Health and Health Care Delivery in Developing Countries

Health and Health Care Delivery in Developing CountriesMichael KremerEconomics 1386Fall 2006

The Determinants of MortalityCutler, Deaton, Llenas-Muney (2005)Life expectancy increased 30% last centuryHunter-gatherers: 25 yearsEngland 1700: 37 yearsEngland 1820-1870: 41 yearsUK today: 77 yearsSouth Asia 2004: 63 years (WB WDI, 2006)Vietnam today: higher life expectancy (69 years) than US in 1900 (47 years) but US in 1900 had 10 times higher per capita income than Vietnam today (Kremer 2002)Sub-Saharan Africa 2004: 46 (WB WDI, 2006)Why? Possible explanations:Improved nutritionPublic healthUrbanizationVaccinationMedical treatmentsEarly life factors

The Determinants of Mortality (II)Still - differences between rich and poor countriesProgress in health until HIV/AIDSCorrelation between per capita income and mortalityCorrelation within countries: richer, better educated people live longer. Why?UnclearAccess to medical careResources for non-health careDifferences in health-related behaviorsSocial structures, stress and healthAuthors: Scientific advance and technical progress Less on direct causality of income

Health Care Delivery in Rural RajasthanBanerjee, Deaton and Duflo (2004)Survey of 100 hamlets in Udaipur, collaboration with Seva Mandir (NGO) and Vidhya Bhavan (schools group)Village survey, facility/traditional healer survey, weekly visit to facilities, and household/individual surveyVery poor regionAdult literacy: men 46%, women 11%21% of households have electricity

Health Care Delivery in Rural Rajasthan (II)Poor health status>50% of men and women anemic93% men and 88% women below US BMI cut-off for low nutritionHigh self-reported disease symptomsHealth facility useAdults visit 0.51 times per monthMore for wealthier households0.12 to public facilities, 0.11 to bhopas, 0.28 to private facilities7% of household budget spent on health

Health Care Delivery in Rural Rajasthan (III)Public Health Care FacilitiesOfficial policy: one subcentre with one nurse per 3000 people, open 6 days per week, 6 hours per day, free care3600 people per subcentre. One primary health centre (PHC) with 5.8 medical personnel and 1.5 doctors per 48,000 people45% absenteeism in subcentre, 35% in larger PHCsSubcentres closed 56% of time, unpredictable32% given injection, 6% given drip, 3% given test75% report that visit made them feel better

Health Care Delivery in Rural Rajasthan (IV)Private CarePoor training as doctors 41% have no medical degree, 18% have no medical training, 17% did not graduate from high school68% given injection, 12% given drip, 3% test81% report that visit made them feel betterAlmost comparable costs even though public supposed to be free:Public: Rs 71Private: Rs 84Bhopa: Rs 61Reported satisfaction compared with poor health outcomes suggests need for state involvement

Do Conditional Cash Transfers Improve Child Health?Gertler (2004) on PROGRESARequirements for cash transfer:Clinic visits for infants, young children, pregnant/lactating womenVaccinations for infantsYearly clinic checkups for all family membersMeetings on health, hygiene, nutrition for adultsIllness rate of treatment children 39.5% lower than control groupTreatment children almost 1 cm tallerTreatment children 25.5% less likely to be anemic

Contracting for Health:Evidence from CambodiaIndu BhushanErik BloomDavid ClingingsmithRathavuth Hong

Elizabeth KingMichael KremerBenjamin LoevinsohnBrad Schwartz

Contracting in Cambodia

Many developing countries have mix of salaried government and private fee for service provision. Lots of problems:

Weak incentives of government providers (high absence rates)

Glucose drip problem: misalignment of private providers incentives withpatients interest (asymmetric information)public health (inadequate attention to externalities from infectious disease, drug resistance)Lack of risk sharing

In 1999, Cambodia tried experiment of tendering contracts for management of health services in certain districtsMonitored performance against 8 targeted outcomesIncreased public funding (offset by decreased private expenditure)

District level contracting could potentially:Tie incentives to public health objectivesAllow benchmark competititonPool risks with limited adverse selection (in rural areas)

But could also lead to diversion of effort from important non-targeted activities.

Estimating program impact:Call for bids in 8 districts, randomly chosen from 12 candidatesAcceptable bids in only some districts IV with random assignmentSmall number of districtsClusteringRandomization inferenceAverage effects

Main resultsDelivery of targeted services improvedNon-targeted services were unchangedSome evidence of health improvementManagement of health centers improved.Patients shifted to public providers Effect on total spending (public and private) was neutral to negative.

Previous workKeller and Schwartz (2001)Bhushan, Keller, and Schwartz (2002)Schwartz and Bhushan (2004)

Based on 2001 survey of districts where program actually implemented

OverviewBackground on project and contextModel of health care provisionEmpirical methodsHealth services resultsTargeted outcomesNon-targeted outcomesHealth outcomesChoice of providerHealth facility managementConsumer perception of care qualityPublic and private health spendingConclusion

Cambodian health contextPolitical background1975-1979 Khmer Rouge1979-1993 Vietnamese-backed regime1993 Elections; adoption of market economy1998 End of fightingHealth care systemGovernment health worker salary ~85% GDP/cap; politicization of civil service, governance issuesBoom in private medical practice after 93: government staff moonlightingdrug sellers get about 33% of curative visits in 1997Traditional understanding of health, diseaseSpending high; health service coverage poorProject runs 1999-2003Huge improvements in health over study period. Health center construction.

Contracting Project ICovered 11% of populationResponsible for Minimum Package of ActivitiesTargets on improvement of child and maternal health service coverage. Prevention oriented

Two program variantsContracting in (CI)Management authority, but cant hire/fire, procure outside governmentOperating budget through governmentContracting out (CO)Full control of staffing--hire and fireFull control of procurementOperating budget through ADB/WB loans

BiddingFixed price per capita bids; increased public spending

Technical criteria and price3 districts got no technically acceptable bids

HR practices under contracting IExample: Peareng district, contracting in (CI)Facilities signed annual contracts with NGO, workers 3-mo subcontracts. Private practice banned.Staff motivation viewed as key problemAdditional payment on top of government salaryFixed supplement, attendance, facility performanceStaff incentives based on targeted outcomes, patient satisfaction, quality of care, and no fraud

HR practices under contracting IIAll contractors chose to use some expatriates.Between 0.5 and 3.0 expatriate staff per contracted district. Local staff between 90 and 150 per district.

HR practices under contracting IIIAdditional compensation for workers in all treated districtsTwo officially banned private practice, three allowed itContractor compensation choicesContracting in (CI): Base salary plus performance bonus, no provision for firingContracting out (CO): high fixed salaries, with possibility of firing non-performersCO attracted some staff from outside district, outside government service

Randomization procedureThree provinces with 3, 4, and 5 treatment-eligible districts respectivelyRandomly assign CI, CO, and comparison district within each province. Remaining 3 districts randomized in capitalEach district had equal probability of being CI, CO, comparison

DataBaseline household survey in 1997, follow-up in 2003; facility survey in 200330 randomly selected villages in each of 12 districts; 7-14 households per village randomly chosen in each survey yearHousehold census, recent illnesses and treatment, program outcomesFollow-up included health service quality module

Targeted outcomes at baseline

Baseline Percentage by Random AssignmentComp.Contracting InContracting OutGoalFully immunized child34%28%31%70%Children get Vitamin A42%46%41%70%Antenatal care9%11%13%50%Delivery by trained personnel24%27%32%50%Delivery in a health facility3%6%5%10%Use modern birth control method13%12%18%30%Knowledge of birth control22%27%20%70%Use of public health care facilities4%4%3%Increase

Randomization qualityWill see baselines as go through each outcomeOf baseline levels for 22 outcomes:three significant for each of CI and CO under clustering one significant for each of CI and CO under randomization inference

Holmstrom and Milgrom (1991)Model of health service provisionSuppose targeted and non-targeted outcomes produced by exerting various kinds of costly effort Suppose only targeted outcome T is contractable; linear compensation contract in TIncreasing incentives for T may lead to more or less NT, depending on whether effort types relevant for T and NT are complements or substitutesEither plausible

Econometric IssuesSelection into treatmentCO: 4 districts tendered, 3 awardedCI: 4 districts tendered, 2 awardedPrevious analysis based on actual treatment status, not initial assignmentPerhaps NGOs focused bids on districts where gains would be easiestCluster-level interventionClustering, randomization inferenceFamily-level effects

Empirical method IDistrict-level intervention with individual outcomesRandomly-assigned eligibility an instrument for actual treatment.TOT for outcome k:

Instruments:

Empirical method IIDistrict-level intervention with individual outcomesNeed to account for district level shocksClustering may over-reject null with small number of clustersRandomization inference Create full set placebo random assignments using actual randomization process. (Rosenbaum 2002)Generate placebo treatment effect for each member of the set.Use distribution of placebo treatment effects as test distribution.Low power: imposes no structure on error

Randomization Inference

Empirical method IIIAverage effect size (AES) for family of K outcomesKling, Katz, Leibman, and Sonbanmatsu (2003), OBrien (1984)Joint estimation of TOT for K outcomesAggregate to get common unit of observation vVCM estimates cross-equation correlation of effectsAES is the average treatment effect measured in standard deviation units.We use the standard deviation of the change in outcome for comparison group.

Change in District Averages I

Change in District Averages II

TOT for changes in targeted outcomesNotes: IV regressions including province X year fixed effects. Average effects are differential increases caused by treatment in units of baseline comparison-group standard deviations. Standard errors presented in parentheses are corrected for clustering at the district level. Stars indicate significance under clustering: * at 10%; ** at 5%; *** at 1%. P-values for treatment effects computed by randomization inference.

Table 1

Table 1: Contracted Health Outcomes Definitions and Coverage Goals with Baseline Levels by Random Assignment Status

Program Goal %Baseline (%)

IndicatorDefinitionComparisonContracting InContracting Out

Fully immunized childFull immunization for children 12 - 23 months.70342831

Vitamin AHigh-dose Vitamin A received twice in the past 12 months by children aged 6 - 59 months70424641

Antenatal care5091113

Delivery by trained professionalBirth attendant was qualified nurse, midwife, doctor, or medical assistant for women with a delivery in past year.50242732

Delivery in a health facilityBirth was in a private or public health facility for women with a delivery in the past year.10365

Use modern contraception methodWomen with a live child age 6-23 months old currently using a modern method of contraception.30131218

Knowledge of modern contraceptionWomen who gave birth in the prior 24 months know four or more modern contraception methods and where to obtain them.70222720

Use of public health care facilitiesUse of district public health care facilities (district hospital or primary health care center) for illness in the prior 4 weeks.Increase443

Notes: Baseline statistics are averages by randomization status, not actual treament status.

Table 2

Table 2: Characteristics of Project Districts

Treatment StatusStaffingProcurementBudget SupplementTechnical Assistance & Management TrainingNumber of districts

Contracting OutHired at market rates. MOH staff could take leave of absenceNGO responsibleNoNo2

Contracting InMOH staff on government salary, usually given performance based bonusNGO responsible but through MOH systemYesNo3

ComparisonMOH staff on government salary, often given supplement from user chargesThrough MOH systemYesYes4

Not Successfully ContractedMOH staff on government salary, often given supplement from user chargesThrough MOH systemNoNo3

Table 3

Table 3: TOT Effects for Health Facility Management

Facilities and StaffingSupervisionDelivery

Permanent health center building open24 hour service at health centerUnann. visit: health center open w/ patientsUnann. visit: All sched staff presentNum. supervisor visits in 3mLast visit: discuss MOH progsLast visit: discussed problemsRegisters match HIS reportsDelivery services offered?

CI--Treated0.236**0.826***0.477**0.496**0.0280.1020.0900.3080.246

Clustered S.E.-0.084-0.107-0.216-0.165-0.487-0.085-0.08-0.189-0.164

Randomization inference p-value0.220.030.170.130.960.250.230.170.11

CO--Treated0.1700.4670.7110.787***5.654***0.197-0.1230.1270.403

Clustered S.E.-0.215-0.268-0.44-0.243-(1.34)-0.188-0.183-0.36-0.358


Observations143121143143143112116143143

R-squared0.230.570.520.430.510.120.130.250.02

Comparison Mean0.740.210.450.242.520.770.810.670.52

User FeesOutreachEquipment and Supplies

Health center has user fee systemUser fees clearly postedUser fee income (2003 US$)Health center support from other NGOs?Number outreach last monthOutreach: actual less scheduledHealth center equipment indexHealth center supplies indexAll child vaccs available at health centerAverage Effect Size

CI--Treated0.1640.238**93.925-0.061-2.6900.193**3.530***5.531***-0.155*0.599***

Clustered S.E.-0.146-0.085-82.828-0.306-(2.06)-0.071-0.661-(1.37)-0.081(0.14)

Randomization inference p-value0.590.120.350.870.320.020.100.100.480.04

CO--Treated0.3010.284*92.3450.2453.4140.1392.990*8.863**0.1461.128***

Clustered S.E.-0.228-0.148-81.633-0.795-(3.19)-0.122-(1.37)-(3.10)-0.182(0.38)


Observations14310889143143124143143143H0: CO=CI, p-value

R-squared0.310.170.190.20.160.020.330.380.3

Comparison Mean0.710.7792.830.4514.31-0.0615.0225.020.36

TOT for changes in targeted outcomesNotes: IV regressions including province X year fixed effects. Average effects are differential increases caused by treatment in units of baseline comparison-group standard deviations. Standard errors presented in parentheses are corrected for clustering at the district level. Stars indicate significance under clustering: * at 10%; ** at 5%; *** at 1%. P-values for treatment effects computed by randomization inference.

Table 1






Antenatal care>2 antenatal care visits with blood pressure measurement at least once for women who gave birth in the prior year.5091113







Table 2







Table 3




CI--Treated0.236**0.826***0.477**0.496**0.0280.1020.0900.3080.246

Clustered S.E.-0.084-0.107-0.216-0.165-0.487-0.085-0.08-0.189-0.164


CO--Treated0.1700.4670.7110.787***5.654***0.197-0.1230.1270.403

Clustered S.E.-0.215-0.268-0.44-0.243-(1.34)-0.188-0.183-0.36-0.358


Observations143121143143143112116143143

R-squared0.230.570.520.430.510.120.130.250.02

Comparison Mean0.740.210.450.242.520.770.810.670.52



CI--Treated0.1640.238**93.925-0.061-2.6900.193**3.530***5.531***-0.155*0.599***

Clustered S.E.-0.146-0.085-82.828-0.306-(2.06)-0.071-0.661-(1.37)-0.081(0.14)


CO--Treated0.3010.284*92.3450.2453.4140.1392.990*8.863**0.1461.128***

Clustered S.E.-0.228-0.148-81.633-0.795-(3.19)-0.122-(1.37)-(3.10)-0.182(0.38)



R-squared0.310.170.190.20.160.020.330.380.3

Comparison Mean0.710.7792.830.4514.31-0.0615.0225.020.36

Robustness check: wealth controlsNotes: All IV regressions in Panel B include province X year fixed effects and wealth controls. Standard errors presented in parentheses are corrected for clustering at the district level. Stars indicate significance under clustering: * at 10%; ** at 5%; *** at 1%. P-values for treatment effects computed by randomization inference.

Table 1













Table 2







Table 3




CI--Treated0.236**0.826***0.477**0.496**0.0280.1020.0900.3080.246

Clustered S.E.-0.084-0.107-0.216-0.165-0.487-0.085-0.08-0.189-0.164


CO--Treated0.1700.4670.7110.787***5.654***0.197-0.1230.1270.403

Clustered S.E.-0.215-0.268-0.44-0.243-(1.34)-0.188-0.183-0.36-0.358


Observations143121143143143112116143143

R-squared0.230.570.520.430.510.120.130.250.02

Comparison Mean0.740.210.450.242.520.770.810.670.52



CI--Treated0.1640.238**93.925-0.061-2.6900.193**3.530***5.531***-0.155*0.599***

Clustered S.E.-0.146-0.085-82.828-0.306-(2.06)-0.071-0.661-(1.37)-0.081(0.14)


CO--Treated0.3010.284*92.3450.2453.4140.1392.990*8.863**0.1461.128***

Clustered S.E.-0.228-0.148-81.633-0.795-(3.19)-0.122-(1.37)-(3.10)-0.182(0.38)



R-squared0.310.170.190.20.160.020.330.380.3

Comparison Mean0.710.7792.830.4514.31-0.0615.0225.020.36

TOT for non-contracted outcomesNotes: All regressions include province X year fixed effects. Standard errors presented in parentheses are corrected for clustering at the district level. Stars indicate significance under clustering: * at 10%; ** at 5%; *** at 1%. P-values for treatment effects computed by randomization inference. Treatment effects are in bold.

Table 1













Table 2







Table 3




CI--Treated0.236**0.826***0.477**0.496**0.0280.1020.0900.3080.246

Clustered S.E.-0.084-0.107-0.216-0.165-0.487-0.085-0.08-0.189-0.164


CO--Treated0.1700.4670.7110.787***5.654***0.197-0.1230.1270.403

Clustered S.E.-0.215-0.268-0.44-0.243-(1.34)-0.188-0.183-0.36-0.358


Observations143121143143143112116143143

R-squared0.230.570.520.430.510.120.130.250.02

Comparison Mean0.740.210.450.242.520.770.810.670.52



CI--Treated0.1640.238**93.925-0.061-2.6900.193**3.530***5.531***-0.155*0.599***

Clustered S.E.-0.146-0.085-82.828-0.306-(2.06)-0.071-0.661-(1.37)-0.081(0.14)


CO--Treated0.3010.284*92.3450.2453.4140.1392.990*8.863**0.1461.128***

Clustered S.E.-0.228-0.148-81.633-0.795-(3.19)-0.122-(1.37)-(3.10)-0.182(0.38)



R-squared0.310.170.190.20.160.020.330.380.3

Comparison Mean0.710.7792.830.4514.31-0.0615.0225.020.36

TOT for final health outcomesNotes: All regressions include province X year fixed effects. Standard errors presented in parentheses are corrected for clustering at the district level. Stars indicate significance under clustering: * at 10%; ** at 5%; *** at 1%. P-values for treatment effects computed by randomization inference. Treatment effects are in bold.

Table 1













Table 2







Table 3




CI--Treated0.236**0.826***0.477**0.496**0.0280.1020.0900.3080.246

Clustered S.E.-0.084-0.107-0.216-0.165-0.487-0.085-0.08-0.189-0.164


CO--Treated0.1700.4670.7110.787***5.654***0.197-0.1230.1270.403

Clustered S.E.-0.215-0.268-0.44-0.243-(1.34)-0.188-0.183-0.36-0.358


Observations143121143143143112116143143

R-squared0.230.570.520.430.510.120.130.250.02

Comparison Mean0.740.210.450.242.520.770.810.670.52



CI--Treated0.1640.238**93.925-0.061-2.6900.193**3.530***5.531***-0.155*0.599***

Clustered S.E.-0.146-0.085-82.828-0.306-(2.06)-0.071-0.661-(1.37)-0.081(0.14)


CO--Treated0.3010.284*92.3450.2453.4140.1392.990*8.863**0.1461.128***

Clustered S.E.-0.228-0.148-81.633-0.795-(3.19)-0.122-(1.37)-(3.10)-0.182(0.38)



R-squared0.310.170.190.20.160.020.330.380.3

Comparison Mean0.710.7792.830.4514.31-0.0615.0225.020.36

TOT for changes in care-seeking outcomesNotes: IV regressions with provinceXyear effects. Standard errors presented in parentheses are corrected for clustering at the district level. Stars indicate significance under clustering: * at 10%; ** at 5%; *** at 1%. P-values for treatment effects computed by randomization inference. Average effect codes drug seller and traditional healer visits as negative and qualified private and public provider visits as positive.

Table 1













Table 2







Table 3




CI--Treated0.236**0.826***0.477**0.496**0.0280.1020.0900.3080.246

Clustered S.E.-0.084-0.107-0.216-0.165-0.487-0.085-0.08-0.189-0.164


CO--Treated0.1700.4670.7110.787***5.654***0.197-0.1230.1270.403

Clustered S.E.-0.215-0.268-0.44-0.243-(1.34)-0.188-0.183-0.36-0.358


Observations143121143143143112116143143

R-squared0.230.570.520.430.510.120.130.250.02

Comparison Mean0.740.210.450.242.520.770.810.670.52



CI--Treated0.1640.238**93.925-0.061-2.6900.193**3.530***5.531***-0.155*0.599***

Clustered S.E.-0.146-0.085-82.828-0.306-(2.06)-0.071-0.661-(1.37)-0.081(0.14)


CO--Treated0.3010.284*92.3450.2453.4140.1392.990*8.863**0.1461.128***

Clustered S.E.-0.228-0.148-81.633-0.795-(3.19)-0.122-(1.37)-(3.10)-0.182(0.38)



R-squared0.310.170.190.20.160.020.330.380.3

Comparison Mean0.710.7792.830.4514.31-0.0615.0225.020.36

TOT for health center management INotes: All columns are IV regressions in levels with province fixed effects. Standard errors presented in parentheses are corrected for clustering at the district level. Stars indicate significance under clustering: * at 10%; ** at 5%; *** at 1%. P-values for treatment effects computed by randomization inference.

Table 1













Table 2







Table 3




CI--Treated0.236**0.826***0.477**0.496**0.0280.1020.0900.3080.246

Clustered S.E.-0.084-0.107-0.216-0.165-0.487-0.085-0.08-0.189-0.164


CO--Treated0.1700.4670.7110.787***5.654***0.197-0.1230.1270.403

Clustered S.E.-0.215-0.268-0.44-0.243-(1.34)-0.188-0.183-0.36-0.358


Observations143121143143143112116143143

R-squared0.230.570.520.430.510.120.130.250.02

Comparison Mean0.740.210.450.242.520.770.810.670.52



CI--Treated0.1640.238**93.925-0.061-2.6900.193**3.530***5.531***-0.155*0.599***

Clustered S.E.-0.146-0.085-82.828-0.306-(2.06)-0.071-0.661-(1.37)-0.081(0.14)


CO--Treated0.3010.284*92.3450.2453.4140.1392.990*8.863**0.1461.128***

Clustered S.E.-0.228-0.148-81.633-0.795-(3.19)-0.122-(1.37)-(3.10)-0.182(0.38)



R-squared0.310.170.190.20.160.020.330.380.3

Comparison Mean0.710.7792.830.4514.31-0.0615.0225.020.36

TOT for health center management IINotes: All columns are IV regressions in levels with province fixed effects. Standard errors presented in parentheses are corrected for clustering at the district level. Stars indicate significance under clustering: * at 10%; ** at 5%; *** at 1%. P-values for treatment effects computed by randomization inference.

Table 1













Table 2







Table 3




CI--Treated0.236**0.826***0.477**0.496**0.0280.1020.0900.3080.246

Clustered S.E.-0.084-0.107-0.216-0.165-0.487-0.085-0.08-0.189-0.164


CO--Treated0.1700.4670.7110.787***5.654***0.197-0.1230.1270.403

Clustered S.E.-0.215-0.268-0.44-0.243-(1.34)-0.188-0.183-0.36-0.358


Observations143121143143143112116143143

R-squared0.230.570.520.430.510.120.130.250.02

Comparison Mean0.740.210.450.242.520.770.810.670.52



CI--Treated0.1640.238**93.925-0.061-2.6900.193**3.530***5.531***-0.155*0.599***

Clustered S.E.-0.146-0.085-82.828-0.306-(2.06)-0.071-0.661-(1.37)-0.081(0.14)


CO--Treated0.3010.284*92.3450.2453.4140.1392.990*8.863**0.1461.128***

Clustered S.E.-0.228-0.148-81.633-0.795-(3.19)-0.122-(1.37)-(3.10)-0.182(0.38)



R-squared0.310.170.190.20.160.020.330.380.3

Comparison Mean0.710.7792.830.4514.31-0.0615.0225.020.36

AES for 11 health center management outcomes Health center open with patientsAll scheduled staff presentChild delivery service availableUser fees clearly postedNumber of supervisor visits

Number of outreach trips Index of equipment installed and functionalIndex of drugs and other supplies availableAll childhood immunizations available

Notes: Standard errors presented in parentheses are corrected for clustering at the district level. Stars indicate significance under clustering: * at 10%; ** at 5%; *** at 1%. P-values for treatment effects computed by randomization inference.

Table 1













Table 2







Table 3




CI--Treated0.236**0.826***0.477**0.496**0.0280.1020.0900.3080.246

Clustered S.E.-0.084-0.107-0.216-0.165-0.487-0.085-0.08-0.189-0.164


CO--Treated0.1700.4670.7110.787***5.654***0.197-0.1230.1270.403

Clustered S.E.-0.215-0.268-0.44-0.243-(1.34)-0.188-0.183-0.36-0.358


Observations143121143143143112116143143

R-squared0.230.570.520.430.510.120.130.250.02

Comparison Mean0.740.210.450.242.520.770.810.670.52


Health center has user fee systemUser fees clearly postedUser fee income (2003 US$)Health center support from other NGOs?Number outreach last monthOutreach: actual less scheduledHealth center equipment indexHealth center supplies indexAll child vaccs available at health centerAverage Effect SizeAverage Effect Size

CI--Treated0.1640.238**93.925-0.061-2.6900.193**3.530***5.531***-0.155*0.599***Contracting-In0.599***

Clustered S.E.-0.146-0.085-82.828-0.306-(2.06)-0.071-0.661-(1.37)-0.081(0.14)Clustered S.E.(0.14)

Randomization inference p-value0.590.120.350.870.320.020.100.100.480.04Randomization inference p-value0.04

CO--Treated0.3010.284*92.3450.2453.4140.1392.990*8.863**0.1461.128***Contracting-Out1.128***

Clustered S.E.-0.228-0.148-81.633-0.795-(3.19)-0.122-(1.37)-(3.10)-0.182(0.38)Clustered S.E.(0.38)


Observations14310889143143124143143143H0: CO=CI, p-valueH0: CO=CI, p-value

TOT for consumer perception of qualityNotes: All regressions include province X year fixed effects. Standard errors presented in parentheses are corrected for clustering at the district level. Stars indicate significance under clustering: * at 10%; ** at 5%; *** at 1%. P-values for treatment effects computed by randomization inference. Treatment effects are in bold.

Table 1













Table 2







Table 3




CI--Treated0.236**0.826***0.477**0.496**0.0280.1020.0900.3080.246

Clustered S.E.-0.084-0.107-0.216-0.165-0.487-0.085-0.08-0.189-0.164


CO--Treated0.1700.4670.7110.787***5.654***0.197-0.1230.1270.403

Clustered S.E.-0.215-0.268-0.44-0.243-(1.34)-0.188-0.183-0.36-0.358


Observations143121143143143112116143143

R-squared0.230.570.520.430.510.120.130.250.02

Comparison Mean0.740.210.450.242.520.770.810.670.52



CI--Treated0.1640.238**93.925-0.061-2.6900.193**3.530***5.531***-0.155*0.599***

Clustered S.E.-0.146-0.085-82.828-0.306-(2.06)-0.071-0.661-(1.37)-0.081(0.14)


CO--Treated0.3010.284*92.3450.2453.4140.1392.990*8.863**0.1461.128***

Clustered S.E.-0.228-0.148-81.633-0.795-(3.19)-0.122-(1.37)-(3.10)-0.182(0.38)



R-squared0.310.170.190.20.160.020.330.380.3

Comparison Mean0.710.7792.830.4514.31-0.0615.0225.020.36

TOT for health care spending INotes: All outcomes in 2003 USD per capita. All regressions include province X year fixed effects. Standard errors presented in parentheses are corrected for clustering at the district level. Stars indicate significance under clustering: * at 10%; ** at 5%; *** at 1%. P-values for treatment effects computed by randomization inference. Treatment effects are in bold.

Table 1













Table 2







Table 3




CI--Treated0.236**0.826***0.477**0.496**0.0280.1020.0900.3080.246

Clustered S.E.-0.084-0.107-0.216-0.165-0.487-0.085-0.08-0.189-0.164


CO--Treated0.1700.4670.7110.787***5.654***0.197-0.1230.1270.403

Clustered S.E.-0.215-0.268-0.44-0.243-(1.34)-0.188-0.183-0.36-0.358


Observations143121143143143112116143143

R-squared0.230.570.520.430.510.120.130.250.02

Comparison Mean0.740.210.450.242.520.770.810.670.52










TOT for health care spending IINotes: All outcomes in 2003 USD per capita. All regressions include province fixed effects. Standard errors presented in parentheses are corrected for clustering at the district level. Stars indicate significance under clustering: * at 10%; ** at 5%; *** at 1%. P-values for treatment effects computed by randomization inference. Treatment effects are in bold.

Table 1













Table 2







Table 3




CI--Treated0.236**0.826***0.477**0.496**0.0280.1020.0900.3080.246

Clustered S.E.-0.084-0.107-0.216-0.165-0.487-0.085-0.08-0.189-0.164


CO--Treated0.1700.4670.7110.787***5.654***0.197-0.1230.1270.403

Clustered S.E.-0.215-0.268-0.44-0.243-(1.34)-0.188-0.183-0.36-0.358


Observations143121143143143112116143143

R-squared0.230.570.520.430.510.120.130.250.02

Comparison Mean0.740.210.450.242.520.770.810.670.52










Effects of spending on health outcomes I

Sheet1

Table X: OLS Estimates of Effect of Total Per-Capita Public Health Spendingon Health Care Outcomes

Panel A: Targeted Outcomes

Full ImmunizationVitamin AAnenatal CareTrained DeliveryDelivery in FacilityUse ContraceptionKnow ContraceptionUse Public Facilities

Per-Capita Spending0.096***0.0450.0290.0700.055-0.0120.0270.011

S.E.(0.018)(0.055)(0.044)(0.070)(0.045)(0.026)(0.026)(0.023)

Contract-In-0.096**-0.0160.171*-0.0710.0020.043-0.0390.104*

S.E.(0.037)(0.085)(0.081)(0.082)(0.060)(0.035)(0.053)(0.048)

Contract-Out-0.270***0.0780.057-0.235-0.1130.064-0.1120.157*

S.E.(0.057)(0.186)(0.158)(0.226)(0.142)(0.082)(0.087)(0.083)

obs25445390252525232510335048835183

R-squared0.030.200.070.040.040.010.010.07

Fraction of Contracting In TOT effect explained1.630.370.200.750.15-0.15-1.190.06

Fraction of Contracting Out TOT effect explained-1.050.820.260.230.280.430.500.05

Robust standard errors in parentheses

* significant at 10%; ** significant at 5%; *** significant at 1%

Panel B: Non-Targeted Outcomes

Alive after 1 yearDiarrheaDiarrhea Treatment (0/1)Add'l Antenatal ChecksVillage Visit

Effects of spending on health outcomes II

Sheet1

Table X: OLS Estimates of Effect of Total Per-Capita Public Health Spendingon Health Care Outcomes

Panel A: Targeted Outcomes

Full ImmunizationVitamin AAnenatal CareTrained DeliveryDelivery in FacilityUse ContraceptionKnow ContraceptionUse Public Facilities

Per-Capita Spending0.096***0.0450.0290.0700.055-0.0120.0270.011

S.E.(0.018)(0.055)(0.044)(0.070)(0.045)(0.026)(0.026)(0.023)

Contract-In-0.096**-0.0160.171*-0.0710.0020.043-0.0390.104*

S.E.(0.037)(0.085)(0.081)(0.082)(0.060)(0.035)(0.053)(0.048)

Contract-Out-0.270***0.0780.057-0.235-0.1130.064-0.1120.157*

S.E.(0.057)(0.186)(0.158)(0.226)(0.142)(0.082)(0.087)(0.083)

obs25445390252525232510335048835183

R-squared0.030.200.070.040.040.010.010.07

Fraction of Contracting In TOT effect explained1.630.370.200.750.15-0.15-1.190.06

Fraction of Contracting Out TOT effect explained-1.050.820.260.230.280.430.500.05

* significant at 10%; ** significant at 5%; *** significant at 1%

Panel B: Non-Targeted Outcomes

Alive after 1 yearDiarrheaDiarrhea Treatment (0/1)Add'l Antenatal ChecksVillage Visit

Conclusion IIncrease in targeted outcomes of about one-half standard deviation.Improved management, particularly in contracting out.No evidence non-targeted outcomes decreased.Total spending neutral or decreased.

Conclusion IIInstitutional change plus increased public spendingOnly one of set of possible interventionsInteresting for policy because feasibleExternal validity difficult to assessAdditional trials in post-conflict environments and others with serious health care delivery problems.

Intradistrict correlation and wealth controls in 1997

Sheet1

Residual from regression of outcome on wealth controls in 1997

Raw outcome in 1997

Full Immunization0.0750.060

Vitamin A0.0430.034

Antenatal Care0.0640.053

Trained Delivery0.0810.059

Del. in Facility0.0120.007

Use Birth Spacing0.0160.015

Know Birth Spacing0.0720.063

Use Public Facilities0.0080.008

Notes: Intraclass correlation coefficients computed from one-way ANOVAs by district.

Sheet2

Sheet3

ITT effects on quantiles of individual spendingNotes: Mean and quantile regressions with provinceXyear effects. Standard errors presented in parentheses are corrected for clustering at the district level using bootstrap. Stars indicate significance under clustering: * at 10%; ** at 5%; *** at 1%. P-values for treatment effects computed by randomization inference. Treatment effects are in bold.

Table 1













Table 2


Treatment StatusStaffingProcureme

Documents

Health and Health Care Delivery in Developing Countries