1 ($m)
The size of the circle is proportional to the patient cost benefit compared to ZN microscopy (e.g. Targetted Xpert benefit $0.24
per patient , Full Xpert roll-‐out benefit $3.02 per patient
Increase in num
ber o
f tho
se with TB
disease
starting & com
pleting TB
treatm
ent (,0
00's)
Modelling pa:ent impacts of TB diagnos:c algorithms -‐ Addi(onal health system costs vs increased numbers on appropriate TB treatment vs mean reduc(on in costs to pa(ent
21 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Possible reasons why patient costs have been ignored in policy formulation and implementation for Xpert MTB/Rif
1. We don’t care about patient costs ✖ 2. There is no evidence that patient costs are
important in relation to TB diagnosis ✖ 3. Policy formulation and implementation is
currently unable to systematically assess evidence on patient costs in relation to other evidence ✔
22 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Overview 1. Possible reasons why patient costs have been
ignored in the policy formulation and implementation for Xpert MTB/RIF:
2. Current evidence for the effect of Xpert MTB/RIF on patient costs
• Presumptive / general TB cases • Presumptive MDR-TB cases
3. How Xpert MTB/RIF policy and implementation will
change when we take patient costs more seriously 4. Conclusions
23 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Effect on general TB patients
24 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Median non-medical direct and indirect costs of 218 PTB patients
Costs Xpert (n=120)
Smear microscopy (n=98)
Difference of medians
P value
Non-medical direct
9.27 13.02 -3.75 0.003
Indirect 6.51 12.40 -5.89 <0.000 Total 16.44 25.24 -8.8 <0.000
25 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Overview 1. The magnitude and composition of patient costs
2. Understanding patient pathways and pre-treatment patient costs.
3. Impact of Xpert MTB/Rif on patient pathways and patient costs.
• Presumptive / general TB cases • Presumptive MDR-TB cases
4. Conclusions
Can new diagnostic tools reduce the time to appropriate TB treatment initiation? The Union Conference, Paris, 2013
A pragmatic randomised trial to assess impact of LPA versus Xpert MTB/RIF versus MGIT in Brazil
Afranio Kritski, Rede TB / Medical School – Federal University of Rio de Janeiro, Brazil
27
1. Inclusion criteria – adult DR/MDR TB suspects presen:ng with a) TB in the past
i. Suspected re-‐treatment failure or ii. Failure or smear posi8ve at 2 months
b) Without previous TB treatment i. Failure or smear posi8ve at 2 months or ii. HIV posi8ve or iii. Close contact with MDR-‐TB case or iv. Homeless
2. Cluster-‐randomised, crossover design • MGIT vs Xpert • MGIT vs LPA
PROVE-‐IT in Brazil -‐ DESIGN inclusion criteria and data collec(on
Ministry of Health, 2010.Guidelines for TB Control. Available at www.saude.gov.br/tuberculose.Acessed on 08/24/2013.
28
Total Patient Expenditure by Arm
Health systems evaluation of implementation and scale-up of LPA and Xpert MTB/RIF in
Cape Town
44th Union World Conference on Lung Health
Pren Naidoo, Elizabeth du Toit, Rory Dunbar, Margaret van Niekerk Carl Lombard, Judy Caldwell, Anne Detjen, S. Bertel Squire,
Donald A. Enarson, Nulda Beyers
TB Testing Algorithm
Universal Algorithm: Xpert MTB/RIF™ replaced smear All presumptive TB cases 2 sputa submitted Specimen 1 Specimen 2 Xpert Negative Culture if HIV+
Discard if HIV-/unknown MTB+, Rif sensitive Smear MTB+, Rif resistant Smear, culture, LPA and 2nd line DST
Smear if only 1 sputum sample submitted
Targeted Algorithm: Smear/Culture/DST (LPA) Low MDR-risk 2 sputa for smears (3rd for culture if Sm-, HIV+) High MDR-risk 2 sputa for smears, Culture, LPA DST
Comparison of Median Patient Costs in the Targeted and Universal Algorithms
$0
$10
$20
$30
$40
$50
$60
$70
$80
Targeted (n=89) $3 $0 $13 $24 $70 Universal (n = 64) $2 $0 $5 $14 $39
Direct Transport
Costs
Direct Medical Costs
Cost of Transport
Time
Cost of Time in HCF Total
32 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Overview 1. Possible reasons why patient costs have been
ignored in the policy formulation and implementation for Xpert MTB/RIF:
2. Current evidence for the effect of Xpert MTB/RIF on patient costs
• Presumptive / general TB cases • Presumptive MDR-TB cases
3. How Xpert MTB/RIF policy and implementation will change when we take patient costs more seriously
4. Conclusions
33 Postgraduate Course, Kuala Lumpur 14th Nov 2012
34 Postgraduate Course, Kuala Lumpur 14th Nov 2012
Conclusions 1. Patient costs have been ignored in policy
formulation and implementation for MTB/RIF because the process is currently unable to systematically weigh the evidence on patient costs in relation to other evidence
2. Initial evidence suggests that Xpert MTB/RIF can reduce patient costs by approximately 30% (only one published study)
3. Xpert MTB/RIF policy and implementation will shift towards more universal use (less as a follow-on test) when we take patient costs more seriously