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Conference Health and social protection: Meeting the needs of the poor Vientiane 2008
Cambodia, China and Lao PDRInitial thoughts from POVILL
www.povill.com
CambodiaChean Rithy MenCentre for Advanced Studies
We will report on…
• Different types of major illness affecting household livelihoods
• Health-seeking behaviors
• Coping strategies to finance health care expenditure
• Impact of HEF on hospital utilization
• Three level health system with first level organized in health district (health centers and referral hospital)
• Public health services are highly subsidized• Public health facilities adopt “flat fees” charging
system• Staff working in public health facilities have modest
economic incentive • Most staff earn their living by dual practices• Private practices are loosely regulated
Cambodian Health Care System
THE STUDY: DESIGN AND DATA COLLECTION
Research sample
Sites
Rapid Household SurveyIn-depth
study
Village HH Person HH
Mongkol Borei 80 2,000 11,495 110
Sonikum 80 2,000 10,950 110
Kirivong80
1,975 10,716 110
Total 240 5,975
33,161 330
PRELIMINARY FINDINGS
Self-reported serious illness last year
N= 33,161 Total number of individual in sample
Percentage of reported serious illness
Mongkol Borei 11,495 13.82%
Sotr Nikum 10,950 14.94%
Kirivong 10,716 16.48%
Average over three ODs 15.05%
Major illness includes more than inpatient care
N=4992 Total number of Individual in Sample (M.I.)
Received Inpatient treatment
Mongkol Borei 1589 29.64%
Sotr Nikum 1637 30.05%
Kirivong 1766 29.38%
Average over three ODs 29.68%
Working days lost due to serious illness
N= 4992 Frequency Percentage
no working days lost 426 11.51%
1-5 workdays lost 343 9.26%
6-10 workdays lost 550 14.86%
11-15 workdays lost 421 11.37%
16-30 workdays lost 696 18.80%
>30 workdays lost 1265 34.17%
Children 1291 25.86%
A highly fragmented health systemDistribution of health seeking behaviors over respective providers (30 days recall period), RHS
Public sector: 18%
Private facility
Health center
NGO clinic
Private practitioner
NGO/religious facility
Did not seek care
District hospital
Pharmacy
Provincial hospital
Kru Khmer
Drugstore/shop
National hospital in Phnom Penh
Provincial hospital
District hospital
Health center
Health post
Outreach
Private facility
Pharmacy
NGO/religious facility
TBA/VHW
Drugstore/shop
Kru Khmer
Monk/religious healer
Did not seek care
NGO clinic
Private practitioner
Mobile drug seller (by moto/boat/car)
Health facility (factory)
Seek treatment in Vietnam/Thailand
Chinese drug shop
Don't know
Different incentives for health professionals with dual practices in public and private settings (n=55)
Factors influencing providers' medical decision in public facilities
0%
20%
40%
60%
80%
100%
No influence Low influence Moderate influence High influence
Factors influencing providers' medical decision in private facilities
0%
20%
40%
60%
80%
100%
No influence Low influence Moderate influence High influence
An example of irrational practices
Coping strategies with major illness
Frequency Percent
Using saving 86 1.4
Reduce food expenditures 24 0.4
Remove children from school 19 0.3
Sell stored food 319 5.3
Sell household assets 99 1.7
Sell production tools 206 3.4
Sell livestock 317 5.3
Sell land 93 1.6
Borrow money from friends/relatives 911 15.2
Borrow money from informal money lender 1,594 26.7
Borrow money from credit institute 234 3.9
Seek additional work 615 10.3
Total of HH reported severe financial problem due serious illness 3,068
(51% total sample)
Redressing health seeking behaviors:HEF as part of the solution?
HEF is a mechanism or fund that• is operated by an independent organisation• in the interest of poor people, • purchases health care for those poor people (from a
public health care provider), • and also pays for all the associated costs (from
non-medical providers).
• Independent = purchaser-provider split , the organisation does not belong to the Ministry of Health.
Functions of HEF
→ Local NGOs are particularly suited to perform these various functions
Targeting for HEF
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
40.00
45.00
no HEF card (n=4782) HEF card (n=1113)
Q1
Q2
Q3
Q4
Q5
HEF boosts utilization of public hospitals(Logistic regression (of likelihood to go to public hospitals (vs other option) for seriously ill people who got the advice from a qualified expert to seek inpatient care (N=1567) RHS)
Odds for a HEF card holder to go to the public hospital are 2.4 higher than someone with a same profile without a HEF card!
,257,000123,437,280-1,358Constant
2,374,000132,045,153,865HEFbook
,899,03014,730,049-,106SES (quintiles ) (=considered as intervalvariable)
2,189,000114,162,208,784Agegroup (more than 45)
1,833,00319,022,202,606Agegroup (16-45)
1,104,6881,161,248,099Agegroup (6-15)
,000320,783Agegroup (refcat: 0-5)
,976,000123,248,005-,024Distance to public hospital
2,122,000124,040,153,752PROVINCE(Takeo dummy)
,930,7011,147,189-,072PROVINCE(Siem Reap dummy)
,000238,727PROVINCE (refcat: BMC)
Exp(B)Sig.dfWaldS.E.B
Variables in the Equation
,257,000123,437,280-1,358Constant
2,374,000132,045,153,865HEFbook
,899,03014,730,049-,106SES (quintiles ) (=considered as intervalvariable)
2,189,000114,162,208,784Agegroup (more than 45)
1,833,00319,022,202,606Agegroup (16-45)
1,104,6881,161,248,099Agegroup (6-15)
,000320,783Agegroup (refcat: 0-5)
,976,000123,248,005-,024Distance to public hospital
2,122,000124,040,153,752PROVINCE(Takeo dummy)
,930,7011,147,189-,072PROVINCE(Siem Reap dummy)
,000238,727PROVINCE (refcat: BMC)
Exp(B)Sig.dfWaldS.E.B
Variables in the Equation
Conclusion• Illness is a major burden for rural households (suffering, health care
expenditures, lost days…).
• Several factors have led to a fragmentation of the Cambodian health system. Many providers are loosely regulated; this leads to unsatisfactory quality of care, irrationnal prescription and unnecessary health care expenditure.
• Due to coping mechanisms adopted by households, households can be tipped into poverty.
• Health equity funds (and the civil society) can be part of the solution to this problem.
• Yet, other measures are needed: improve quality of service and care in public facilities to attract users, maintain a system of public hospitals close to the rural population and regulate private health care facilities, including informal providers.
More to come
• More analysis on RHS and In-depth data• Further analysis or follow-up study on households with
chronic diseases• More analysis on informal health providers
ChinaProfessor JinInstitute of Social and Public Policy
Quantitative Research:Major Research questions and methods
Research questions Dependent variables
Independent variables
Samples collected
Impact of Major illness on household livelihood
Household livelihood
Major illnessCoping strategies
Rapid Household survey: 12000 HH In-depth Interview: 600HH
NCMS’ effect on the out-of-pocket inpatient care expenses.NCMS’ effect on utilization of inpatient service among rural residents.
Medical expenditureOut-of pocket paymentInpatient care
schemes As above
Unnecessary care and drug, and unnecessary cost to the poor
Unnecessary drug, tests, services
Poor/non-poor
3 tracer conditions628 inpatient care
Impact of scheme on unnecessary care, drug
Unnecessary drug, test and services
With/wo scheme
As above
Major Preliminary Findings---1. Household Survey
1 Diversity of Major IllnessConcept/definition, Perception from different actors
– Complicated concept: economically, socially, medically
• Household perception in terms of – inpatient care; – large amount of money spent; – long time drugs-taken; disabled; – great amount of working days lost
• NCMS: not adequate response
Outpatient and inpatient use for selected serious illness groups
Type of serious illness
Percent using inpatient treatment
Percent using only outpatient services
Percent other
Circulatory 13.5 60.5 25.9
Respiratory 16.6 62.6 20.9
Digestive 16.5 57.8 25.7
Urinogenital 15.2 65.2 19.6
2 Demographic changes and its implication for healthcare intervention– Household composition and out migration
• Changing patterns of household composition: – Unit of analysis
• Migrant labor and their health seeking behavior: – Scheme: population targeted
• Impact of changing demographic pattern on household health seeking behavior and their livelihoods
Preliminary findings from household study in China
Major Preliminary Findings---2. Impact of Schemes
With NCMS Social-economic
Situation Yes Ratio (%) No Ratio (%) Total Ratio (%)
Poorest 1587 84.15 299 15.85 1886 100.00
Second 1622 89.42 192 10.58 1814 100.00
Middle 1555 90.78 158 9.22 1713 100.00
Fourth 1607 91.57 148 8.43 1755 100.00
Richest 1616 92.03 140 7.97 1756 100.00
Total 7987 89.50 937 10.50 8924 100.00
The distribution of the social economic situation of households by NCMS
● The poorest were less inclined to be covered by NCMS
• Method– Multiple Linear regression
• Result – The effect of NCMS participation on out-
of-pocket expenses of hospitalization of households with major illness is not statistically significant (P>0.05).
• Method– Two-level logistic regression
• Result
– The effect of NCMS on utilization of hospital service of households with major illness is not statistically significant (P>0.05)
Different household social economic status of MFA targets
• 0.66% of the poorest households were covered by MFA• The overall coverage rate(0.31%) is low
MFA target Social economic status
Number of households N Ratio (%)
Poorest 2410 16 0.66 Second 2410 6 0.25 Middle 2408 5 0.21 Fourth 2407 7 0.29
Richest 2414 3 0.12 Total 12049 37 0.31
Major Preliminary Findings---3. Provider’s performance, Unnecessary Care and Unnecessary cost
Model 1 Model 2 Model 3 Model 4
Economic status (Ref.: Low)
Middle 0.240* 0.230* 0.176+ 0.195*
High 0.386** 0.375** 0.279* 0.312*
Facility level (Ref.: County hospital)
Township Health centre -0.801** -0.701* -0.652*
Health insurance (Ref.: No insurance)
NCMS -0.299* -0.273*
Other insurance -0.234+ -0.166
Doctor education level (Ref.: <3)
3 -0.080
>=5 0.000
Age of the patient -0.114*
Squared age 0.015*
_cons 6.491** 6.533** 6.782** 6.777**
N 207.000 207.000 199.000 201.000
Regression of log transformed total cost of pneumonia
+: P<0.1; *: P<0.05; **: P<0.01; ***: P<0.001 NCMS: New Cooperative Medical Scheme
53.68
1.3
43.72
50.22
2.6
48.48
020
4060
unnecessary nucessary more needed
Percent of Unnecessary Care for Treating Pneumonia
drug test_exam
37.4
42.040.4
010
20
30
40
Un
ne
cess
ary
co
st o
f dru
g
1 2 3
Median unnecessary cost of drug treating pneumonia by economic status (RMB Yuan)
Major Preliminary Findings---4. Institutional Analysis
Qualitative researchMajor Research questions and methods
Research Questions MethodsPolicy process of the NCMS and MFA at national level;
Impact of the policy context and the interplay of relevant stakeholders on policy process
- Literature and record review: documents/published paper/gray report/ news;- Key informants interview : officials from MOH, MOCA, MOF; hospital managers; - Focus group discussion: rural residents- Participatory observation: policy seminar by MOCA, workshops
Qualitative research --Main findings
Rural health policy process: response to the transitional context of China - unequal share of the resources distributed; - unequal access to essential health care; - political priority shift to harmonious development; - rising concern on rural health development; - more revenues to support
Stakeholder analysis: - political elites & academic elites: significant role - the media: active in shaping public opinion - rural residents: passive recipients of policies
Formal/informal mechanisms: not sufficiently to voice out the interest of rural residents
“Its not the end, its just the end of beginning” ----Churchill
With the unique datasets, More findings are coming
Medical care used:Medical records
In hospital
Patient and household Social and
economic data:Exit interview
Medical Cost data:hospital account
Linked
6000 householdsurvey
600 householdIn-depth interview
Next steps
• To Provide the evidence by– Dealing with selection bias– Dealing with confounding factors
• To Influence evidence-based policy making process to– Improve better targeting of scheme– Improve design and implementation of schemes– Improve provider’s performance for cost-effective
services
Lao PDRAnonh XeuatvongsaMinistry of Health
Topics to be covered in the presentation
• Country profile• Enforcement of medical law• Findings from the research into the level and causes of household poverty and health seeking behaviour• Analysis of the way in which the Health Equity Fund is working• Some findings related to provider performance• Further issues to be explored
Country Profile & Health Indicators
• Population: 5.82 millions (2007)
• GDP 701US$ per capita (2007)
• GDP annual growth rate: 7.9%
(2007)
• 30% of the population under
poverty line (2005)
• Life expectancy 61 years (female
62, male 59) (2005)
• IMR 70 per 1000 live births
(2005)
• U5MR 98 per 1000 live births
(2005)
• MMR 405 per 100.000 live births
(2005)
Data source: National report 2006-07 and National census 2005.
National Health Expenditure
• 3.6% of GDP in 2005
• 17.5 USD per capita in
2005
- Out of pocket: 79.8% of
THE
- Donor: 11.3% of THE
- Domestic Gov. : 8.9% of
THE
• GGE on Health as % of
GGE: 4.6%
• Social security fund as %
of GGHE: 11.2%Data source: NHA unit, EIP/HSF/CEP, WHO, Geneva 2007
Transform of Medical Law into practice
Lao has a strong legal framework to protect poor people from catastrophic illness. However,• Law dissemination is yet saturated in public and whose responsibility is not clear,• Institutional arrangement to enforce the Law’s implementation is yet sufficient, • Fee exemption for poor is not standardized,• Inconsistent in identifying poverty level in different sectors.
Graph 1: Percentage of number of poor households officially recognized ( N= 3000 HHs )
91%
9%
No
Yes
Graph 2 : Comparison of Percentage of main reasons of being poor among 9% of poor (n = 270 recognized as poor households)
0.00% 20.00% 40.00% 60.00% 80.00%
a
b
c
d
e
e
d
c
b
a
a = Poor environment (e.g. unfertile soil, no land, natural disaster, crops damage by wild animals e.g. insects and mice…)b = Labor shortagec = Many dependentsd = Illness / disabilitye = Other
Rapid HH Survey [ in general ] (n=3000hh) : In-Dept Studies [ serious illness ] (n=150hh) .
Self Treatm. Out Patient In Patient .
Type of facility No ( n=809) (%) No (n=70hh) (%) No(n=99hh) (%) No(n=99hh) (%)
1. Govt. hospital : 353 43.64 15 21.5 65 65.6 65 65.6
a. Provincial Hospital : 138 17.1 9 12.9 44 44.4 44 44.4
b. District Hospital ] : 215 26.6 6 8.6 21 21.2 21 21.2
2. Govt. primary facility: 101 12.5 3 4.3 11 11.1 11 11.1[ Health center ]
3. Private facility : 30 3.7 7 10 2 2 2
4. Pharmacy: 182 22.5 33 47.1 3 3 3
5.. TBA/VHW : 19 2.3 1 1.4 3 3 3 3
6. Drugstore/shop/trader : 4 0.5 0 0 0 0 0 0
7. Traditional healer : 14 1.7 9 12.9 4 4.04 4 4.04
8. Religious faith healer : 4 0.5 1 1.4 2 2 2 2
9. Other : 94 11.6 1 1.4 9 9.1 9 9.1
10. Did not seek care: 8 0.9 0 0 0 0 0 0
Total 809 100 70 100 99 100 99 100
Remarks : 1. Poor households : 9% ( out of 3000 hh )
2. Death: n = 90 persons =>0.53% out of 17 093 persons
3. Serious health problem no treated because of cost: n = 102hh =>47.67
(out of 214 hh get serious health problem [ n = 219 persons] )
Health seeking behavior of people in the last month before the survey
Health seeking behavior of people with severe illnesses
Type of facilities Number of Households (n = 3000 ) Percent ( %) 1. Central hospital : 51 1.7 2. Provincial hospital : 712 23.7 3. District Hospital : 1545 51.5 4. Health Centre : 440 14.675. Private clinic : 75 2.5 6. Outside country : 10 0.3 7. Other ** : 167 5.63 Total 3000 100 .Remark : Specified places ** : 1. Military hospital : 81 HH => 48.51% out of 167 HH 2. Traditional medicine : 40 HH => 23.96 % ; 3. Pharmacy : 12 HH => 7.19% .
Coverage of Health Equity Fund
Number Percent Number Percent Number Percent % Year
Nambak District 6,535 11 4,652 8 4,652 7 20 2002
Vientiane province 10,148 3 11,230 3 11,230 3 6 2008
Sepone 7,984 23 10,890 24 34 2002
Location Pre-identified HEF member
2006 2007 2008Poverty rate
(NGPES)
103
23
407
230
462
253 258
55
289
125
272
104
26
200
397
102
1067
130
36
289
1076
468
1% 0%3% 3%
8% 7%
2% 1% 2% 2% 2%1% 1% 2%
8%
2%
28%
1% 1% 3%
27%
6%
0%
20%
40%
60%
80%
100%
0
200
400
600
800
1,000
1,200
1,400
SNK VKH FEU KAS HHP MAE TOU KEO PHG HOM VVG
% o
f poo
r hou
seho
lds
in p
rovi
nce
Poor
hou
seho
lds
in p
rovi
nce
HEF pre-identified Poor-Households in Vientiane Province
HEF HH (2007)
Poor Prov HH (2008)
%HEF HH (2007)
% Poor Prov HH (2008)
HEF: 2.522 HH (11.230 pers) pre-dentified = 3% of HH (3% pers.)vs
Poor Province: 3.895 HH (23.412 pers) pre-dentified = 5% of HH (6% pers.)
Excluding Saysomboun district
• General poverty level:– Three different situation from Sepone (very poor but changing very fast) to
average rural situation (Nambak) and low poverty rate (in Vientiane Province but ranging from 1 to 15% across districts)
• HEF coverage:– Lower rate of HEF pre-identification in Nambak and Vientiane Province
versus general poverty level defined by government (30% in 2005)– Decrease HEF in Nambak, and stable in Vientiane and Sepone
* NGPES = National Growth and Poverty Eradication Strategy
HEF by Wealth index. Study sites: Nambak, Vangvieng and Sepone
0
10
20
30
40
50
60
70
80
90
100
HEFNB
Poorest: 15,7%
Second: 23,4%
Middle: 23,2%
Fourth: 22%
Richest: 15,7%
0
10
20
30
40
50
60
70
80
90
100
HEFB
Poorest: 59,1%
Second 26,1%
Middle: 6,8%
Fourth: 8%
HEF Bénéficiaires (n=88) HEF Non Bénéficiaires (n=1412)
Source: RHS
Utilization of HEF
OPD: Visible positive impact of HEFB in Nambak and Vientiane ProvinceIPD: Visible positive impact of HEFB in the 3 HEF Schemes
Costs
Yearly data (Nambak, Vientiane province:
2007, Sepone: 2007/08)
Nambakdistrict
VientianeProvince (11 districts)
Sepone district
Total benefits/year $19,717 $54,896 $19,108
total benefits/HEFB capita
HEF Pre-id: $2,3; HEF Post-id: $1,9
HEF Pre-id: $2,8; HEF Post-id: $2,2 HEF Pre-id: $1,7
% OPD-IPD 12% vs 88% 19% vs 81% 18% vs 82%
% medical fees-transport-others 82% vs 16% vs 2% 74% vs 13% vs
13% 82% vs 11% vs 7%
Knowledge on types of services for free with the HEF members
Knowledge on benefits of HEF HEF Beneficiaries NEF NB
N % N %
Free medical services 78 98.7 470 98.5
Free food and soap while hospitalized 24 30.4 213 44.7
Free ambulance transportation to upper level
36 45.6 188 39.4
Free transportation back home of a relative’s body dead while hospitalized
34 43.0 147 30.8
Other (Room) 1 2.6 3 0.6
Provider performance
• No significant differences in treating poor and non poor patients
• Use of Essential Medicines is high in treating pneumonia 95% in poor patient (T1), 94% in near poor (T2) and 100% in non poor (T3)
• Unnecessary cost may not be high since many Essential Medicines prescribed
Provider performance continued
• However informal payment was 32% considered as unnecessary cost
• Access to health care for the poor may be a problem as expressed by one villager: “having no money for the care cost I would prefer dying at home rather than going to hospital”
Issues for further exploration
• How do we increase knowledge amongst potential users of the benefits of the Health Equity Fund beyond free medical care?
• Should we extend the Health Equity Fund to the 15% of the population classed as very poor who are not currently covered? How?
• How can we encourage patients to utilise health centres?
• What is the optimum strategy for preventing the misuse of the Health Equity Fund?
• What institutional arrangement should be seriously made to enforce the medical law?