Xpert MTB/RIF: a patient cost perspective - Patient cost...Xpert MTB/RIF: a patient cost perspective...

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


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


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


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


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


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


Distribution of costs Before & After Diagnosis (8 studies)


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


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


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


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


Opera:onal Modelling -‐ capturing complex pathways -‐ Opera(onal model of TB diagnos(c centre in Tanzania


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


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


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?


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


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 ✔



ignored in the policy formulation and implementation for Xpert MTB/RIF:



3.  How Xpert MTB/RIF policy and implementation will

change when we take patient costs more seriously 4.  Conclusions


Effect on general TB patients


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


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.


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



ignored in the policy formulation and implementation for Xpert MTB/RIF:



3.  How Xpert MTB/RIF policy and implementation will change when we take patient costs more seriously

4.  Conclusions


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

Xpert MTB/RIF: a patient cost perspective - Patient cost...Xpert MTB/RIF: a patient cost perspective...

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