Health care utilization patterns and economic consequences of TB

Dr. K. ZamanICDDR,B

National TB Conference 2007, NATAB

Background

8.8 million new cases of TB, 1.6 million deaths globally in a year

TB causes 1.6 million DALYs loss annually among low- and middle-income countries

Poor patients seek care – frequently from non- licensed providers

Delay in diagnosis & start treatment Put economic burden on families

Distribution of tuberculosis in the worldDistribution of tuberculosis in the world

Dye C. Lancet 2006;367:938-40Dye C. Lancet 2006;367:938-40

Ranks 5Ranks 5thth globally globally

Incidence allIncidence all cases 227/100Kcases 227/100K /Yr/Yr

Incidence Incidence SS+ve cases SS+ve cases 102/100K/Yr 102/100K/Yr

300,000 new 300,000 new cases in a year cases in a year

70,000 70,000 deaths/year deaths/year

Objectives

To describe health care utilization patterns of TB suspects and TB cases

To assess the economic consequences of TB at family level

Population prevalence of smear positive TB cases by age and gender- Matlab

139***

28

293***

39

190***

31

0

50

100

150

200

250

300

350pe

r 10

0,00

0

15-44 >45 AllYear

MaleFemale

*** p<0.0001 Zaman et al, 2006

 

From cough to cure pathway

Care seekingNon TB / Irregular treatment

TB suspectsCough > 21

Days

TB specific treatment

Diagnosis as TB

ExpenditureImpact Coping with TB

Beginning of TB symptoms

>

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Legend Comparison area

Embankment

> ICDDR,B Hospital in Matlab

Intervention area

Main river

Village boundaries

KM

43210

The Map Showing Villages of Matlab Study Area

EGIS unit, ICDDR,B

TB Surveillance in Rural Matlab

Routine surveillance inRoutine surveillance in the intervention areathe intervention area

Referral of all suspectedReferral of all suspected cases to Matlab THCcases to Matlab THC

Specific data collection Specific data collection from all areasfrom all areas

General Characteristics of TB cases in rural Matlab

Items Intervention

N = 81(%)

Non-Intervention

N = 82(%)

All

N =163(%)

Family Size 5.27 5.39 5.33

No Schooling 38 ( 46.9) 37 (45.1) 75(47.3)

Monthly income (Taka) 4019 3939 3979

Care sought: First consultation by TB Cases

Type of provider Intervention N = 81(%)

Non-interventionN=82 (%)

All N =163 (%)

Non-graduate allopath 17 (20.9) 24 (29.2) 41 (25.1)Pharmacy 21 (25.9) 20(24.3) 41 (25.1)Homeopath 0 1 (1.2) 1 (0.6)NGO 4 (4.9) 0 4 (2.4)THC 6 (7.4) 3 (3.6) 9 (5.5)ICDDR,B 19 (23.4) 0 19 (11.6)Graduate Allopath (GP) 11 (13.6) 27 (32.9) 38 (23.3)

Others 3 (3.7) 7 (8.5) 10 (6.1)

Knowledge about TB and TB services

Items Intervention N = 81(%)

Non-interventionN=82 (%)

All N =163 (%)

Know signs / symptoms of TB

65 (80.2) 64 (78.0) 129 (79.1)

Know free TB treatment available

73 (90.1) 71 (86.5) 144 (88.3)

TB case in the Family 33 (40.7) 24 (29.2) 57(34.9)

Survey of TB suspects in Urban areas

Adults screened for cough > 3 weeks

60,382

TB suspects

1,138 (1.9%)

TB suspects interviewed

1,046 (91.9%)

Sought care Sought care 648 (62%)648 (62%)

DOTS (Public DOTS (Public + NGO)+ NGO)

106 (16.4%)106 (16.4%)

NON - DOTS NON - DOTS (Private (Private Sector)Sector)

542 (83.6%)542 (83.6%)

Care seeking of suspected TB cases

Measures taken by different providers

†Measures taken at DOTS centre not shown

Chronic coughers 1046 Care sought 648 (62%)

Measures taken by provider

Percentage of providerGraduate

PP(n=111)

Non-graduate PP

(n=283)

Pharmacy & others

(n =148)Investigations 2.7 0.4 2.0

Advises 2.7 0.7 0.7Prescribed drugs 93.7 97.9 95.3

Refer to DOTS 0.0 0.4 0.0

Refer to another providers

0.9 0.4 0.0

Others 0.0 0.4 2.0

General Characteristics of TB cases in urban areas

Subjects (N = 40)

Average Comments

Family Size 4.8 -

Monthly income in past month Patient (Taka)

2577 23% had no income

Monthly income in past month Household (Taka)

4101 5% had no income

No. of visit to providers before specific treatment

2.6 Range 1- 5 visits

Expenditure before TB treatment

Expenditure Number of patients

Range (Taka)

Mean (Taka)

Provider fee 20 5 – 2760 214

Diagnostic cost 8 20 – 4192 823

Medicine cost 16 30 – 3500 767Transport cost 23 10 – 1250 128

Other cost 18 10 – 1400 220

Total expenditure 37 10 - 9270 811

Impact on work

Items N = 40 Comments

Preceding month of Diagnosis

67% Work loss 16 days (2-30days)

Previous 3 months of diagnosis

50% Stop/Reduce/change jobs

Previous 3 months of diagnosis

20% • Interfered work of other members• Other members started new job• Members stopped schooling (10%)

Impact on Household

Items N = 40 Comments

Changes regular expenditures

90 % Adjusted in the families

Health expenditure 56 % increased

Food expenditure due to illness

53 % increased

Transport related expenditure

36 % increased

Coping Strategies

Items N = 40 Comments

Adopted coping strategies 48 % of Households

Taking loan 30 %

Accepting Donations 20 % Relatives and friends

Savings 17.5 % Stop or use previous

Sale of properties 10 %

Conclusions

Many TB suspects sought care from non-DOTS Most of them knew the signs and symptoms of TB Significant expenditure before diagnosis of TB Many adopted coping strategies Poses high economic burden to the families

Government of Bangladesh (NTP)

Matlab THC

BRAC

WHO

All partners of NTP

ICDDR,B

Collaboration