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Conference  Health and social protection: Meeting the needs of the poor  Vientiane 2008 Cambodia, China and Lao PDR Initial thoughts from POVILL www.povill.com
Cambodia Chean Rithy Men Centre for Advanced Studies
We will report on… ,[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Cambodian Health Care System
THE STUDY: DESIGN AND DATA COLLECTION
Research sample Sites   Rapid Household Survey In-depth study   Village HH Person HH Mongkol Borei 80 2,000 11,495 110  Sonikum 80 2,000  10,950      110 Kirivong 80   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 system Distribution of health seeking behaviors over respective providers (30 days recall period), RHS Public sector: 18%
Different incentives for health professionals with dual practices in public and private settings (n=55)
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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? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Functions of HEF ->   Local NGOs  are particularly suited to perform these various functions
Targeting for HEF
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!
Conclusion ,[object Object],[object Object],[object Object],[object Object],[object Object]
More to come ,[object Object],[object Object],[object Object]
China Professor Jin Institute 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 illness Coping 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 expenditure Out-of pocket payment Inpatient care schemes As above Unnecessary care and drug, and unnecessary cost to the poor Unnecessary drug, tests, services Poor/non-poor 3 tracer conditions 628 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
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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
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Preliminary findings from household study in China
Major Preliminary Findings ---2. Impact of Schemes
The distribution of the social economic situation of households by NCMS  ●   The poorest were less inclined to be covered by NCMS
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Different household social economic status of MFA targets  ,[object Object],[object Object]
Major Preliminary Findings ---3. Provider’s performance, Unnecessary Care   and Unnecessary cost
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 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
 
Median unnecessary cost of drug treating pneumonia by economic status (RMB Yuan)
Major Preliminary Findings ---4. Institutional Analysis
Qualitative research Major Research questions and methods Research Questions Methods Policy process of the NCMS and MFA at national level; Impact of the policy context and the interplay of relevant stakeholders on policy process ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Qualitative research   --Main findings ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
“ Its not the end, its just the end of beginning”   ----Churchill With the unique datasets, More findings are coming 6000 household survey 600 household In-depth interview
Next steps ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Lao PDR Anonh Xeuatvongsa Ministry of Health
Topics to be covered in the presentation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Country Profile & Health Indicators  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Data source: National report 2006-07 and National census 2005.
National Health Expenditure ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Data source: NHA unit, EIP/HSF/CEP, WHO, Geneva  2007
Transform of Medical Law into practice  ,[object Object],[object Object],[object Object],[object Object],[object Object]
Graph 1: Percentage of number of poor households officially recognized ( N= 3000 HHs )
Graph 2 :  Comparison of Percentage of main reasons of being poor among 9% of poor (n = 270 recognized as poor households)  a = Poor environment (e.g. unfertile soil, no land, natural disaster, crops damage by wild animals e.g. insects and mice…) b = Labor shortage c = Many dependents d = Illness / disability e = Other
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],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  14.67 5. 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 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
HEF by Wealth index. Study sites: Nambak, Vangvieng and Sepone HEF Bénéficiaires (n=88) HEF Non Bénéficiaires (n=1412) Source: RHS
Utilization of HEF OPD: Visible positive impact of HEFB in Nambak and Vientiane Province IPD: Visible positive impact of HEFB in the 3 HEF Schemes
Costs Yearly data (Nambak, Vientiane province: 2007, Sepone: 2007/08) Nambak district Vientiane Province  (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 ,[object Object],[object Object],[object Object]
 
Provider performance continued ,[object Object],[object Object]
 
Issues for further exploration ,[object Object],[object Object],[object Object],[object Object],[object Object]

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3 Country Presentation For Vientiane Conference

  • 1. Conference Health and social protection: Meeting the needs of the poor Vientiane 2008 Cambodia, China and Lao PDR Initial thoughts from POVILL www.povill.com
  • 2. Cambodia Chean Rithy Men Centre for Advanced Studies
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  • 5. THE STUDY: DESIGN AND DATA COLLECTION
  • 6. Research sample Sites   Rapid Household Survey In-depth study   Village HH Person HH Mongkol Borei 80 2,000 11,495 110  Sonikum 80 2,000  10,950     110 Kirivong 80   1,975 10,716     110 Total 240   5,975   33,161 330  
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  • 10. 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%
  • 11. 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%
  • 12. 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%
  • 13. A highly fragmented health system Distribution of health seeking behaviors over respective providers (30 days recall period), RHS Public sector: 18%
  • 14. Different incentives for health professionals with dual practices in public and private settings (n=55)
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  • 16. 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)
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  • 18. Functions of HEF -> Local NGOs are particularly suited to perform these various functions
  • 20. 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!
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  • 23. China Professor Jin Institute of Social and Public Policy
  • 24. 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 illness Coping 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 expenditure Out-of pocket payment Inpatient care schemes As above Unnecessary care and drug, and unnecessary cost to the poor Unnecessary drug, tests, services Poor/non-poor 3 tracer conditions 628 inpatient care Impact of scheme on unnecessary care, drug Unnecessary drug, test and services With/wo scheme As above
  • 25. Major Preliminary Findings ---1. Household Survey
  • 26.
  • 27. 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
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  • 29. Major Preliminary Findings ---2. Impact of Schemes
  • 30. The distribution of the social economic situation of households by NCMS ● The poorest were less inclined to be covered by NCMS
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  • 34. Major Preliminary Findings ---3. Provider’s performance, Unnecessary Care and Unnecessary cost
  • 35. 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 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
  • 36.  
  • 37. Median unnecessary cost of drug treating pneumonia by economic status (RMB Yuan)
  • 38. Major Preliminary Findings ---4. Institutional Analysis
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  • 41. “ Its not the end, its just the end of beginning” ----Churchill With the unique datasets, More findings are coming 6000 household survey 600 household In-depth interview
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  • 43. Lao PDR Anonh Xeuatvongsa Ministry of Health
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  • 48. Graph 1: Percentage of number of poor households officially recognized ( N= 3000 HHs )
  • 49. Graph 2 : Comparison of Percentage of main reasons of being poor among 9% of poor (n = 270 recognized as poor households) a = Poor environment (e.g. unfertile soil, no land, natural disaster, crops damage by wild animals e.g. insects and mice…) b = Labor shortage c = Many dependents d = Illness / disability e = Other
  • 50.
  • 51. 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 14.67 5. 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% .
  • 52.
  • 53. HEF by Wealth index. Study sites: Nambak, Vangvieng and Sepone HEF Bénéficiaires (n=88) HEF Non Bénéficiaires (n=1412) Source: RHS
  • 54. Utilization of HEF OPD: Visible positive impact of HEFB in Nambak and Vientiane Province IPD: Visible positive impact of HEFB in the 3 HEF Schemes
  • 55. Costs Yearly data (Nambak, Vientiane province: 2007, Sepone: 2007/08) Nambak district Vientiane Province (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%
  • 56. 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
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