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7/30/2019 Bellows-Vouchers for UHC
1/27
Can vouchers help movehealth systems toward
universal healthcoverage?
Ben Bellows
GIC Forum on Health and Social Protection
27 August 2013
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Problem: inequality within country
"Countries across Africa [and Asia] arebecoming richer but whole sections of societyare being left behind.... The current
pattern of trickle-down growth isleaving too many people in poverty, toomany children hungry and too many young
people without jobs."
- Africa Progress Panel, May 2012
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Of 12 MNH interventions in a review ofpublic data across 54 countries, family
planning was the third most inequitable
*Barros, A. J. D., Ronsmans, C., et al. (2012). Equity in maternal, newborn, and child health interventions in Countdown to2015: a retrospective review of survey data from 54 countries. Lancet, 379(9822), 1225-33.
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constraints^3 to financing UHC
in a finite universe Trade-offs in three dimensions
1. Utilization: expand population covered?2. Scope: expand health services offered?3. Financial protection: increase size ofsubsidies per service (or improve
regulation of informal charges)?
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Financing trade-offs
Finance movement toward UHC eitherfrom a greater budget allocation or
greater efficiency
Interventions that generate greatestefficiency will likely operate on supply &
demand
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Voucher functions (management)
Decide to government-run, contract-out, or franchiseConduct provider administrative & clinical training (i.e. CMEs)Design & maintain claims processing & fraud controlMonitor costs, utilization, qualityOffer credit to facilities
FacilityAccredited?Clinical quality?Competition?Reimbursement rates?
ClientPoverty status & need?Voucher is free or fee?Which services
offered?
Program design & functions
Objective reach beneficiaries who in the absence
ofsubsidy would nothave sought equivalent care
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What can vouchers do & where
are the gaps in knowledge?
Recent review catalogued 40 programsthat used vouchers for reproductive
health services (excluded TB andcoupons for health products)
Summarized evidence from multiplestudies of 21 voucher programs
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Number of active reproductive health voucherprograms
0
5
10
15
20
25
30
Small ($1m /yr)
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Program contracts with public & privateproviders
18
6
10
1
5
0
2
4
6
8
10
12
14
16
18
20
private mostly private mixed mostly public public
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Outcometype
Number ofstudies
Direction of effect & gaps in research
Equity ortargeting
8 studies Positive effects: inequalities werereduced.
Missing: nationally standard measures.
Costing 4 studies Positive effects: OOP spending reduced.
Missing: cost-effectiveness,administrative-to-service delivery ratio
Knowledge 5 studies Positive effects: increased knowledge of
important health conditions.
Missing: measures of community normsand partner knowledge.
Evaluation outcomes (1 of 2)
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Outcometype
Number ofstudies
Direction of effect & gaps in research
Utilization 17 studies Positive effects: increased use of ANC,facility deliveries and contraceptives.
Missing: Postnatal care.
Quality 8 studies Positive effects: improved customer care,infrastructure upgrades.
Missing: clinical care scores.
Health 8 studies Positive effects: decreases in STIprevalence, fewer stillbirths, fewerunwanted pregnancies
Missing: maternal mortality, DALYsaverted, CYPs
Evaluation outcomes (2 of 2)
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Prospective studies 2009-2013
Quasi-experimental design for voucherprograms about to launch or expand
Measure change in: utilization (new users, aggregate use) equity (concentration indices, standard
quintiles)
quality of care frameworks (Donabedian,Respectful Care, facility investments) out-of-pocket spending on healthcare
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Data sources:
2 rounds of household surveys 4 voucher & 3 non-voucher
sites
5 km radius from voucher &comparison facilities
Births within two years beforesurvey
2010-11: 962 births among2,933 women 15-49 years
2012: 1,494 births among3,094 women 15-49 years
Study #1, Demand: Study of voucherutilization in Kenya
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Analysis
Cross tabulation with Chi-square tests births by place of delivery over time
Multilevel random-intercept logit analysis ()= +
Three arm design 2006 voucher arm: respondents within 5km of
facilities in program since 2006 2010-11 voucher arm: respondents within 5km of
facilities added to program in 2010 & 2011 Comparison arm: respondents within 5 km of non-
voucher facilities
14
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2006 voucherarm
2011 voucherarm
Comparison arm
Place ofdelivery
Firstsurvey
Secondsurvey
Firstsurvey
Secondsurvey
Firstsurvey
Secondsurvey
Home 32% 21% 59% 47% 45% 42%
Healthfacility
66% 79% 39% 51% 54% 57%
Publicfacility
45% 49% 32% 36% 41% 44%
Privatefacility
21% 30% 7% 15% 13% 13%
p-value p
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Outcome 2006voucher arm
2010-11voucher arm
Comparisonarm
Facilitydelivery
2.04**(1.40-2.98)
1.72**(1.22-2.43)
1.32(0.96-1.81)
Home delivery 0.53**(0.36-0.78)
0.61**(0.43-0.85)
0.75(0.54-1.03)
Adjusted odds ratios
Changes consistent with increased use ofvouchers by respondents 2006 voucher arm: 20% -> 43% 2010-11 voucher arm: 11% -> 45% Comparison arm: 0% in both rounds
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Limitations of analysis
Teasing out direct and indirect effects ofthe program on facility delivery
Identification of respondents withinspecified distances to facilities could affect
over or under-estimation of impact
Most covariates for multivariate analysispertain to time of interview Changes in time dependent co-variates
could affect access to facilities
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Study#2,Supply:Facilityuseof
reimbursements
Crosssectionaldatafrom77accreditedfacilities Retrospectivemeasurementofhowaccredited
facilitiesallocatedrevenuesacrosssixstandardcostcategoriesforphase1(2006-2008)andphase2(2008-2011)
Astructuredquestionnairesenttoaccreditedfacilities
88%responserateachieved Responsesanalyzedtoshowpercentagesof
revenueusedinstandardaccountingcategories
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UseofrevenuebycategoryinPhase2
9% 6%
33%35%
11%
7%
0%
5%10%
15%
20%
25%
30%
35%
40%
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Revenuesourcebeforevouchersprogram
PriortotheGoKVoucherprogram
81%ofthefacili7esreportedthatfollowingthelaunchofthe
voucherprogram,thevoucherprogramhasbeentheirmainrevenue.
RevenueSource
PublicFacilities
PrivateFacilities
FBOs
Government 50% 0 0
Self-generatedrevenue
31% 57% 53%
BankLoans 0 43% 0
Donors 19% 0 37%
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Facilitiesalsoreported
Challengesinaccessingandpurchasingmedicalandnon-medicalsupplies.
Voucherrevenueusedto:
1. CoverthefinancingshorDallforpurchases2. Increasecapacityandprovidemoreservices3. Improveservicequalityandincreasepa7entvolumes/
bedcapacity
Flexibilityinusingrevenuemayhelpovercomeperennialproblemsofcentrallymanaged,publicsectorsupplyandcommodityconstraintsandprivatesectorfinancinggapstoprovidebeMerhealthcareservices.
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In a scaled vouchers strategy thatmoves us toward UHC, which trade-offs would be less painful than others?
Is this a more efficient option p thanalternatives?
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US$millions 70%coverageof2lowestquintiles
2013 2014 2015
Servicedeliverycost 23 29 32
Managementcost(15-20%) 3 6 6
Totalcost:Maternalvoucher 27 35 38
%MOH2011-12budget$813m 3.3% 4.3% 4.7%
Familyplanningservicecost 16 17 20
Managementcost(15-20%) 3 3 3
Totalcost:FPvoucher 19 20 22
%MOH2011-12budget$813m 2.3% 2.5% 2.7%
Think like a demographer. An incrementalallocation could take vouchers to scale
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UHC & vouchers - Equity
Voucher clients are often identified as poor,with a low likelihood of using care
Vouchers educate households to use service,even when the service is free (patientscharter)
Vouchers can control informal payments Vouchers provide managers with data on
eligible households, utilization, and feedbackon populations that need extra mobilization
Vouchers can be targeted to the poor to paytheir insurance premiums
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UHC & vouchers- Financial
protection
Voucher clients receive a subsidy andavoid paying out-of-pocket at point-of-
care Voucher programs often contract
private facilities, which expand accessand improve the likelihood that
households will avoid OOP
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UHC & vouchers- Quality of care
Accreditation standards screen outunderperforming facilities
Reimbursements paid conditional onmeeting minimum service delivery
requirements
Quality-adjusted reimbursements arepossible
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Thank you
RHVouchers.org
@benbellows