health sector pers: ukraine case study fiscal, efficiency, and equity issues in the health sector...

Health Sector PERs: Ukraine Health Sector PERs: Ukraine Case StudyCase Study

Fiscal, Efficiency, and Equity Fiscal, Efficiency, and Equity Issues in the Health SectorIssues in the Health Sector

Adam Leive

Human Development Network

Outline

• Objectives of PER• Health outcomes and demographics• Description of health financing and delivery system• Background on intergovernmental fiscal transfers and

Ministry of Health norms in Ukraine• Analysis of efficiency and equity of health sector

• Conclusions and Recommendations

Core Objectives – Fiscal Issues and Health Sector

• Examine the intergovernmental fiscal and administrative issues affecting efficiency and equity of public spending in the health sector.

• Identify other social/economic trends affecting the efficiency of public spending in the sector

• Link efficiency issues to quality of service delivered, performance, and equity.

• To provide recommendations to improve the financing, efficiency, and equity of spending of the health sector.

Outline


Ministry of Health norms in Ukraine• Analysis of efficiency and equity of health sector• Conclusions and Recommendations

Health Outcomes – Low Life Expectancy• Life expectancy has not rebounded as quickly as other ECA

countries and was higher 40 years ago

High-Income OECD

EU

ECA

Ukraine

Russia

65

70

75

80

Life

exp

ect

an

cy a

t bir

th

1960 1970 1980 1990 2000Year

Source: World Development Indicators

TRENDS IN LIFE EXPECTANCY, 1960-2004UKRAINE VS COMPARATOR COUNTRIES/REGIONS

Health Outcomes – Differences in Life Expectancy Between Males and Females

• Life expectancy is 12 years higher for females than for males, on average

Ukraine

60

65

70

75

80

Life e

xpecta

ncy a

t bir

th

100 250 1000 2500 1000025000GDP per capita

Source: World Development IndicatorsNote: GDP per capita in constant 2000 US$; Log scale

LIFE EXPECTANCY VS INCOME, 2004MALES

Ukraine

65

70

75

80

85

Life e

xpecta

ncy a

t bir

th

100 250 1000 2500 1000025000GDP per capita

Source: World Development IndicatorsNote: GDP per capita in constant 2000 US$; Log scale

LIFE EXPECTANCY VS INCOME, 2004FEMALES

Demographics – Aging Population

Structure

2005

6 4 2 0 2 4 6

0-45-9

10-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-74

75+

Percent

Males Females

2025

6 4 2 0 2 4 6

0-45-9

10-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-74

75+

Percent

FemalesMales

Source: World Bank staff calculations

Outline



International Comparisons of Total and Public Health Spending

Ukraine

05

10

15

Tota

l health e

xpenditure

as s

hare

of G

DP

100 250 1000 2500 1000025000GDP per capita

HEALTH EXPENDITURE VS INCOME

Ukraine

05

10

15

Public h

ealth e

xpenditure

as s

hare

of G

DP

100 250 1000 2500 1000025000GDP per capita

PUBLIC HEALTH EXPENDITURE VS INCOME

Source: World Development Indicators & WHONote: Log scale

Country/Region Total health spending per capita (US $)

Total health spending (% GDP)

Public health spending (% GDP)

Ukraine 90 6.5 3.7

ECA 318 6.4 3.9

High-income OECD 3,365 9.3 6.7

Public Health Expenditure by Economic and Functional Classification

• Wages and other current expenditures constitute the majority of public health spending (usually over 90%)

• Hospitals capture a large share of spending while polyclinics and preventive facilities receive less

Government Health Expenditure by Functional Classification, 2006

Polyclinics, ambulatories, first-

aid, and emergency

14%

Other health protection facilities

10%

Health protection research

1%

Hospitals and sanatoriums

70%

Preventive and anti-pandemic institutions and

activities5%

Health Care Delivery

• The Ukrainian health system has evolved from a centrally-planned Soviet-style model to one where responsibilities have been delegated to lower tiers of government

• Most facilities are owned and managed at the regional (oblast) and sub-regional (rayon) levels

• There is negligible participation by the private sector in service delivery

• Ukraine has slightly fewer physicians per 100,000 (301) than in EU (348) and CIS (378)

• However, it has about the same hospital beds per 100,000 (872) as CIS (866) and more than EU (591)

• Ukraine also has a similar level of hospitals per 100,000 (5.6) as CIS (5.9) but more than EU (3.1)

Outline

• Objectives of PER• Health outcomes and demographics• Description of health financing and delivery system• Background on intergovernmental fiscal transfers

and Ministry of Health norms in Ukraine• Analysis of efficiency and equity of health sector• Discussion of Policy Reforms and Recommendations

Intergovernmental Fiscal Issues

• The budget reform in 2001 radically changed the intergovernmental finances in the country

• Funding from the central government for health is part of a horizontal equalization formula

• In Ukraine the most basic shape of the equalization formula for the allocation to a local government is the following:

where Ti is the transfer to local government i; Vi are the estimated expenditure needs for local government i and Di its estimated revenue capacity

• The estimated expenditure needs for health are calculated based on population size

)( iii DVT

Ministry of Health (MoH) “Norms”• Despite decentralization in service delivery there remains extensive

regulation by the center • The MoH norms (mandatory guidelines) dictate to all health facilities across

the country how they should allocate resources (particularly staffing, but also others) based mostly on bed size or another indicator

• Facilities prepare budgets fulfilling the “norms”, which leads to current spending over 90% of total spending in most cases and little autonomy is left to local governments

Examples of Norms for the functioning of health facilities1 Infection disease doctor per 25 beds in outpatient aid in Rayon hospitals; 1 Surgeon per 20 beds (adults) and 15 beds (children) in Rayon hospitals 1 Nurse (gynecology) per 25 beds in Rayon hospitals; 1 Nurse per 20 beds in Children’s hospitals1 Dietarian nurse per 500 portions served a day 1 Obstetrician-gynecologist per 20 beds in Rayon hospitals; 1 post per 15 beds in

District hospitals; 0.5 Statisticians per 20 posts of doctors in polyclinics 1 Cook per 30 beds in a health facility1 Cleaner per 500 square meters (0.5 per each 250 square meters) Source: Extracted from Order No. 33 Ministry of Health

The Inefficient Process of Budgeting by Input Norms Dictated from the Fiscal Framework

Ministry of Finance

Rayon

Budget Allocation Through:(1) Shared Revenues (PIT, Land)(2) Equalization Transfer (population- based for health)(3) Local Taxes

Mismatch

Input Norms to form health facility budgets, which constrain budget flexibility (Order No 33)

Budget Formation: Prepare budgets fulfilling the “norms”, which lead to extremely high current spending

Health Facility

“Norms” fulfillment + Large network of facilities = non-flexible local budgets crowded by high recurrent spending little spending autonomy is left to local governments.

Ministry of Health

Local Budget Submission complying with Norms

Outline



The Effect of Intergovernmental Fiscal Transfers on Public Health Expenditure

• In 2001, public health spending varied across oblasts and was correlated with income

• Despite a major change in the way transfers are allocated, differences in absolute public health spending per capita across oblasts remain

AR Crimea

CherkasyChernihiv

Chernivtsi

DnipropetrovskDonetsk

Ivano-Frankivsk

KharkivKherson

Khmelnytsky

Kirovohrad

Kyiv

Kyiv city

Luhansk

LvivMykolayiv

Odesa

PoltavaRivne

Sevastopol city

Sumy

Ternopil

VinnytisaVolyn

Zakarpattia

Zaporizhzhia

Zhytomyr

80

100

120

140

160

180

Obla

st p

ub

lic h

ea

lth e

xpen

ditu

re p

er

capita

(h

ryvn

as)

3000 3500 4000 4500 5000Oblast GDP per capita (hryvnas)

Source: Ministry of Finance; State Treasury; and Bank Staff estimations

HEALTH EXPENDITURE VS INCOME BY OBLAST, 2001

Labor vs. Capital Across Oblasts• Personnel highly correlated with public health exp. across oblasts

while there is little correlation with public expenditure and the number of health facilities

• This is most likely due to rigidities created by health norms which specify strict requirements for staffing levels and must be followed in order to receive budgetary allocations at the oblast and rayon levels

050000

100000

Obla

st to

tal health p

ersonnel

0 200000 400000 600000 800000Oblast public health expenditure (hryvnas)

HEALTH PERSONNEL VS EXPENDITURE

0500

1000

1500

Obla

st to

tal num

ber o

f health facilitie

s

0 200000 400000 600000 800000Oblast public health expenditure (hryvnas)

HEALTH FACILITIES VS EXPENDITURE

Source: Ministry of Finance; State Treasury; and Bank Staff estimations Health facilities include general hospitals, polyclinics, medical assistance, and obstetric centers

Variation in Average Length of Stay (ALOS) Across Oblasts

• ALOS in Ukraine was about 15 days, higher than the CIS average of 13 days and EU average of 9.

• ALOS also varies widely across oblasts (see Annex 2 for probit regression)

• ALOS is higher in regions with lower inpatient utilization rates and may be compensating to maintain budgetary allocations

VolynskaChernivetska

KirovogradskaIvano-Frankivska

KhmelnitskaDniepropetrovskaLvivskaCherkaska

ChernigivskaDonetska

KievAR Crimea

SumskaZakarpatska

KharkivskaPoltavska

KhersonskaZhytomirska

RivnenskaKiev city

Sebastopol cityOdeska

VinnitskaZaporizhska

TernopilskaLuganska

Mykolaevska

10 15 20 25Average length of stay (days)

Source: World Bank Health and Education Survey 2004

Average length of stay by oblast

Budget Rigidities and Inefficiencies Translate into Inequities - OOP Expenditure

Across Oblasts• Insufficient public financing translates into the need for households to purchase drugs

outside the health facility and into high rates of informal payments at health facilities• Extent of OOP expenditure is large, although estimates vary (40% to 60% of total health

expenditure depending on source) • As a share of total income, OOP expenditures range widely across oblasts• Drugs constitute the largest share of OOP spending and households finance 99.9% of

total drug costs in Ukraine (National Health Accounts)

Source: Authors’ calculations from World Bank Health and Education Survey 2004

Out of Pocket Expenditures by Type

0.0%1.0%2.0%3.0%4.0%5.0%6.0%7.0%8.0%

Oblast

OO

P S

ha

re o

f In

co

me

Drugs

Travel

Travel Cost

Outpatient

Inpatient

High Levels of Catastrophic OOP Spending

• Compared to other ECA countries, Ukraine has the highest proportion of households facing catastrophic OOP spending (OOP spending greater than 40% non-subsistence spending. See Annex 3 for methodology)

• 10 % of households face catastrophic spending due to drug spending alone, suggesting little financial protection

Percent of households spending more than 40% of non-subsistence expenditure on OOP

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

Slovakia Croatia Slovenia Hungary Latvia Estonia Russia Ukraine

Outpatient Facility Use by Type of Facility and Economic Status

• The poorest quintile is significantly less likely to use outpatient services• Public polyclinics and rayon hospitals constitute the largest share of

outpatient visits and these are used most by the three richest quintiles

0 500 1,000 1,500Sum of outpatient visits

Specialized facility

Other

Oblast hospital

Private polyclinic

Village hospital

Med Asst/Obstetric care center

Rayon or town hospital

Public polyclinic


Outpatient visits by facility type and economic status

Bottom Quintile Quintile 2Quintile 3 Quintile 4

Top Quintile

Inpatient Facility Use by Type of Facility and Economic Status

• The richest and poorest quintile use inpatient services the least and their utilization rates are statistically significantly less than the median and 2nd richest quintiles

• Across income quintiles, the majority of inpatient visits occur at rayon hospitals

0 200 400 600 800 1,000Sum of inpatient visits

Private hospital

Academic Medical Clinic

Departmental hospital

Village hospital

Sanatorium

Other

Maternity home

Oblast hospital

Raion or town hospital


Inpatient visits by facility type and economic status

Bottom Quintile Quintile 2Quintile 3 Quintile 4

Top Quintile

Outline



Conclusions and Policy Recommendations of PER

• Reformulate the MoH norms to eliminate the rigidities preventing efficient resource use (necessary condition but it may not be sufficient)

• Attempt to reduce underlying inefficiencies through: – Basing transfers on outputs rather than inputs – Gearing regulations more towards accreditation of facilities rather

than towards the control of their production function• Purchase drugs, especially for the poor, if physician expenditures can

be reduced by reforming the norms• Target expenditures on facilities that poor prefer to use (public

polyclinics and rayon/town hospitals) • Provide incentives to shift a larger proportion of doctors into primary

care• Regarding HIV/AIDS and TB, improve training of public health

professionals and improve coordination between levels of government• In the medium to long term, introduce prospective payment into

provider reimbursement at the level of the hospital or the individual provider

Annex 1 - Probit regression of a higher length of stay than average

Variable Coefficient Z-statisticEconomic RegionEastern 0.252 (1.94)Donetsk 0.241 (1.79)Prechornomorsk 0.291 (2.36)*Podilia 0.109 (0.87)Central 0.074 (0.55)Predniprovsk 0.235 (1.71)Carpathian 0.014 (0.11)

1,688 Observations * = significant at 5%Other control variables: age, sex, body mass index, marital status, income, education level, inpatient facility type, and geographical location of facility

Average Partial Effects

Economic Region Mean Standard deviation Min Max

Eastern 0.085 0.016 0.024 0.100

Donetsk 0.081 0.016 0.023 0.096

Prechornomorsk 0.099 0.019 0.029 0.116

Podilia 0.036 0.007 0.010 0.043

Carpathian 0.005 0.001 0.001 0.005

Central 0.024 0.005 0.006 0.029

Predniprovsk 0.079 0.015 0.022 0.094

• Probit regression of a higher length of stay than average• Variable Coefficient Z-statistic• Economic Region• Eastern 0.252 (1.94)• Donetsk 0.241 (1.79)• Prechornomorsk 0.291 (2.36)*• Podilia 0.109 (0.87)• Central 0.074 (0.55)• Predniprovsk 0.235 (1.71)• Carpathian 0.014 (0.11)• Socioeconomic and demographic characteristics• 19 < age < 30 0.291 (1.59)• 30 < age < 40 0.217 (1.02)• 40 < age < 50 0.549 (2.60)**• 50 < age < 60 0.586 (2.73)**• 60 < age 0.571 (2.79)**• High education 0.107 (1.38)• No education -0.016 (0.09)• 2nd Income quintile -0.131 (1.13)• 3rd Income quintile -0.267 (2.23)*• 4th Income quintile -0.185 (1.54)• 5th Income quintile -0.289 (2.09)*• Male 0.141 (1.96)• Body mass index 155.31 (1.81)• Single 0.083 (0.57)• Divorced -0.103 (0.74)• Widow 0.074 (0.71)• Location and type of inpatient facility• Oblast hosp. 0.305 (1.61)• Rayon hosp. -0.027 (0.15)• Maternity hosp. -0.595 (2.11)*• Sanatorium 1.649 (6.29)**• Other hosp. 0.950 (3.99)**• Clinic 0.573 (2.64)**• City 0.056 (0.60)• Town 0.022 (0.25)• Constant -1.537 (4.70)**

Observations 1,688* significant at 5%; ** significant at 1%Ramsey’s RESET Test: p-value = 0.09 Reference individual is female, under 19, lives in a rural area of the Polisya economic region, married, lowest income quintile, has secondary education, and was hospitalized in a village hospital.

Annex 2 – Definition of Catastrophic Spending

Catastrophic out-of-pocket (OOP) spending is defined for a household h if OOP spending exceeds 40% of the household’s capacity to pay. The definition of capacity to pay is constructed in the following way and closely follows Xu, K. (2005). "Distribution of health payments and catastrophic expenditures: Methodology." World Health Organization Health Systems Financing Discussion Paper, Number 2.

First, the food expenditure share of total household expenditure is constructed by dividing the household's food expenditure by its total expenditure.

FOODEXPh = The household equivalence scale is used instead of the actual household size to account for economies of scale in household consumption. The equivalence scale is defined as: EQSIZEh = HHSIZEh

B

Previous research from household surveys in 59 countries indicates that the B = 0.56 (Xu et al. 2003). The equivalised food expenditure share is generated by dividing food expenditure by the equivalent household size.

EQFOODh = The poverty line is defined as the food expenditure of the household with food expenditure share of total household expenditure at the 50th percentile in the country. Average food expenditure of the households with food expenditure shares between the 45th and 55th percentiles of the total sample are used to minimize measurement error. The percentiles consider the household weighting variable of the survey. PL = The subsistence expenditure of each household is then calculated as the poverty line multiplied by the equivalent household size of each household.

SEh = PL X EQSIZEh

Capacity to pay is defined as a household's non-subsistence spending. Additionally, for those households reporting food expenditure lower than the level of subsistence spending, non-food expenditure is used as capacity to pay. CTPh = TEXPh - SEh if SEh ≤ FOODh

CTPh = TEXPh - FOODh if SEh > FOODh

FOOD

TEXPh

h

FOOD

EQSIZEh

h

EQFOODh h

h

w

w

Annex 3 - Decomposition of the Redistributive Effect (RE) of OOP health

payments• In addition to access, the effect of financing source on the income distribution is an important

element of equity. The RE, which is the difference between pre- and post-payment Gini coefficients, is affected by: 1) degree of progressivity 2) OOP share of income 3) degree of horizontal inequity 4) reranking due to payment. Possible to think broadly of two components of RE: vertical (V) and horizontal (H+R), where V is a combination of 1) and 2) and (H+R) is the sum of 3) and 4). GX is the Gini coefficient before payment, GX-P is the

Gini coefficient after payment,GF(x) is the Gini coefficient for post-payment income for households with pre-payment income x, αx are weights equal to the product of the population share squared and the post-tax income share of households with income x, GB is the Gini coefficient of the income distribution after payment that would exist if all members of each equal pre-payment income group paid the same amount, and CX-P is the concentration index after payment that is obtained by ranking households first by their income before payment and then within each group of pre-payment equals according to their income after payment

RHVGG

Kg

gGGV

CGR

GH

CGGGG

GGRE

PXX

BX

PXPX

xFx

PXPXBxFxPX

PXX

1

)(

)(

References: Aronson, J.R. and P. Lambert. (1994). “Decomposing the Gini Coefficient to Reveal the Vertical, Horizontal, and Reranking Effects of Income Taxation.” National Tax Journal. 47(2): 273-94. van Doorslaer, E. et al. (1999). “The redistributive effect of health care finance in twelve OECD countries.” Journal of Health Economics, 18: 291-313.

Annex 3 - OOP Payments are Regressive in Ukraine• The redistributive effect, which is the difference between pre- and post-payment

Gini coefficients, indicates the effect of a financing source on the income distribution

• Compared to other ECA countries, OOP payments are most regressive (RE is lowest) in Ukraine

• Increase in income inequality is also greater than of that of direct payments in 10 of 12 OECD countries estimated in van Doorslaer et al (1999).

Redistributive Effect of OOP Financing

Croatia

Slovakia

LatviaUkraine

Russia

Estonia

Slovenia

Hungary

-0.015

-0.010

-0.005

0.000

0.005

0.010

0.015

0.020

Red

istr

ibu

tive E

ffect

Annex 3 - Decomposing the Redistributive Effect: Horizontal Effect Dominates

Vertical Effect• RE is affected by: 1) degree of progressivity 2) OOP share of income 3) degree

of horizontal inequity 4) reranking due to payment (See Annex 4)

• Differential treatment of households of similar income levels is very large in Ukraine

• While possibly due to random nature of illness, most likely greater indicator of regional differences in OOP payment rates and variation in informal payments across facilities, regions, and type of care

Decomposition of Redistributive Effect of OOP Financing

-0.030

-0.020

-0.010

0.000

0.010

0.020

0.030

HungarySlovenia Croatia Estonia Slovakia Russia Latvia Ukraine

Red

istr

ibu

tive E

ffect

Vertical Effect Horizontal Effect

health sector pers: ukraine case study fiscal, efficiency, and equity issues in the health sector...

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