GAP ESTIMATING MODEL: Future supply vs demand in Indonesia s healthcare system

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1 2 nd InaHEA Congress, April 2015 GAP ESTIMATING MODEL: Future supply vs demand in Indonesia s healthcare system Ufara Zuwasti Curran, Prastuti Soewondo, Halimah, James P. Thompson National Team for Accelerating Poverty Reduction

2 Supply Side Challenges 2

3 Hypertension: Diagnosed vs Unmet Needs Pabar Lampung Lampung Papua DKI Jakarta Banten Sulut Jabar Aceh Sumut Kalbar Kaltim Gorontalo Kepri NTT Sulsel Malut Sumbar Bali Kalteng Jambi Sultra Maluku Sumsel NTB Riau DI Yogyakarta Babel Sulteng Sulbar Sulbar Jatim Kalsel Sick Treated Source: Riskesdas

4 Research question: What is the gap between the medical needs of Indonesians and the health care system capacity to fulfil those needs? Aims: To build structure that permits deeper analysis and understanding about gaps in supply and demand Examine future demand of healthcare services as healthcare insurance expands and healthcare supply to serve it Provide recommendations to improve supply adequacy GEM study is a system approach. It accounts for dynamics of and relationship between supply and demand from three perspectives: Accessibility Affordability Availability Gap Estimating Model Study 4

5 Fundamental Dynamics in Indonesia s Healthcare System 5

6 How Supply (Healthcare Facilities) Affect Demand? 6

7 How to estimate medical needs (demands) of population? What is the health status of population? What is the agreed standards of care received by population? Assumption used as standards of care: Askes insured population prior to 2014 Why not other utilization Methodology Who is our population? Population is dynamic 32 cohorts = 2 gender groups * 4 age groups * 4 health insurance status Askes rates (by age and gender) were extrapolated to all venues and adjusted, accounting for insured status groups and accessibility. Healthcare capacities (supply) Doctors, nurses, midwives, hospital facilities rates? 7

8 Small models for Population and insured status For doctors, nurses, midwives, and hospital beds Parameters & initial values*: birth, mortality, migration rates, insured status, current capacity for supply, enrolment, graduation, attrition rates, practice patters for HCW, hospital capacity growth rates, admission rates, ALOS, etc Small models to larger model that simulates the whole country (national model) 200+ parameters and initial values Methodology (2) Demand is affected by affordability, accessibility, and availability and is measured as unconstrained demand, desired/expected/real demand, and constrained demand Gap was calculated between capacity and assumed standard of care The concept was carried to 34 provincial models, with 200+ parameters and initial models for each province *Data Sources : BPS 2010 population data; BPS population projection; UNDESA ; BPS birth, mortality, migration rates; MOH insured status; Registered physicians MOH; Practicing nurses and midwives MOH; Hospital capacity and ALOS MOH; Askes utilization rates MOH; Susenas 2013; PODES 2011; etc. 8

9 Gender Age Methodology (3) Adjustment factor (relative to Askes) Outpatient Inpatient Midwife Uninsured JKN Jamkesda Private Illustration for JKN insured group rates relative to Askes after adjusted using adjustment* and accessibility** factors Outpatient (primary) Inpatient (primary) Outpatient (hospital) Inpatient (hospital) Askes Adjusted Askes Adjusted Askes Adjusted Askes Adjusted Male Female Male Female Male Female Male Female Average * Estimates agreed by research team **PODES

10 40 M 36 M Laki-laki Population Projection and Change in Insurance Status Perempuan Age 00 to 14 Indonesia 300 M TOTAL NATIONAL POPULATION people people 32 M 28 M 24 M 20 M M 58 M 56 M 54 M Age 15 to 44 Indonesia people 280 M 260 M 240 M 220 M 200 M Date total natl population : Indonesia 52 M 250,000,000 JKN Jamkesda Private Uninsured 50 M M Age 45 to 64 Indonesia 200,000, M people 26 M 24 M 150,000, M 20 M ,000, M 9 M Age 65 and over Indonesia 50,000,000 8 M people 7 M 6 M 5 M

11 DOCTORS Supply and Demand for Doctors Gap Practicing doctors Desired demand Constrained demand Primary Care 300, , , Hospital 100,000 50, Practicing doctors Desired demand Province Total Primary care Hospital Jatim Jateng Jabar Jakarta Bali Banten Lampung NTB Sulsel Sumsel Sumbar Kalsel Sumut Jambi Aceh Kalbar Bengkulu NTT Sultra Sulteng Babel Gorontalo Kalteng Sulbar Maluku Riau Kaltara Kaltim Pabar Malut Sulut Kepri Jogja Papua <(20,000) (10,001)-(20,000) (5,001)-(10,000) (2,001)-(5,000) (1)-(2,000) 0 1-2,000 2,001-5,000 5,001-10,000 10,001-20,000 >20,000 11

12 Supply and Demand for Nurses 250, , , ,000 50, , , , ,000 50,000 - Gap Hospital Perawat di RS Primary care Perawat di Yankes Primer Permintaan perawat di Yankes Primer Permintaan perawat di RS NURSES Practicing nurses Desired demand Constrained demand Practicing nurses Desired demand Province Total Primary care Hospital Jatim Jabar Jateng Banten Bali Sulsel Lampung Sumsel Jakarta Sumut Sumbar NTB Jogja Kalsel Jambi Babel Gorontalo Sulbar Kepri Sulut Kaltara Bengkulu Sulteng Kalbar Malut Kaltim Pabar Sultra Riau NTT Kalteng Maluku Aceh Papua <(20,000) (10,001)-(20,000) (5,001)-(10,000) (2,001)-(5,000) (1)-(2,000) 0 1-2,000 2,001-5,000 5,001-10,000 10,001-20,000 >20,000 12

13 MIDWIVES Supply and Demand for Midwives Surplus Practicing doctors Desired demand HOSPITAL BEDS Supply and Demand for Hospital Beds Gap Capacity Desired demand Constrained demand Province Midwife Kaltara Sulbar Babel Gorontalo Jogja Pabar Kaltim Malut Kepri Maluku Jakarta Banten Kalteng Sulut Sultra Sulsel Papua Kalbar Sulteng Jambi Bali Kalsel Bengkulu Lampung Riau NTB NTT Sumsel Sumbar Jabar Aceh Sumut Jatim Jateng Province Hospital beds Jakarta Jateng Jabar Jatim Sulsel Sumsel Bali Jambi Lampung Banten Sumbar Sumut Riau Kalsel Sulteng NTB NTT Sulut Babel Aceh Kalteng Kalbar Sultra Bengkulu Malut Sulbar Gorontalo Maluku Kaltara Kepri Pabar Kaltim Papua Jogja <(20,000) (10,001)-(20,000) (5,001)-(10,000) (2,001)-(5,000) (1)-(2,000) 0 1-2,000 2,001-5,000 5,001-10,000 10,001-20,000 >20,000 13

14 Provincial Gap Summary 33 Deficiency 1 Doctors Surplus: Papua Worst: Jatim, Jateng, Jabar, Jakarta, Bali, Banten 17 Deficiency Nurses 17 Surplus: Papua, Aceh, Maluku, Kalteng, NTT, Riau, Sultra, Pabar, Kaltim, Malut, Kalbar, Sulteng Bengkulu, Kaltara, Sulut, Kepri, Sulbar Worst: Sulsel, Lampung, DKI Jakarta, Jawa Tengah 5 Surplus: Jogja, Papua, Kaltim, Pabar, Kepri 29 Deficiency Hospital beds Worst: Jakarta, Jateng, Jabar, Jatim 34 No deficiency Midwives 14

15 CONCLUSIONS Availability of healthcare services is the greatest constraint on utilization Shortfalls in physicians, nurses, and hospital beds, and no deficiency in midwives In particular, the likely demand for physician and nurse services exceeds available capacities at all care levels For nurses, the gap will widen when numbers of physicians and hospital beds reach ideal figures For midwives, however, local customs and need for more midwives where the population is spread out indicate that the surplus is smaller than estimated Insufficient capacity at the primary care level increases the burden at the hospital level The generous governmental funding of healthcare costs makes shortfall in capacities even more evident While remote areas will remain difficult to serve in future, it is possible and even likely that more physicians and allied healthcare workers will be drawn to metropolitan areas, exacerbating access issues for Indonesians living in rural areas Quality and distribution of healthcare workers are still main problems, in addition to quantity RECOMMENDATIONS A 10 year strategic Master Plan Focus infrastructure development in rural/remote areas Primary care strengthening to reduce secondary care burden Development of tax policies to encourage investment by private sector Engage development partners, ministries, professional organizations, private sectors, NGO Improve quality of medical, nursing, midwifery trainings and provide continuous trainings Increase quota and number of medical schools Use of physician extenders add qualifications for nurses and midwives A national service commitment which places HCWs in rural and remote areas should be considered for bonded in lieu compensations. There may be needs to modify incentives Consider placement of foreign doctors in strategic areas 15

16 Thank you 16