2nd 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
Supply Side Challenges
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Hypertension: Diagnosed vs Unmet Needs 45.0
45.0 40.0
40.0 35.0
35.0 30.0
30.0 25.0
25.0 20.0
20.0 15.0
15.0 10.0
10.0 5.0
5.0
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
|3 Source: Riskesdas 2010
Gap Estimating Model Study • 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 |4
Fundamental Dynamics in Indonesia’s Healthcare System
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How Supply (Healthcare Facilities) Affect Demand?
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Methodology • 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 rates?
• 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
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Methodology (2) • “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
• 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 2010-2035 population projection; UNDESA 2010 – 2015; 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.
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Methodology (3) Adjustment factor (relative to Askes) Uninsured JKN Jamkesda Private
Outpatient
Inpatient
Midwife
0.5 0.9 0.7 1.1
0.2 0.8 0.8 1.2
0.5 0.9 0.7 1.1
Illustration for JKN insured group rates relative to Askes after adjusted using adjustment* and accessibility** factors Gender
Age
Outpatient (primary)
Inpatient (primary)
Outpatient (hospital)
Inpatient (hospital)
Male
Askes Adjusted Askes Adjusted Askes Adjusted Askes Adjusted 0-14 261.68 201.16 1.91 1.45 24.54 18.87 6.23 4.72
Female
0-14
378.50
290.96
2.42
1.84
28.00
21.52
6.97
5.28
Male
15-44
209.95
161.39
1.16
0.88
28.82
22.15
5.02
3.80
Female
15-44
243.10
186.88
2.50
1.89
32.90
25.29
5.62
4.26
Male
45-64
428.84
329.66
1.35
1.03
72.61
55.82
6.97
5.28
Female
45-64
558.69
429.48
1.90
1.44
82.34
63.30
7.74
5.87
Male
65+
437.97
336.68
1.64
1.24
77.96
59.93
8.41
6.37
Female
65+
635.84
488.79
2.53
1.92
87.90
67.57
9.30
7.04
394.32
303.13
1.93
1.46
54.38
41.81
7.03
5.33
Average
* Estimates agreed by research team **PODES 2011
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Population Projection and Change in Insurance Status Perempuan
Laki-laki
Age 00 to 14 Indonesia
TOTAL NATIONAL POPULATION
40 M
300 M 280 M
32 M 28 M
people
people
36 M
24 M 20 M 2010 2011
2012 2013
2014 2015
2016 2017
2018 2019
260 M 240 M
2020
220 M Age 15 to 44 Indonesia 60 M
200 M 2010
people
58 M 56 M
2011
2012
2013
2014
2015 Date
2016
2017
2018
2019
2020
total natl population : Indonesia
54 M
250,000,000
52 M 50 M 2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
JKN
Jamkesda
Private
Uninsured
2020
Age 45 to 64 Indonesia 30 M
200,000,000
people
28 M 26 M
150,000,000
24 M 22 M 20 M 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
100,000,000
Age 65 and over Indonesia 10 M
people
9M
50,000,000
8M 7M
-
6M 5M 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
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DOCTORS Supply and Demand for Doctors
Gap
Desired demand
Practicing doctors
Constrained demand
Primary Care 300,000 200,000 100,000 2014 2015 2016 2017 2018 2019 2020
Hospital 100,000
50,000
2014 2015 2016 2017 2018 2019 2020
Practicing doctors
Desired demand
Province Total 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
Primary care Hospital
<(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
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NURSES Supply and Demand for Nurses
Gap
Constrained demand
Desired demand
Practicing nurses
Primary care 250,000 200,000 150,000 100,000 50,000 2014 2015 2016 2017 2018 2019 2020 Perawat di Yankes Primer Permintaan perawat di Yankes Primer
Hospital 250,000 200,000 150,000 100,000 50,000 2014 2015 2016 2017 2018 2019 2020 Perawat di RS
Practicing nurses
Permintaan perawat di RS
Desired demand
Province Total 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
Primary care Hospital
<(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
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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
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Provincial Gap Summary
1
Surplus:
17
Papua
17
Deficiency
33
Papua, Aceh, Maluku, Kalteng, NTT, Riau, Sultra, Pabar, Kaltim, Malut, Kalbar, Sulteng Bengkulu, Kaltara, Sulut, Kepri, Sulbar Worst: Sulsel, Lampung, DKI Jakarta, Jawa Tengah
Worst:
Deficiency
Surplus:
Jatim, Jateng, Jabar, Jakarta, Bali, Banten
Nurses Doctors
5 29
Deficiency
Hospital beds
Surplus: Jogja, Papua, Kaltim, Pabar, Kepri
34
Worst: Jakarta, Jateng, Jabar, Jatim
No deficiency
Midwives | 14
RECOMMENDATIONS
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
• • • • • • • • •
•
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
Thank you
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