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GAP ESTIMATING MODEL: Future supply vs demand in Indonesia’s healthcare system
National Team for Accelerating Poverty ReductionUfara Zuwasti Curran, Prastuti Soewondo, Halimah, James P. Thompson
2nd InaHEA Congress, April 2015
Supply Side Challenges
| 2
Hypertension: Diagnosed vs Unmet Needs
Source: Riskesdas 2010
KalselJatimSulbarSulbarSultengBabelD
I YogyakartaR
iauN
TBSum
selM
alukuSultraJam
biKaltengBaliSum
barM
alutSulselN
TTKepriG
orontaloKaltimKalbarSum
utAcehJabarSulutBantenD
KIJakartaPapuaLam
pungLam
pungPabar
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
SickTreated
| 3
• 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
| 6
How Supply (Healthcare Facilities) Affect Demand?
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
• 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: Askesinsured population prior to 2014
• Why not other utilization rates? | 7
• “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
Methodology (2)
*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; Susenas2013; PODES 2011; etc. | 8
Methodology (3)
Gender AgeOutpatient (primary) Inpatient (primary) Outpatient (hospital) Inpatient (hospital)
Askes Adjusted Askes Adjusted Askes Adjusted Askes AdjustedMale 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
Average 394.32 303.13 1.93 1.46 54.38 41.81 7.03 5.33
Adjustment factor (relative to Askes) Outpatient Inpatient Midwife
Uninsured 0.5 0.2 0.5 JKN 0.9 0.8 0.9
Jamkesda 0.7 0.8 0.7 Private 1.1 1.2 1.1
Illustration for JKN insured group rates relative to Askes after adjusted using adjustment* and accessibility** factors
* Estimates agreed by research team **PODES 2011 | 9
Population Projection and Change in Insurance StatusAge 00 to 14 Indonesia
40 M
36 M
32 M
28 M
24 M
20 M2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
peop
le
Age 15 to 44 Indonesia
60 M
58 M
56 M
54 M
52 M
50 M2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
peop
le
Age 45 to 64 Indonesia
30 M
28 M
26 M
24 M
22 M
20 M2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
peop
le
Age 65 and over Indonesia
10 M
9 M
8 M
7 M
6 M
5 M2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
peop
le
TOTAL NATIONAL POPULATION300 M
280 M
260 M
240 M
220 M
200 M2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Date
peop
le
total natl population : Indonesia
-
50,000,000
100,000,000
150,000,000
200,000,000
250,000,000
Laki-laki Perempuan
JamkesdaJKN UninsuredPrivate
| 10| 10
<(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
-
100,000
200,000
300,000
2014 2015 2016 2017 2018 2019 2020
Primary Care
Province Total Primary care HospitalJatim
JatengJabar
JakartaBali
BantenLampung
NTBSulsel
SumselSumbar
KalselSumutJambiAceh
KalbarBengkulu
NTTSultra
SultengBabel
GorontaloKaltengSulbar
MalukuRiau
KaltaraKaltimPabarMalutSulutKepriJogja
Papua
Gap
DOCTORS
Practicing doctors Desired demand Constrained demand
Supply and Demand for Doctors
Desired demandPracticing doctors
-
50,000
100,000
2014 2015 2016 2017 2018 2019 2020
Hospital
| 11
-
50,000
100,000
150,000
200,000
250,000
2014 2015 2016 2017 2018 2019 2020
Hospital
Perawat di RS Permintaan perawat di RS
- 50,000
100,000 150,000 200,000 250,000
2014 2015 2016 2017 2018 2019 2020
Primary care
Perawat di Yankes Primer
Permintaan perawat di Yankes Primer
<(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
Gap
Province Total Primary care HospitalJatimJabar
JatengBanten
BaliSulsel
LampungSumselJakartaSumut
SumbarNTB
JogjaKalselJambiBabel
GorontaloSulbarKepriSulut
KaltaraBengkulu
SultengKalbarMalut
KaltimPabarSultraRiauNTT
KaltengMaluku
AcehPapua
NURSESSupply and Demand for Nurses
Practicing nurses Desired demand Constrained demand
Desired demandPracticing nurses| 12
<(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
Province MidwifeKaltaraSulbarBabel
GorontaloJogjaPabarKaltimMalutKepri
MalukuJakartaBantenKalteng
SulutSultraSulselPapuaKalbar
SultengJambi
BaliKalsel
BengkuluLampung
RiauNTBNTT
SumselSumbar
JabarAceh
SumutJatim
Jateng
Surplus
MIDWIVESSupply and Demand for Midwives
Practicing doctors Desired demand
Gap
Supply and Demand for Hospital Beds
Capacity Desired demand Constrained demand
HOSPITAL BEDS
Province Hospital bedsJakartaJateng
JabarJatim
SulselSumsel
BaliJambi
LampungBanten
SumbarSumut
RiauKalsel
SultengNTBNTT
SulutBabelAceh
KaltengKalbarSultra
BengkuluMalut
SulbarGorontalo
MalukuKaltara
KepriPabar
KaltimPapuaJogja
| 13
Provincial Gap Summary
Doctors
33
1
Nurses
Deficiency17
17
Worst:Jatim, Jateng, Jabar, Jakarta, Bali, Banten
Worst:Sulsel, Lampung, DKI Jakarta, Jawa Tengah
Hospital beds
Deficiency29
5
Worst:Jakarta, Jateng, Jabar, Jatim
Deficiency
Surplus:Papua Surplus:
Papua, Aceh, Maluku, Kalteng, NTT, Riau, Sultra, Pabar, Kaltim, Malut, Kalbar, Sulteng Bengkulu, Kaltara, Sulut, Kepri, Sulbar
Surplus:Jogja, Papua, Kaltim, Pabar, Kepri
Midwives
No deficiency34
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• 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
CONCLUSIONS RECOMMENDATIONS
| 15
Thank you
| 16