DISTRICT HEALTH SYSTEM PERFORMANCE ASSESSMENT IN INDONESIA 1... · DISTRICT HEALTH SYSTEM...

M H BPS St ti ti W ld H lth O i tiMoH, BPS Statistics, World Health Organization

DISTRICT HEALTH SYSTEM PERFORMANCE ASSESSMENT IN INDONESIA

11

ASSESSMENT IN INDONESIAresults and future use for benchmarking

DISTRICT HEALTH SYSTEM PERFORMANCE S C S S O CASSESSMENT IN INDONESIA:

results and future use for benchmarking

Why assess district health system performance Why assess district health system performance Indonesia?Indonesia?

WHO Health System Performance Assessment WHO Health System Performance Assessment (HSPA) framework as template.(HSPA) framework as template.

Adaptation of WHO HSPA framework to Indonesia.Adaptation of WHO HSPA framework to Indonesia.

Results for Indonesia HSPA.Results for Indonesia HSPA.

Relating inputs to outcomes: measuring efficiency.Relating inputs to outcomes: measuring efficiency.

Possible uses for benchmarking (Possible uses for benchmarking (work in progresswork in progress).).

22

oss b e uses o be c a g (oss b e uses o be c a g ( o p og esso p og ess))

MoH, BPS, World Health Organization



Why assess district health system performance Indonesia?

WHO Health System Performance Assessment (HSPA) framework as template.

Adaptation of WHO HSPA framework to Indonesia.

Results for Indonesia HSPA.

Relating inputs to outcomes: measuring efficiency.

Possible uses for benchmarking ((work in progresswork in progress).).

33

oss b e uses o be c a g (( o p og esso p og ess))


Why Assess District Health SystemWhy Assess District Health SystemWhy Assess District Health System Why Assess District Health System Performance in Indonesia?Performance in Indonesia?

DecentralizationDecentralization in 2001 redefined role of central in 2001 redefined role of central MoH and districts: created new challenges visMoH and districts: created new challenges vis--àà--vis vis districtdistrict--centre information flowscentre information flows..

MoH currently in MoH currently in national health planning processnational health planning process..

Interest in what existing data can say about districtInterest in what existing data can say about districtInterest in what existing data can say about district Interest in what existing data can say about district performance and what the implications would be for performance and what the implications would be for district benchmarkingdistrict benchmarking..

Who is the Who is the target audiencetarget audience for results of health for results of health system performance assessment?system performance assessment?

44MoH, BPS, World Health Organization

Indonesia: General Background and Context

PostPost--crisis economic recoverycrisis economic recovery continues:continues:

Indonesia: General Background and Context

Country/RegionCountry/Region GNI per capita GNI per capita GDP growthGDP growth(PPP, 2002)(PPP, 2002) (1995(1995--2002)2002)

IndonesiaIndonesia $ 2,990$ 2,990 0.5%0.5%East Asia & PacificEast Asia & Pacific $ 4,160$ 4,160 5.4%5.4%

DecentralizationDecentralization: continuing boundary changes; Number : continuing boundary changes; Number of districts before decentralization: 292. After: 440.of districts before decentralization: 292. After: 440.

I t ti l fI t ti l f ill i d l t lill i d l t lInternational focus on International focus on millennium development goalsmillennium development goals(MDGs): large proportion are health(MDGs): large proportion are health--related indicators related indicators for MDGs (e.g., skilledfor MDGs (e.g., skilled--birth attendance, immunization, birth attendance, immunization, etc.).etc.).

55

etc.).etc.).


Indonesia: Health System Background

National health goalsNational health goals, similar to those identified by WHO HSPA., similar to those identified by WHO HSPA.

and Context

National health goalsNational health goals, similar to those identified by WHO HSPA., similar to those identified by WHO HSPA.

Relatively Relatively lowlow health expenditure per capitahealth expenditure per capita

Relatively Relatively lowlow health expenditure as percent of GDPhealth expenditure as percent of GDPCountry Country Health expenditure Health expenditure Health percent of GDPHealth percent of GDP

(PPP, 2001)(PPP, 2001)BangladeshBangladesh $58$58 3.5%3.5%IndonesiaIndonesia $77$77 2.4%2.4%

$$IndiaIndia $ 80$ 80 5.1%5.1%VietnamVietnam $ 134$ 134 5.1%5.1%PhilippinesPhilippines $ 169$ 169 3.3%3.3%ThailandThailand $ 254$ 254 3.7%3.7%

OutOut--ofof--pocket (OOP) expenditure: 70%; 20% population “insured”.pocket (OOP) expenditure: 70%; 20% population “insured”.Variety of Variety of reformsreforms in last 10 years: to improve staff distribution, in last 10 years: to improve staff distribution, insurance coverage provider performance (quality) etcinsurance coverage provider performance (quality) etc

66

insurance coverage, provider performance (quality), etc.insurance coverage, provider performance (quality), etc.










77



WHO Health System Performance

OO WHO HSPA d fi d h ll l f h l hWHO HSPA d fi d h ll l f h l h

Assessment (HSPA)

OutcomesOutcomes: WHO HSPA defined three overall goals of health : WHO HSPA defined three overall goals of health system:system:

Improving health (level and distribution).Improving health (level and distribution).Enhancing responsiveness to legitimate nonEnhancing responsiveness to legitimate non health expectationshealth expectationsEnhancing responsiveness to legitimate nonEnhancing responsiveness to legitimate non--health expectations health expectations of population (level and distribution).of population (level and distribution).Assuring financial risk protection.Assuring financial risk protection.

Health system efficiencyHealth system efficiency: WHO HSPA framework relates: WHO HSPA framework relatesHealth system efficiencyHealth system efficiency: WHO HSPA framework relates : WHO HSPA framework relates health system outcomes to resource inputs: the goal being to health system outcomes to resource inputs: the goal being to identify the maximum achievable outcomes relative to identify the maximum achievable outcomes relative to resource inputs. resource inputs.

Health system functionsHealth system functions: WHO HSPA framework relates : WHO HSPA framework relates variations in efficiency to differences in the way a health variations in efficiency to differences in the way a health system carries out its four core functions: system carries out its four core functions: provisionprovision, , financingfinancing, , resource generationresource generation, and , and stewardshipstewardship..

88

gg pp


WHO HSPA Framework

Stewardship

FUNCTIONS THE SYSTEM PERFORMS GOALS / OUTCOMES OF THE SYSTEM

p(oversight) Responsiveness

(to people’s non medical

expectations)ResourceI

N Coverage

Health

p )developmentN

P

g

HealthService delivery(provision)

U

TFinancing

(collecting, pooling and purchasing)

Financial risk protection

S Provider Performance


Relating Inputs to Outcomes:

Maximum possible

g pMeasuring Efficiency

me

nt

Same output

CD

oa

l att

ain

m

Less efficientMore efficient

p

A B

Ove

rall

g

More inputs


Inputs to overall goal

Wh A H lth S t P f ?

Monitor and evaluateMonitor and evaluate attainment of health systemattainment of health system

Why Assess Health System Performance?

Monitor and evaluateMonitor and evaluate attainment of health system attainment of health system outcomes outcomes –– and the efficiency of the health system and the efficiency of the health system –– in in a way that allows comparison over time and across a way that allows comparison over time and across systems. systems.

Build an evidence baseBuild an evidence base on the relationship between the on the relationship between the design and organization of the health system and design and organization of the health system and performance, e.g., identification of characteristics of a performance, e.g., identification of characteristics of a

llll f i h lth t (d t i t f h lthf i h lth t (d t i t f h lthwellwell--performing health system (determinants of health performing health system (determinants of health system performance).system performance).

Feedback into the policy debate.Feedback into the policy debate.

Empower publicEmpower public with information relevant to their wellwith information relevant to their well--being.being.










1212



Adaptation of WHO HSPA for Indonesia

WHO HSPA 2000 Framework Indonesia Application

Scope International/National District-level

Outcomes HALE Life expectancyFinancial risk protection Catastrophic expenditureResponsiveness [Responsiveness]Responsiveness [Responsiveness]

Inputs Health expenditure Human resourcesEducation Facilities

IncomeF l d tiFemale educationAccessOOP expenditure

Intermediate Outcomes Coverage indicators Coverage indicatorsg gProvider performance Utilization

Risk Factors Smoking










1414



Health Information System: Indonesian Data Sources

CENSUS 2000.CENSUS 2000.SUSENAS and other household surveys.SUSENAS and other household surveys.MoH inventories: human resources; facilities.MoH inventories: human resources; facilities.National health accounts.National health accounts.Public health expenditure reviewPublic health expenditure reviewPublic health expenditure review.Public health expenditure review.Indonesia Human Development Report 2001, 2004.Indonesia Human Development Report 2001, 2004.

SystemSystem--wide perspective: used wide perspective: used populationpopulation--basedbased data where data where possible; possible; privateprivate-- and publicand public--sectorsector data where available.data where available.


DISTRICT VARIATIONS IN LIFE EXPECTANCY AT BIRTH, 2002

National Estimate: 66.3

Range: 58.8 – 72.5

1717

Below National Estimate

Above National Estimate

Kabupaten KotaProvincial Estimate

INDONESIA: Life Expectancy At Birth 2002

75h

(Yea

rs)

Provincial Estimate

National estimate

2010 Tar get

6570

ctan

cy a

t birt

h60

Life

Exp

ec

at an en ra ah ur at at ra lo a lu ku an at ur g g bi a eh u an ah ah ur ali

ra ta ta

Teng

gara

Bar

am

anta

n Se

lata

Ban

teM

aluk

u U

tar

ulaw

esi T

enga

engg

ara

Tim

ulim

anta

n Ba

raJa

wa

Bara

wes

i Ten

ggar

Gor

onta

lPa

puBe

ngku

lM

aluk

mat

era

Sela

taum

ater

a Ba

raJa

wa

Tim

uLa

mpu

nan

gka

Belitu

nJa

mb

umat

era

Uta

rD

I Ace Ria

ulaw

esi S

elat

aJa

wa

Teng

am

anta

n Te

nga

liman

tan

Tim

u BaSu

law

esi U

tar

DKI

Jak

art

DI Y

ogya

kart

Nus

a Te

Kalim Su

Nus

a Te Ka

Sula

w

Sum Su Ba Su Su

Kalim Ka

l S

Source: Recalculated from IHDR2004

1818

There are significant differences in average life expectancy across provinces;8 provinces exceed the Healthy Indonesia 2010 target of life expectancy of 67.9

Life Expectancy versus Income Deciles and Education Deciles

75 75

707

707

657

Life

exp

ecta

ncy

657

Life

exp

ecta

ncy

606

606

6

1 2 3 4 5 6 7 8 9 10

6

1 2 3 4 5 6 7 8 9 10Income deciles Education deciles

1919

Across districts there is a socio-economic gradient (as expected): on average, districts with higher income and education levels have higher life expectancy.

Life Expectancy and Health Service ProvisionLife Expectancy and Health Service Provision

After Controlling for Income and EducationLife Expectancy and Health Service Provision By District

No Control VariablesLife Expectancy and Health Service Provision By District

n Y

ears

)

After Controlling for Income and Education

n Y

ears

)

No Control Variables

Life

Exp

ecta

ncy

(in

Life

Exp

ecta

ncy

(in

Slope = 1.6 Slope = 1.1L

Health Service Provision IndexNote: The relationship is statistically signif icant

L

Health Service Provision IndexNote: The relationship is statistically significant

p p

From the figure above, districts with higher levels of health service provision appear to have higher life expectancy levels on an average.

The figure above suggests a linkage between health outcomes and health system factors, even after controlling for the effects of socio-economic


e pecta cy e e s o a a e age a te co t o g o t e e ects o soc o eco o cfactors such as income and education.

Catastrophic Expenditure

Reduce other basic expensesOut-of-pocket health

p p

It can mean thathouseholds expenses

Push some house-holds into povertyForgo health

expenditures defined as more than 40% of household non-subsistence spending

households

gservices and suffer illness

spending

% households % households % households

3.0

4.0

ds 6,000,000

8,000,000

3.0

4.0

ds 6,000,000

8,000,000

3.0

4.0

ds 6,000,000

8,000,000

% households with catastrophic

% householdsimpoverished

% householdsnot seeking care

0.0

1.0

2.0

1999 2000 2001

% H

ouse

hold

0

2,000,000

4,000,000

, ,

0.0

1.0

2.0

1999 2000 2001

% H

ouse

hold

0

2,000,000

4,000,000

, ,

0.0

1.0

2.0

1999 2000 2001

% H

ouse

hold

0

2,000,000

4,000,000

, ,

2222

1999 2000 2001 1999 2000 2001 1999 2000 2001

Catastrophic Expenditureym

ents Kabupaten Kota

Provincial Estimate

INDONESIA: Catastrophic Health Payments6

810

tast

hrop

ic Pa

y

National estimate

24

6f H

Hs

with

Cat

0Pr

opor

tion

o f

Uta

raPa

pua

enga

hBa

nten Ba

ligg

ara

Tim

urel

atan

Ria

uel

atan

elat

anBa

rat

Mal

uku

Bara

tJa

mbi

Uta

rael

itung

enga

hTi

mur

Uta

raBa

rat

Bara

tm

pung

akar

tang

kulu

akar

taTi

mur

enga

hon

talo

Mal

uku P

Kalim

anta

n Te B

Sula

wes

i Ten

gKa

liman

tan

Sum

ater

a S e

Kalim

anta

n Se

Sula

wes

i Se

Kalim

anta

n MJa

wa J

Sum

ater

a B

angk

a B e

Sul

awes

i Te

usa

Teng

gara

Su

law

esi

Sum

ater

a us

a Te

ngga

ra

Lam

DKI

Ja

Ben

DI Y

ogya

Jaw

a Ja

wa

T eG

oro

2323

Nu Nu

Source: Susenas 2001

Catastrophic ExpenditureIndicators for the ten provinces with lowest Indicators for the ten provinces with lowest

catastrophic expenditurescatastrophic expenditures

p p

Percent of households facing catastrophic expenditureby province

5

Combined life expectancyby province

72

2

3

4

5

Perc

ent

63

66

69

72

Year

s

National AverageNational Average

0

1

Mal

uku

Uta

ra

Papu

a

liman

tan

Teng

ah

Bant

en Bali

ulaw

esi

engg

ara

liman

tan

Tim

ur

umat

era

Sela

tan

Ria

u

liman

tan

Sela

tan

57

60

Mal

uku

Uta

ra

Papu

a

liman

tan

Teng

ah

Bant

en Bali

Sula

wes

ien

ggar

a

liman

tan

Tim

ur

umat

era

Sela

tan

Ria

u

liman

tan

Sela

tan

Kal T S T e Kal T Su S

Kal S Ka

T S Te KaT S S

KaS

• The ten provinces with lowest levels of catastrophic expenditures have been presented here• Only four of the provinces that perform well on catastrophic expenditure have higher than average life

t hil i i h lif t i id bl b l th ti l

2424

expectancy, while six provinces have life expectancies considerably below the national average• This means that catastrophic expenditures cannot be looked at (as an outcome) in isolation – thereby having implications for benchmarking

Catastrophic Expenditurep p

Predicted effects of changes in poverty, health

PP If i d b 1% If i d b 1% 27 00027 000

insurance, and levels of household health spending, on catastrophic expenditure (2001):

Poverty.Poverty. If poverty increased by 1%, If poverty increased by 1%, 27,00027,000 more more people would face catastrophic expenditures.people would face catastrophic expenditures.

InsuranceInsurance If insurance coverage increased by If insurance coverage increased by Insurance.Insurance. If insurance coverage increased by If insurance coverage increased by 1%, 1%, 83,00083,000 more people would be protected from more people would be protected from catastrophic expenditurescatastrophic expenditures

Health Spending.Health Spending. If households spent 1% more If households spent 1% more of their budget on health, of their budget on health, 1.5 million1.5 million more more people would face catastrophic expenditurespeople would face catastrophic expenditures

2525

people would face catastrophic expenditurespeople would face catastrophic expenditures


Catastrophic ExpenditureFactors that protect or increase risk of catastrophic spending

Risk of facing catastrophic expenditure

Factors that protect or increase risk of catastrophic spending

g p p

-34%

-29%

-100% -50% 0% 50% 100% 150% 200% 250% 300% 350%Increase riskProtect

Company

Others

-3%

-10%

-19%

-27%

MaleEdu

UrbanAskes/JamsostekCompany

12%

-1%3%

20%22%

MaleHhsize

Health cardJPKM

Exppc 22%

33%43%

98%154%

Health fund

Senior memberChild

Exppc

2626

154%

305%Use public

Use private

Health System ResponsivenessNational Level Results

Evaluation of health systems responsiveness by users

h th

e Ambulatory Inpatient

20

25

30d

expe

rienc

e w

ithce

: MC

SS

200

0)

5

10

15

sers

repo

rting

ba

th s

yste

m (S

our c

0

Prom

ptAt

tent

ion

Dig

nity

Com

mun

icat

ion

Auto

nom

y

Con

fiden

tiality

Cho

ice

Basi

cAm

enitie

s

Acce

ss to

supp

ort

Perc

ent o

f us

heal

• Basic amenities in health facilities, choice of health care provider, and patient autonomy in decision making appear to be the three main concerns when considering the quality of health services in Indonesia• Timely attention is a bigger problem in ambulatory health services than in inpatient care

C C

2828

• Choice and dignity are significantly larger concerns in inpatient care than in ambulatory services


D t V i ti b P iDoctors: Variation by ProvinceDoctors per 100,000 population By Province �

50

60

70

80 Doctors per 10(Source: M

O

Province DI Yogyakarta

2010 National Target

10

20

30

40

50 00,000 populationH

Inventory, 2001)


0

Below National Average

Above National Average

• National average: 15.5 doctors per 100,000 population.• Provincial variation: 7.0 (Maluku) - 70.8 (DKI Jakarta).

3030

• Doctors form 7% of the total health system workforce, and 15% of all health professionals in Indonesia.

Doctors: Variation by Province and District

Variation across districts and provincesINDONESIA: Doctors per 100000 population

300

pula

tion

Kabupaten KotaProvincial Average

100

200

per 1

0000

0 po

p

N ati onal Average2010 Tar get

0D

octo

rs p

aluk

uU

tara

Bara

tpu

ngTi

mur

ntal

oBa

rat

ante

nap

uagk

ulu

ngah

Aceh

Bara

ttu

ngat

anTi

mur

Ria

uam

biat

anga

rang

ahng

ahBa

rat

atan

Uta

raTi

mur

Uta

ra Bali

karta

karta

Ma

Mal

uku

Usa

Ten

ggar

a B

Lam

psa

Ten

ggar

a Ti

Gor

onKa

liman

tan

BB

a PaBe

ngKa

liman

tan

Ten

DI A

Jaw

a B

Bang

ka B

elit

Kalim

anta

n Se

lJa

wa

Ti R JaSu

mat

era

Sel

Sula

wes

i Ten

ggJa

wa

Ten

Sula

wes

i Ten

Sum

ater

a B

Sula

wes

i Sel

Sum

ater

a U

Kalim

anta

n T

Sula

wes

i U

DI Y

ogya

kD

KI J

ak

3131

Nus

Nus K K S

Source: MOH Inventory 2001

DISTRICT VARIATION IN DOCTORS PER 100,000 POPULATION

Source MOH Inventory 2001Source MOH Inventory 2001

National Average: 15 5National Average: 15.5

Range: 1.6 – 285.9

3232

Below National Average (15.5)

Above National Average (15.5)

Missing Data

Doctors: Public vs. PrivateDoctors: Public vs. Private

Distribution of doctors by sectorS MOH I t 2001

Doctors per 100,000 populationBy Sector and Province

Public (Government + Military) Private & State Owned Corp.


27%

Government

Military40

50

60

70

80

Doctors per 100,00(S

ource: MO

H Inve

69%

4%

Military

Private & State Owned Corp.

0

10

20

30

00 populationentory, 2001)

• According to the inventory, 69% of all doctors work for the government, whereas 27% of doctors are in the private sector and state-owned corporations. The military accounts for the remaining 4% of doctors.• Three provinces have not reported any doctors working in the private sector

3333

• Three provinces have not reported any doctors working in the private sector -Kalimantan Tengah, Gorontalo, and Maluku Utara.• DKI Jakarta has 38.4% of doctors working in the private sector - it is the province with the highest ratio.

Midwives: Variation by ProvinceMidwives: Variation by ProvinceMidwives per 100,000 populationBy Province �


60

80

100

120 Midw

ives per 10(Source: M

OH


Province Jawa Tengah

0

20

40

60

00,000 population Inventory, 2001)



• National average: 32.3 midwives per 100,000 population• Provincial variation: 17.5 (Maluku) - 102.6 (DI Aceh)• Midwives form 13% of the total health workforce and 28% of all health professionals in Indonesia

3434

p

Midwives: Variation by Province and Districts

Kabupaten Kota

Variation across districts and provincesINDONESIA: Midwives per 100000 population


200

250

popu

latio

n

Provincial Average

2010 Tar get

100

150

2pe

r 100

000

p

N ati onal Average

050

Mid

wive

s

uku

nten arat

talo

mur

arat

arta

ung

atan ara

gah

arta

ung

arat

Ria

uat

an mur Bali

mbi

gara

mur ara

ara

arat

pua

gah

atan gah

kulu

ceh

Mal

uBa

nJa

wa

BaG

oron

tJa

wa

Tim

Teng

gara

Ba

DKI

Jak

aLa

mpu

Sula

wes

i Sel

aSu

law

esi U

tJa

wa

Ten g

DI Y

ogya

kaBa

ngka

Bel

ituKa

liman

tan

Ba R

umat

era

Sela

Teng

gara

Tim B

Jam

law

esi T

engg

Kalim

anta

n Ti

mSu

mat

era

Ut

Mal

uku

Ut

Sum

ater

a B a Pa

pim

anta

n Te

ngim

anta

n Se

laSu

law

esi T

eng

Beng

kD

I Ac

3535

Nus

a S K Su

Nus

a Sul K S

Kali

Kal S


DISTRICT VARIATION IN MIDWIVES PER 100,000 POPULATION



Range: 2.1 – 233

Below National Average (32 2) Missing Data

3636



Missing Data

Human Resources and Coverage

Skilled Birth Attendance and MidwivesSource: MOH Inventory 2001, Susenas 2001

Skilled Birth Attendance and Physicians, Nurses and Midwives Source: MOH Inventory 2001, Susenas 2001

40

5060

7080

Dis

tric

ts

Below 80% Coverage 5060708090

Dis

tric

ts

Below 80% Coverage

010

203040

Less than 18 18 - 30 31 - 51 52+

Num

ber o

f

Above 80% Coverage

010203040

Less than 58 58 - 96 97 - 179 180+

Num

ber o

f

Above 80% Coverage

Less than 18 18 30 31 51 52

Midwives per 100,000 population Physicians, Nurses, and Midwives per 100,000

• A higher concentration of midwives increases the likelihood for a district to achieve greater than 80% skilled birth attendance (MDG target)attendance (MDG target)

• However, the relationship is not very clear for the highest category of midwives – the number of districts achieving more than 80% coverage is less for the highest category (52+) than for the second highest (31 – 51)

• Though when we include physicians and nurses together with midwives the relationship between higher coverage and higher concentration of human resources is stronger

3737

g g


Hospital Beds: Variation by Province

Hospital Beds per 100,000 populationBy Province

Ho

Province Kalimantan Timur

6080100120140160180

ospital Beds per 100

(Source: M

OH

Inve

0204060 ,000 population

ntory, 2001)



• National average: 62 hospital beds per 100,000 population• Provincial variation: 26 (Lampung) to 166 (DKI Jakarta)

3939

Provincial variation: 26 (Lampung) to 166 (DKI Jakarta)


DISTRICT VARIATION IN HOSPITAL BEDS PER 100,000 POPULATION



Range: 0 - 1046

Below National Average (62 6) Missing Data

4040



Missing Data

Hospital Beds: Public vs. Private

Distribution of hospital beds by sector

Hospital Beds per 100,000 populationOwnership by Province

180 (S

Public (Including Military) Private & Corporate

Distribution of hospital beds by sectorSource: MOH Inventory 2001

37%

54%

Government

Military 60

80

100

120

140

160

Hospital B

eds per S

ource: MO

H Invento

9%

Military

Private & State Owned Corp.

0

20

40

60 100,000ory, 2001)

• 37% of all hospital beds are in the private sector and state-owned corporations, while the military accounts for 9% and government-run hospitals for 54%.• Jakarta and Yogyakarta are the only two provinces with 50% or more beds in the private sector

4141

the private sector



WHO HSPA 2000 FrameworkWHO HSPA 2000 Framework Indonesia ApplicationIndonesia Application

ScopeScope International/NationalInternational/National DistrictDistrict--levellevel

OutcomesOutcomes HALEHALE Life expectancyLife expectancyFinancial risk protectionFinancial risk protection Catastrophic expenditureCatastrophic expenditureResponsivenessResponsiveness [Responsiveness][Responsiveness]ResponsivenessResponsiveness [Responsiveness][Responsiveness]

InputsInputs Health expenditureHealth expenditure Human resourcesHuman resourcesEducationEducation FacilitiesFacilities

IncomeIncomeF l d tiF l d tiFemale educationFemale educationAccessAccessOOP expenditure

Intermediate Outcomes Intermediate Outcomes Coverage indicatorsCoverage indicators Coverage indicatorsgg gProvider performanceProvider performance UtilizationUtilization

Risk FactorsRisk Factors SmokingSmoking


Coverage: Iodized Salt

(%) Kabupaten Kota

Provincial Average

Variation across districts and provincesINDONESIA: Iodized salt content (%)

N ati onal Average

080

100

ate

iodi

ne in

sal

t Provincial Average

020

4060

lds

with

ade

qua

0H

ouse

hol

ggar

a Ba

rat

ggar

a Ti

mur Bali

wes

i Sel

atan

Bant

enD

KI J

akar

taaw

a Te

ngah

Jaw

a Ba

rat

si Te

ngga

raJa

wa

Tim

urYo

gyak

arta

anta

n Ba

rat

Lam

pung

Ria

uat

era

Uta

raw

esi T

enga

her

a Se

lata

nat

era

Bara

tPa

pua

gka

Belitu

ngJa

mbi

tan

Sela

tan

anta

n Ti

mur

Gor

onta

lota

n Te

ngah

awes

i Uta

raBe

ngku

lu

Nus

a Te

ngN

usa

Teng

Sula

w DJa

Sula

wes J

DI Y

Kalim

a

Sum

aSu

law

Sum

ate

Sum

Ban g

Kalim

anKa

lima

Kalim

an Sul

a

Source: Iodized Salt Survey 2001


DISTRICT VARIATION IN ADEQUATE IODIZED SALT CONTENT

Source Iodized Salt Survey 2001

National Average: 64.3%National Average: 64.3%

Range: 8.5 – 100%

Below National Average Missing Data

4444


Coverage: Skilled Birth Attendance


Variation across districts and provincesINDONESIA: Skilled birth attendance

N ati onal Average

2010 T ar get

8010

0nd

ance

(%)

Provincial Average

N ati onal Average

2040

60Sk

illed

birth

atte

nS

gara

Tim

ursi

Teng

gara

ggar

a B

arat

aluk

u U

tara

anta

n Ba

rat

Gor

onta

loJa

wa

Bara

tw

esi T

enga

hw

esi S

elat

anPa

pua

Mal

uku

Bant

enJa

mbi

tan

Sela

tan

Lam

pung

wa

Teng

ahta

n Te

ngah

ka B

elitu

ngJa

wa

Tim

urBe

ngku

luer

a Se

lata

nR

iau

anta

n Ti

mur

ater

a Ba

rat

Yogy

akar

taat

era

Uta

raaw

esi U

tara Bali

DKI

Jak

arta

Nus

a Te

ngSu

law

esN

usa

Teng M

aKa

lima J

Sula

wSu

law

Kal

iman

t

Jaw

Kalim

ant

Bang

J

Sum

ate

Kalim

aSu

ma

DI Y

Sum

aSu

la D




DISTRICT VARIATION IN SKILLED BIRTH ATTENDANCEATTENDANCESource Susenas 2001

National Average: 65.8%

Range: 16.5 – 100%

4646



Missing Data

Coverage: Immunization


Variation across districts and provincesINDONESIA: Complete immunization

2010 Tar get

6080

100

niza

tion

(%)

g

N ati onal Average

020

406

Com

plet

e im

mun

0C

ater

a U

tara

DI A

ceh

ggar

a Ba

rat

Jaw

a Ba

rat

Jam

bi

ater

a Ba

rat

Ria

uan

tan

Bara

tw

esi S

elat

anta

n Se

lata

nD

KI J

akar

ta

Papu

aM

aluk

uer

a Se

lata

nBe

ngku

luta

n Te

ngah

Lam

pung

Jaw

a Ti

mur

si T

engg

ara

awa

Teng

ahw

esi T

enga

hgg

ara

Tim

uran

tan

Tim

ur

awes

i Uta

ra Bali

Yogy

akar

ta

Sum

a

Nus

a Te

ngJ

Sum

Kalim

aSu

law

Kalim

ant D

Sum

ate

Kalim

anat J

Sula

wes Ja

Sula

wN

usa

Teng

Kalim

a

Sula

DI Y



Ambulatory Utilization Based On NeedINDONESIA: Ambulatory care utilization (%)

ed (%

) Kabupaten KotaProvincial Average

Variation across districts and provincesINDONESIA: Ambulatory care utilization (%)

N ati onal Average

4060

80on

bas

ed o

n ne

e0

20bu

lato

ry u

tiliza

tio

u h a u n n at at bi g n h a n o a at a u a r ur h at at a g a li

Amb

Mal

uku

Sula

wes

i Ten

gah

law

esi T

engg

ara

Ria

uim

anta

n Se

lata

nSu

law

esi S

elat

anKa

liman

tan

Bara

Kalim

anta

n Ba

raJa

mb

Lam

pung

umat

era

Sela

tan

iman

tan

Teng

ahSu

law

esi U

tara

Ban

ten

Gor

onta

loM

aluk

u U

tara

Jaw

a Ba

raD

KI J

akar

taBe

ngku

luSu

mat

era

Uta

raJa

wa

Tim

uTe

ngga

ra T

imu

Jaw

a Te

ngah

Sum

ater

a Ba

raTe

ngga

ra B

ara

Papu

aBa

ngka

Bel

itung

DI Y

ogya

karta Ba

SSu

l

Kal S K K Su Kal S

Nus

a

Nus

a B


4949

From the analysis of SUSENAS 2001, Bali province has the highest ambulatory utilization, 65.8%. Maluku has the lowest with 20.4% of visits. There are 12 provinces out of 29 provinces above the national average, 50.3%.

DISTRICT VARIATION IN AMBULATORY UTILIZATIONSource: Susenas 2001

National Average: 50.3%

Range: 16.5 – 100%

5050



Missing Data






IncomeF l d tiFemale educationAccess OOP expenditure

Intermediate Outcomes Coverage indicators Coverage indicatorsProvider performance Utilization



Risk Factor: Smokingve

ry d

ay Kabupaten KotaProvincial Estimate

INDONESIA: Smoking Prevalence 2003

National estimate

2030

who

sm

oke

ev10

2op

ulat

ion

10+

0ro

porti

on o

f Po

Tim

ur Bali

Mal

uku

Uta

raPa

pua

elat

anak

arta

Ace

hon

talo

Tim

urel

atan

akar

taU

tara

ggar

aen

gah

enga

hBa

rat

Uta

rael

atan

Jam

bien

gah

Tim

urBa

nten

Bara

tm

pung

elitu

ngBa

rat

Bara

tR

iau

ngku

lu

Pr

usa

Teng

gara

MM

aluk

u PKa

liman

tan

SeD

I Yog

ya DI

Gor

oK

alim

anta

n Su

law

esi S

eD

KI J

aSu

mat

era

Sula

wes

i Ten

gKa

liman

tan

TeJa

wa

TeK

alim

anta

n Su

law

esi

Sum

ater

a S e J

Sula

wes

i Te

Jaw

a Bus

a Te

ngga

ra

Lam

Bang

ka B

eSu

mat

era

Jaw

a

Ben

5252

Nu Nu










5353



Inputs vs. Outcomes: Measuring Efficiency

2

WHO HSPA: Outcomes vs. inputs across countries

Inputs vs. Outcomes: Measuring Efficiency

01

dex

BahamasOman

-2-1

Out

put i

nd-3

-

-2 0 2 4Input index

WHO HSPA: Relating outcomes to inputs across countries. Some countries achieve relatively high health outcomes even

ith l ti l l i t l l ( O B h )

p

5454

with relatively low input levels (e.g., Oman vs. Bahamas).


Inputs vs. Outcomes: Measuring EfficiencyVery Preliminary Findings

Indonesia HSPA: Outcomes vs. inputs across districts

Very Preliminary Findings

24

Magelang (Jawa Tengah)Kulon Progo (DI Yogyakarta)

INPUT INDEX• Permanent Income

• Female Education

OUTPUT INDEX• Complete Immunization

• Skilled Birth Attendance

20

Out

put i

ndex

• Female Education

• Nurses per 100,000

• Out-of-pocket expenditure

• Access to health facilities

• Skilled Birth Attendance

• Iodized Salt Content

• Catastrophic Expenditure

• Life Expectancy

-4-

-4 -2 0 2 4 6

Indonesia HSPA: Relating outcomes to inputs across districts. Some districts have achieve relatively high health system outcomes

ith l ti l l i t l l U f l f b h ki

4 2 0 2 4 6Input index

5555

even with relatively low input levels. Useful for benchmarking.



4

Indonesia HSPA: Outcomes vs. inputs across districts

Madiun (Jawa Timur)


2de

x

W onogiri (Jawa Tengah)

Kulon Progo (DI Yogyakarta)

Soppeng (Sulawesi Selatan)

Madiun (Jawa Timur)Blitar (Jawa Timur)

-20

Out

put i

n d

J i J (P )

Manokwari (Papua)

-4

-4 -2 0 2 4 6

Jayawi Jaya (Papua)

Input index

Indonesia HSPA: This shows one way to characterize the “frontier”. The frontier reflects the maximum achievable outcomes for given input l l Di tri t n r l t th fr nti r r r l ti l high p rf rm r

5656

levels. Districts on – or close to – the frontier are relatively high performers.



4

Deciles of input index


2pu

t ind

ex-2

0D

istri

butio

n of

out

p-4

1 2 3 4 5 6 7 8 9 10

Indonesia HSPA: This is another way to see the relationship between inputand outputs: the x-axis shows deciles of inputs; the y-axis shows the distributionof outputs within each input decile. As can be seen, there is a positive gradientwith diminishing returns

5757

with diminishing returns.









Possible uses for benchmarking (work in progress).

5858

oss b e uses o be c a g ( o p og ess)


Implications for BenchmarkingImplications for Benchmarking

HSPA framework can be used for setting benchmarks.HSPA framework can be used for setting benchmarks.

Benchmarks for input indicators could be in terms of targets for Benchmarks for input indicators could be in terms of targets for h lth k h lth f iliti d ti l tt i t th lth k h lth f iliti d ti l tt i t thealth workers, health facilities, educational attainment, etc.health workers, health facilities, educational attainment, etc.

Benchmarks may be defined in terms of attainment of health Benchmarks may be defined in terms of attainment of health system outcomes (e g attainment of life expectancy ofsystem outcomes (e g attainment of life expectancy of xxsystem outcomes (e.g., attainment of life expectancy of system outcomes (e.g., attainment of life expectancy of xxyears).years).

Benchmarks for outcomes could be based on attainment of Benchmarks for outcomes could be based on attainment of b tb t f i di t i t t diff t i t l lf i di t i t t diff t i t l lbestbest--performing districts at different input levels.performing districts at different input levels.


Implications for BenchmarkingOther examples of benchmarking frameworks.Other examples of benchmarking frameworks.

Implications for Benchmarking

UN Millennium Development Goals (MDGs)UN Millennium Development Goals (MDGs)::TargetTarget IndicatorsIndicators

Reduce byReduce by twotwo--thirdsthirds UnderUnder--5 mortality rate5 mortality rateReduce by Reduce by twotwo thirdsthirds UnderUnder 5 mortality rate5 mortality rateunderunder--5 mortality rate 5 mortality rate Infant mortality rateInfant mortality rate(1990(1990--2015)2015) Proportion of 1Proportion of 1--year old year old

children immunized against children immunized against measlesmeasles

Reduce by Reduce by threethree--quartersquarters Maternal mortality ratioMaternal mortality ratiothe maternalthe maternal--mortality ratiomortality ratio Proportion of birthsProportion of births(1990(1990--2015)2015) attended by skilled attended by skilled

personnelpersonnel

UNDP Human Development Index (HDI)UNDP Human Development Index (HDI): Composite : Composite index of health, education, and income. No specific index of health, education, and income. No specific targets; can be used to monitor improvements over targets; can be used to monitor improvements over time.time.

6060

time.time.



Other examples of benchmarking frameworks.Other examples of benchmarking frameworks.


gg

Healthy Indonesia 2010 and Minimum Service StandardsHealthy Indonesia 2010 and Minimum Service Standards::IndicatorsIndicators TargetTarget

Percent coverage of births attended Percent coverage of births attended by trained staffby trained staff 90%90%Percent of contraceptive usersPercent of contraceptive users 70%70%P t f ill ith i l hildP t f ill ith i l hildPercent of villages with universal child Percent of villages with universal child immunizationimmunization 100%100%Percent coverage for Percent coverage for puskesmaspuskesmas visits (HI2010) /visits (HI2010) /

Percent coverage of outpatient visitsPercent coverage of outpatient visits (MSS)(MSS) 15%15%g pg p ( )( )Percent of subPercent of sub--districts free of severe districts free of severe malnutritionmalnutrition 80%80%


Panel Discussion:Panel Discussion: How to Choose Benchmarks?

What indicators should be chosen?What indicators should be chosen?

How should targets be set for the chosenHow should targets be set for the chosenHow should targets be set for the chosen How should targets be set for the chosen indicators?indicators?

Is measurement of chosen indicator feasible? Is Is measurement of chosen indicator feasible? Is it valid and reliable?it valid and reliable?

Can the indicator be measured reliably over Can the indicator be measured reliably over time?time?time?time?



A h i di liA h i di li i ?i ?Are the indicators policyAre the indicators policy--reactive?reactive?

Should benchmarks be chosen for input as well Should benchmarks be chosen for input as well as outcome indicators?as outcome indicators?as outcome indicators?as outcome indicators?

Are districtAre district--representative data available for the representative data available for the chosen indicators?chosen indicators?chosen indicators?chosen indicators?

What are the implications for future survey What are the implications for future survey design?design?

Are resources available for data collection? Are resources available for data collection? Statistical capacity for analysis?Statistical capacity for analysis?



How to deal with problems relating to data How to deal with problems relating to data quality and measurement error?quality and measurement error?

Sh ld th b b h k fSh ld th b b h k f h lthh lthShould there be benchmarks for nonShould there be benchmarks for non--health health related aspects of health system, e.g., related aspects of health system, e.g., responsiveness, patient satisfaction, waiting responsiveness, patient satisfaction, waiting time etc ?time etc ?time, etc.?time, etc.?

Benchmarks related to quality of care? Medical Benchmarks related to quality of care? Medical error rates? Compliance with protocols?error rates? Compliance with protocols?error rates? Compliance with protocols?error rates? Compliance with protocols?

How many indicators? What is the marginal How many indicators? What is the marginal information content of an indicator?information content of an indicator?


Key MessagesKey Messages

Various frameworks for benchmarking, including Various frameworks for benchmarking, including WHO HSPAWHO HSPA

Benchmarks may include input, output, Benchmarks may include input, output, outcome non healthoutcome non health related aspects of healthrelated aspects of healthoutcome, non healthoutcome, non health--related aspects of health related aspects of health system, quality of caresystem, quality of care

Input vs Output: Measure EfficiencyInput vs Output: Measure EfficiencyInput vs Output: Measure EfficiencyInput vs Output: Measure Efficiency

Indicators selection and target settingIndicators selection and target setting

Problems related to data availability and qualityProblems related to data availability and qualityProblems related to data availability and quality Problems related to data availability and quality (HIS)(HIS)


THANK YOUTHANK YOU

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