Measuring to Manage
Progress toward
Universal Health
Coverage
Ben Bellows
On behalf of the Social Franchise Metrics Working Group
NHIS 10th Anniversary International Conference on UHC
Accra
UHC is multidimensional &
aspirational
Access: Expand
coverage
to
wider
How universal can
vouchers
really be?
population
Despite growing evidence for vouchers’ impressive impact in terms of equity,
Scope:
Improve
financial protection and quality of care, they
remain for now
aquantity
specific tool to of
enable
quality
&
underserved groups to access priority
services. However
the WHO’s ‘cube’
frames health
services
offered
progress towards UHC in terms of the share
of people, servicesprotection:
and costs covered, with
Financial
a focus on growing these three dimensions
Improve
size
as
far
as
possible of
.
Given
this
understanding of UHC, how important can
subsidies
or to UHC
reduce
vouchers’ contribution
really be?
informal
charges
The first point to remember is that vouchers
xi
do not have to be targeted. For example, all
families were eligible for the wildly successful
family planning voucher programmes in
Korea and Taiwan in the 60s-90s. Even
among targeted voucher programmes, some
Figure 1: WHO's Universal Health Coverage 'Cube'
Pitfall 1: Social Health Insurance can
emphasise curative care at the expense of
public health and preventative care
Access is far from universal in 54 LMIC
•
Of 12 MNH interventions in a review of
public 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 to 2015: a retrospective review of survey data from 54 countries”. Lancet,
379(9822), 1225-33.
Limited financial protection is
common in 51 LMIC*
•
•
•
•
13–32% of household expenditures over 4
weeks went to healthcare
25% poor households incurred potentially
catastrophic healthcare expenses
>40% of households used savings,
borrowed money, or sold assets to pay for
care
41-56% of households spent 100% of
health care expenditures on medicines
*Wagner, Graves, Reiss, LeCates, Zhang, Ross-Degnan. 2011. “Access to care and medicines,
burden of health care expenditures, and risk protection: Results from the World Health Survey”
Health Policy. 100(2-3):151-158
Selected constructs and metrics
for UHC measurement
Quality of care:
•
Donabedian framework (structure, process, outcomes)
•
Investment in facility infrastructure
Financial protection:
•
Out-of-pocket spending on health paid for by the patient at
the point of service
•
Proportion of household consumption that is spent on
healthcare
Equitable access:
•
Geographic proximity
•
Above or below a poverty line
•
Member of a wealth quintile
Preferred characteristics in a UHC equity
measure
•
Program Managers
• Quick, inexpensive to
collect
• Easy to interpret by
managers and field staff
•
Agency Headquarters
• Standardized &
comparable nationally
• Easy to explain to policy
makers
•
Other Stakeholders
• Comparable internationally
•
Clients
• Transparent,
trustworthy, quick
application process
• Time-delimited
membership
• Recognition of
solidarity
• Recourse for appeal
Pilot study: Find a good routine,
monitoring equity indicator
Progress out of
Poverty Index
(PPI)
•
Wealth Index
(WI)
Multidimensional
Poverty Index
(MPI)
MPI dismissed: not feasible to collect
• PPI and Wealth Index piloted in 5 countries in
2012 as part of franchise client exit interviews
• Results compared against selection criteria
PPI tools
DHS questions
Results & indicator attributes
Wealth Index
PPI
Relative measure
Uses DHS data to compare client
sample to national wealth quintiles
Low-cost because DHS data is publicly
available
Absolute measure
Asset list gives likelihood that a client is
under $1.25/day poverty threshold
Expensive: unique asset weights
developed for each country
Quintile
India
Madag
Benin
DRC
Mali
n=797
n=853
n=535
n=242
n=293
1 (Poorest)
27.9
2.1
3.4
0
0
2 (Poorer)
22.5
9.3
2.4
0
0
3 (Middle)
21.7
25.4
4.3
0
0.3
4 (Richer)
15.3
38.6
13.1
9.1
13.9
5 (Richest)
12.7
24.6
76.8
90.9
85.7
Only 6% of Benin franchise clients
are from the bottom 40% of the
population
Threshold
Clients
Benin
Pakistan
Philippines
Vietnam
$1.25/da
y
Franchise
19%
17%
17%
8%
National
47%
21%
18%
17%
Franchise
61%
72%
51%
51%
National
75%
60%
42%
43%
$2.50/da
y
19% of Benin franchise clients living
under the $1.25/day threshold vs.
47% of the national population
Selection criteria
Criteria
PPI
Wealth Index
Easy to Collect and
Interpret
 Easy to collect
 Easy to collect
 Easy to calculate
 Difficult to calculate
 Easy to interpret poverty threshold
 Quintiles widely used/understood
 $20,000-$25,000 per country
 Inexpensive
 Requires some upkeep costs
 Based on publicly-available DHS
 Percent of clients under poverty line easily
 Wealth quintiles accurate and validated
Low Cost
Comparable to
National Context
comparable to national poverty rate
 Difficult/impossible subgroup analysis e.g.:
comparison to national distribution
 Easy subgroup analysis
just urban, or just FP clients
Comparable Across
Countries
 Percentage of clients under $1.25/day
standard across countries
 Can discuss percentage of clients that fall
within bottom 40%, but measure is
relative to a country
Using Wealth Index routinely
•
•
•
•
•
Randomly select NHIS facilities or enrollment
centers
Conduct exit surveys among clients
• 20 questions about household characteristics
• Adds approximately 10 minutes to each interview
Centralized data analysis in M&E unit – takes about
8 hours
Build capacity through a tool kit and standard syntax
files
Conduct surveys on quarterly or semi-annual basis
Uganda & Kenya: Equity targeting
for program enrollment
•
Uganda & Kenya voucher programs
• Every client identified in the community
using a short targeting tool
• Voucher expires after a year and can
only be used for one service package.
Respondents who had ever used the
HealthyBaby voucher in Uganda (20102011)
35%
30%
25%
20%
15%
10%
5%
0%
Poorest
quintile
Poorer
quintile
Middle
quintile
Richer
quintile
Richest
quintile
Does NHIS enrollment vary by
wealth quintile?
50%
40%
Women (DHS 2008)
All (SHINE, 2009)
30%
20%
10%
0%
Poorest
Less poor
Middle
Less rich
Richest
Conclusions: Active equity targeting
is key component of UHC
•
•
•
•
Tools exist that can cost-effectively identify
the poor for enrollment who, in the
absence of the active identification, would
not have become NHI members
Monitor samples of clients for reporting
against performance targets
Use for beneficiary identification and
enrollment
Consider: Are other exemptions as
effective to achieve the same objective?
Thank you
Social Franchising Metrics Working Group
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Bill & Melinda Gates Foundation
DKT
International Planned Parenthood Federation
Johns Hopkins
Marie Stopes International
Population Services International
Rockefeller Foundation
Population Council
University of California San Francisco
USAID
World Health Partners