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

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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

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• 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

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Fundamental Dynamics in Indonesia’s Healthcare System

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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

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-

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

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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

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Thank you

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