Health worker absence, HIV testing and behavioral

change

Markus Goldstein (World Bank)Joshua Graff Zivin (UCSD)

James Habyarimana (Georgetown)Kiki Pop-Eleches (Columbia)

Harsha Thirumurthy (UNC-Chapel Hill)

Information and behavior

• Information assumed to shape choices and behavior

• This has implications for effects of HIV testing Provides information about future health and

longevity

• Setting for this study Antenatal clinic in Kenya where testing is offered

to pregnant women for prevention of MTCT

• Aim: study take-up of HIV testing and impact of learning HIV status on behavioral outcomes

Two important aspects of HIV testing• Take-up of HIV testing

Supply and demand side factors influence this, but role of each not well understood

• Should testing be an important component of policy response to HIV? Discussion has largely focused on its impact

on sexual behavior (Coates et al. 2000; Thornton 2008)

Impacts on other outcomes largely neglected• Take-up of other valuable health services• forward-looking behavior

Obstacles to scale-up of HIV testing• Supply and demand side factors

Demand side factors (see Thornton 2008 & others)

• This paper focuses on supply side Structural constraints (health worker absence)

• Health worker absence in developing world 35% absence rate among public health

providers (Chaudhury et al. 2005) Limited evidence re: impact on health outcomes

• Also a valid instrument for testing decision

Effects of HIV testing (1): health outcomes• Main reason for testing pregnant women:

provide PMTCT medication & advice In 2005, 11% of HIV+ women in Africa got PMTCT

• Inexpensive & effective meds available for PMTCT Nevirapine ($0.50 per dose) In this setting, ARV therapy also given for PMTCT

• Other possible benefits of PMTCT counseling Healthier mothers and children through safer

delivery and increased take-up of neonatal care

Effects of HIV testing (2): socio-economic behavior• Information about future health &

expected longevity should affect number of inter-temporal investment decisions at household level Fertility – important assumption in macro

models of impact of AIDS epidemic (Young 2005)

Human capital formation Asset accumulation

ANC TEST

Individual

Structural

Inputs

HEALTH OUTCOME

S

BREAST FEED

BIRTH LOCATIO

N

PMTCT

TESTING AND COUNSELLING: HEALTH OUTCOMES

ANC ECONOMIC

OUTCOMES

FERTILITY

SCHOOLING

INVESTMENT

TESTING AND COUNSELLING: ECONOMIC OUTCOMES

TEST

Individual

Structural

Inputs

Summary of results

• Absence rate of 10% of PMTCT nurse Large effect on uptake of testing and counseling

• Large effect on delivery of PMTCT medications Safer delivery Lower likelihood of breastfeeding

• Change in investment behavior among negatives Asset accumulation Schooling

• No effects on fertility preferences

Outline

• Panel survey of pregnant women in Kenya• HIV testing decisions and nurse absence

Survey in Nyanza Province

Kenya adult prevalence 6.7% (1.2 million)

Nyanza Province adult prevalence of 20%

Rural health center provides ANC care, and has HIV clinic that provides ARVs (managed by AMPATH program)

Survey conducted in two waves

Panel survey of pregnant women• Wave 1: In-clinic interview before HIV test (July ‘05 –

Feb ‘06) Only first time visitors for current pregnancy interviewed Short questionnaire, included subjective beliefs about HIV

status 650 women from catchment area enrolled

• HIV testing offered after wave 1 interview

• Wave 2: Household interview (May ‘06 – Feb ‘07) comprehensive socio-economic data collected at home:

• demographics, education, health, employment, sexual behavior, assets, etc

• Interviewed ANC client and spouse• Completed panel on 591 women (9% attrition)• Loss to follow up generally due to relocation out of province

Additional data obtained from clinic• PMTCT logbook

HIV status: continuously updated because pregnant women could have tested on subsequent antenatal visits

Nurse presence/absence: based on # of women tested

• AMPATH records Fraction of HIV+ women who enrolled

(imperfect matching)

PMTCT in western Kenya

• Pregnant women typically get tested at first ANC visit 3 visits recommended

• Most common med for HIV+ women: Nevirapine Given to the mother with onset of labor and

drops given to the baby within 72 hours of birth Reduces the risk of transmission by about 50%

• In our study setting, ART also given for PMTCT

• Breastfeeding generally not recommended

HIV testing in sample of 591 women

61.9%15.2%

22.8%

Negative PositiveNot tested

Source: Chulaimbo ANC Intake, 2006

HIV status of women

Health worker absence & HIV testing

• About 77% of women in panel data tested for HIV 25% of those who tested were HIV+

• Controlling for selection into testing 10% absence rate for PMTCT nurse (relatively

small)

• Useful as an instrumental variable to deal with selection Effect of absence on testing is first stage Also control for day of the week and prior beliefs

Table 2a: Nurse absence and testing

Table 2b (1) (2)Age in years 0.001 0.001

(0.002) (0.002)Completed primary school -0.020 -0.017

(0.026) (0.026)Married 0.021 0.027

(0.039) (0.038)# of church attendances (past 4 wks) 0.011 0.012

(0.004)* (0.004)**Number of sexual partners (past 6 mths) 0.007 0.010

(0.035) (0.034)Boils drinking water 0.035 0.038

(0.026) (0.025)HIV subjective beliefs Moderate chance 0.012 0.010

(0.039) (0.040) Small chance -0.029 -0.032

(0.037) (0.038) No chance at all -0.071 -0.078

(0.049) (0.049)Livestock ownership 0.003 0.003

(0.002) (0.002)*House has non-grass roof -0.033 -0.032

(0.028) (0.028)Household resides in clinic catchment -0.001 -0.001

(0.028) (0.028)Day of week = Tuesday -0.013

(0.029)Day of week = Wednesday -0.028

(0.030)Day of week = Thursday -0.085

(0.033)**Day of week = Friday -0.193

(0.046)**Constant 0.865 0.909

(0.081)** (0.080)**Observations 577 574R-squared 0.03 0.08

Nurse present at time of woman's first visit

HIV testing and behavior change• Instrument for testing offers opportunity

to examine whether behavior changes after learning HIV status We estimate separate effects for HIV- and

HIV+ women

• Comparison group? We compare to women who do not get tested

but have similar pre-test beliefs about own status

IV strategy for estimating impact of testing (by test

result)• Ideally:

Do not know status for non-testers

• Therefore, we assume that

Control for pre-test subjective beliefs Our assumption (non-testers’ behavior shaped

by beliefs)

Subjective beliefs about HIV status• First, are pre-test subjective beliefs good

proxy for HIV status? i.e. do pre-test beliefs predict actual test

result?

• Second, do beliefs change after learning HIV status? Perhaps a prerequisite for behavioral change

to occur We examine beliefs about own status and

partner’s status

Variation in pre-test subjective beliefs

12.1%

18.5%

51.8%

17.7%

Great ModerateSmall None at all

Source: Chulaimbo ANC Intake, 2006

Distribution of priors

Pre-test beliefs do have predictive power

10.7%

18.9%

52.6%

17.8% 21.1%

25.6%44.4%

8.9%

9.7%

12.7%

54.5%

23.1%12.1%

18.5%

51.8%

17.7%

Negative Positive

Not tested Total

Great Moderate

Small None at all

Source: Chulaimbo ANC Intake, 2006

Distribution of priors

Pre-test beliefs & actual test result

Tested positive

Tested positive

Tested positive

(1) (2) (3)

Chance of having HIV- great 0.272 0.267 0.226(0.097)** (0.098)** (0.098)*

Chance of having HIV- moderate 0.171 0.168 0.126(0.081)* (0.082)* (0.080)

Chance of having HIV- small 0.077 0.079 0.055(0.059) (0.059) (0.059)

Day of week controls? N Y YOther controls N N YMean of dep. variable 0.197 0.197 0.197Sample Size 453 452 452

Testing and changes in subjective beliefs

HIV testing and behavior change• Evidence of changes in subjective beliefs

about one’s status provide motivation for other behavioral responses

• We first estimate average effect across all women who learn they are HIV+ and HIV- (not interacted with pre-test beliefs)

Why pre-test beliefs may matter (Boozer & Philipson 2000)

Prior belief (subj. belief)

Costs and Benefits of testing

High-risk

Low-risk

Cost of testing

Benefit of testing

Literature has focused largely on the effect of HIV testing on sexual behavior• Policy rationale

Those who test HIV- may have incentives to avoid infection

Those who test HIV+ can be encouraged to adopt safe sex practices

• Effects are theoretically ambiguous In both cases, the opposite response possible

• Existing studies of testing and sexual behavior Coates el al. 2000: VCT, Kenya and Tanzania Thornton 2005: community-based VCT, Malawi

Impacts on other outcomes also important for evaluation of HIV testing• PMTCT take-up, health outcomes• Socio-economic behavior, particularly

forward-looking decisions

Effects on PMTCT and health outcomes

Socio-economic behavior

Heterogeneous response by level of surprise and updating• As in Boozer and Philipson (JHR 2000)• Do women who learn more from the HIV

test have larger changes in behavior? Not much evidence that this matters Actual test result is more salient than how

surprised one is by the test result

Summary of results

• Absence rates are moderate but have large effects on PMTCT outcomes

• Pre-test beliefs do predict HIV status, and these beliefs evolve over time

• Increases in investment behavior for women who test HIV-negative

• No effect on fertility