From Health and Social Protection: Meeting the needs of the poor, 9-10 October 2008, www.povill.com

1. The Impact of Health Insurance
in Rural China: Evidence from
the New Cooperative Medical
Scheme
POVILL Conference, Vientiane, October 2008
Magnus Lindelow, World Bank
Joint work with:
Adam Wagstaff, World Bank
Gao Jun, CHSI, Ministry of Health, China (now WHO, Manilla)
Xu Ling , CHSI, Ministry of Health, China
Qian Juncheng , CHSI, Ministry of Health, China

2. Background
 Many countries are experimenting with reforms to
expand health insurance to the informal sector
 Subsidized participation in national schemes (e.g. Colombia,
Philippines and Vietnam)
 Separate subsidized contributory scheme (e.g. Mexico)
 Separate fully subsidized scheme (Thailand)
 China introduced a new health insurance scheme in rural
areas in 2003
 Initially rolled out in around 300 counties—rapidly expanding
towards national coverage
 Aim of research is to evaluate early impact of scheme on
use of health services and health expenditures

3. China’s New Cooperative Medical
Scheme (NCMS)
 ‘Old’ CMS collapsed during 1980s—at same time health care costs
increased dramatically
 Resulted in high incidence of catastrophic spending and increased
barriers to utilization
 Aims of NCMS are to reduce impoverishment resulting from illness
and encourage utilization of needed care
 Key features of NCMS
 County-based (200-300K population)
 Voluntary participation (~80% in most counties)
 Variation in design and implementation across counties
 In principle focus on IP; in practice OP also covered in most counties
 Few measures to control costs
 Financing (at time of evaluation—fall of 2005)
 Flat-rate household contribution (min. 10 RMB / USD 1.3)
 Government subsidy (min. 40 RMB / USD 5.5)
 Small share of overall p.c. rural health spending (~250 RMB)

4. Evaluation question and approach
 Evaluation question
 What has been impact of NCMS on health expenditures and use of
health services?
 Also component based on facility level data—not covered here
 Pre-intervention data from 2003 National Health Survey (MOH)
 Post-intervention data from new household survey (Sept. 2005)
 10 counties with NCMS, 5 without NCMS (purposively selected)—8,476
households
 Also broader cross-section sample
 Control group: households in “non-exposed” counties
 Alternative approach: non-participating households in NCMS counties
 Evaluation of impact though combination of differences-in-
differences (DD) and matching
 DD to deal with unobserved (time-invariant) heterogeneity
 Matching to control for observed heterogeneity
 Estimate impact for sample & individual income deciles
 Quantitative analysis complemented with qualitative work

5. Methods
 Propensity score matching (PSM) to match treated &
untreated HHs and estimate average treatment on the
treated (ATT)
 Probit analysis (1=NCMS member, 0=HH in non-NCMS county)
 Nearest neighbor matching (5), with caliper (requiring
sufficient “closeness”)
 Significant differences between NCMS and non-NCMS
counties
 Poorer and more rural counties
 Matching achieves good balancing on observables,
except when treated HHs are matched with HHs in non-
NCMS counties
 Some bias on observables remain
 Better matching if use non-members in NCMS counties
 But problem of unobservables

6. Use of services
OP visit last 2 weeks 52%
OP visit village clinic 56%
OP visit THC 21%
OP visit county hospital 81%
IP episode last 12 months 42%
IP episode: THC 24%
IP episode: county hosp. 53%
# IP episodes (12 months) 119%
Expenditures
HH OOPs (12 months) 61%
OOP per OP visit 236%
OOP per IP episode 103%
OOP delivery -61%
ATT (%
change)
OP visits have increased in
village clinics (the poorest
Q) and county hospitals
(other Q)
IP visits have increased (no
significant differences
between bottom and higher
Qs)
Increase in OOPs,
particularly OP visit;
decline in OOPs for
deliveries. Impact on OOPs
less pronounced among
bottom Q
Key findings from HH data

7. Conclusions
 Increase in utilization consistent with findings from other studies
 Most studies from other countries find reduction in OOP—China
seems to be different
 Implications?
 Welfare gains from improved access must be weighed against welfare
losses from demand- and supply-side moral hazard
 Reasons for concern about (supply-side) moral hazard in China
(overuse of drugs and procedures)
 Key limitations
 Short life of program at time of evaluation (<2 years)
 No evidence on impact of health outcomes
 Limited insight into how impact varies with design & implementation
 Potential bias due to imperfect balancing and possible time-variant
unobservables
 Uncertain generalizability due to non-random sample and non-random
program placement

8. Thank you!
For more information on WB work on China’s health system, see:
www.worldbank.org/chinaruralhealth
For copies of paper, email
mlindelow@worldbank.org, with cc to sthitsy@worldbank.org