Utilization of TB control services in Kenya

Analysis of wealth inequalities

Christy Hanson, PhD, MPH

World Health Organization

Stop TB Department

Trends in Tuberculosis: Kenya

Infectious (smear+) cases of TB

010,00020,00030,00040,00050,00060,00070,00080,000

1995 1996 1997 1998 1999 2000

Estimated sm+ cases(incidence)

Sm+ cases detected

Source: WHO reports: 1997, 1998, 1999, 2000,2001

• 62.3% of population lives on <$2/day (1994)

• 50+% of TB patients are HIV+

TB and HIV in Kenya

0

100

200

300

400

500

600

700

1980 1990 2000 20100.000.020.040.060.080.100.120.140.16

HIV

pre

vale

nce

TB

inci

den

ce

Source: B. Williams, WHO Geneva

Where the system provides DOTS

Health facilities by type,2001

Health centre12%

Hospital10%

Dispensary61%

Nursing home4%

Health clinic13%

0

20

40

60

80

100

Hospital Health centre Dispensary

Percent of all public facilities that participate in DOTS implementation

2001

88% of Kenyans with illness sought care from formal sector

Study objectives

Current performance of health sector in reaching poor

Treatment seeking patterns of poor vs. non-poor

Identify provider and patient characteristics associated with utilization of DOTS providers

Survey implementation

Sampling Frame 1 district per province 20% of all facilities/pharmacies: public,

private, NGO N=3500

4 points in service delivery Outpatient (TB symptomatic)

n=1750 Diagnostic (TB suspect)

n=675 Treatment: initial phase (TB patient)

n=540 Treatment: completion phase (cured TB case)

Survey Tools

Provider: costs, services, patient base Individual

Demographic information Health information

• Symptoms, choice set (providers that patients perceive are accessible)

TB knowledge Treatment-seeking behavior

• Movement between formal, informal, private, public• Utilization and expenditures

Valuation• Inventory what is important in decision-making• Preferences

Analytical techniques Asset-index used for measuring

wealth Transition matrices Logistic regression: individual

factors Conditional logit (McFadden’s):

provider characteristics Define individual choice set

Profile of TB patients treated in public and private sectors

0

10

20

30

40

50

60

% o

f al

l pat

ient

s

Q1:

poor

est

Q2

Q3

Q4

Q5:

wea

lthi

est

Wealth Quintiles

Public sector: initiating tx

Private sector: initiating tx

Public sector: completing tx

Private sector: completing tx

3% of patients completing treatment are among the poorest quintile

Expected vs. actual utilization distribution

01020304050607080

% of patients surveyed

Q1-Q3: Poorest Q4-Q5: Non-poor

Wealth quintiles

Expected

Symptomatics

Suspects

New cases

Cases completing tx

Change in wealth profile along continuum of diagnosis & treatment

0

1

2

3

4

5

mea

n w

ealt

h s

core

Stage in treatment process

Nairobi

TB symptomatics

Diagostics; TB suspects

New PTB (1st month of tx)

0

0.5

1

1.5

2

2.5

mea

n w

ealt

h s

core

S tage in treatment process

Nyeri

Diagnostics

New PTB (1st month)

Completing treatment

Movement through the health system: the case of the poor

40% start at decentralized dispensaries Almost equal % in public / private

Those who start at hospital level, 12% transition “backwards” Less efficient transitioning

• More visits (half had 5-10 visits, still not referred for dx)

• More time ill

• Higher expenditures

Most interact with a “DOTS” facility within 1st three visits, still don’t get referred for diagnosis

• Individual & provider factors behind transitioning

Where patients go vs. Where the system provides DOTS

0

5

10

15

20

25

dispensary healthcentre

hospital pharmacy

First interaction with health system

public private

0

20

40

60

80

100

Hospital Health centre Dispensary

Percent of all public facilities that implement DOTS

2001

Health facilities by type,2001

Dispensary61%

Health centre12%

Hospital10%

Nursing home4%

Health clinic13%

Factors associated with selection of public sector DOTS provider as 1st choice

Poor

Individual characteristics

Ability to pay in kind, negotiate price (Q1 only)

Perception of DOTS facility as best quality

Knowledge of fees (negative association)

Non-poor

Individual characteristics

Know TB treatment is free in public sector (35% knew)

Confidentiality

Availability of medicine

Waiting time

Perception of public DOTS facility as best quality

Knowledge of fees (negative association)

Conclusions & Next steps TB patients actively seeking care

System passive in referral, detection

Poor disproportionately represented at all stages Research: prevalence distribution by wealth Social science research: why?

Private sector: competitive, well used Define comparative advantage of NLTP

Public system subsidizing non-poor Not effectively supporting poor

District variance: lessons to be learned from successful districts