“determinants of the efficiency of public spending …§ão de crianças matriculadas em creches...

“Determinants of the efficiency of Public Spending on Health in Brazilian States”

SANTIAGO

January 26th, 2012

Introduction

Motivation

Literature Review

Methodology

Results

Concluding Remarks

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Efficiency of Public Spending on Health

Introduction Background:

• The 1998 Constitution established a new political formulation of the health services in the country.

The new system was grounded on three principles: Universality, Integrality and Equity.

• In addition to the those principles, others were created to organize the process. Decentralization

stands out among them.

• In 1990, Law 8.080 linked the decentralization to municipalization.

• In 2000, the Constitutional Amendment Number 29 established how much each Federative

Unit had to invest. The Federal Government is the main financial agent of the public health

network.

• The Amendment was regulated by a Complementary Law in January 2012. The Law states

what can be considered expenses on the health area and what cannot. However, it does not

bring any novelty concerning Deadlines or Sanctions.

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Region

2000 2008 2000 2008 2000 2008 2000 2008

TOTAL 2,89 3,6 1,73 1,61 0,54 0,92 0,62 1,07

Northern Region 4,62 4,92 2,49 1,61 1,59 2,21 0,54 1,11

Northeastern Region 4,65 5,36 3,12 2,29 0,86 1,54 0,68 1,52

Southeastern Region 2,28 2,69 1,17 0,89 0,43 0,75 0,67 1,05

Southern Region 2,29 2,66 1,35 1,15 0,37 0,54 0,57 0,97

Central Region 2,16 2,6 1,25 0,88 0,54 1,04 0,37 0,68

Source: Ministry of Health

1. All expenditures shown were made on public health services and actions.

Table 1: expenditures on public health services and actions in proportion to the total

expenditures/GDP % by Region (in 2000 and 2008)

Total Expenditure

Proportion/GDP

Federal Expenditure

Proportion/GDP

State Expenditure

Proportion/GDP

Municipal Expenditure

Proportion/GDP

Background:

Introduction

Introduction

Public Spending on Health and Intergovernmental Transfers

The Unified Health System (SUS): The Brazilian public healthcare framework

The Constitution and the provision of public healthcare services: States and

Municipalities´ role

The minimum level of spending of each government level: The Constitutional

rule

Transferring resources from central to local governments – The National

Health Fund

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Introduction

Motivation

Literature Review

Methodology

Results

Concluding Remarks

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Motivation

Transfers Scheme – How is it related to efficiency?

Law 8.080/1990: The transfer of health resources to states and municipalities will be

based on:

I. Demographic profile

II. Epidemiological profile

III. Quantity and Quality of Health Services

IV. Technical, economic and financial performance in previous years

V. Health share in local budget

VI. A 5-year investment plan

VII. Reimbursements from other government levels

VIII. Half of the resources will be distributed according to the number of

inhabitants

IX. Special criteria may apply to states and municipalities with high migration flows 7


Motivation

Public Spending on Health and Intergovernmental Transfers

Based on the criteria listed in the referred law, this paper examines if - and how - the

technical criteria set out in the act 35 of Law 8.080/1990 for the distribution of

resources related to the efficient management of health services in the Federal States.

Therefore, we use a measure of efficiency based on Stochastic Frontier where the

input is public spending on health, whereas health care products are

consultations, hospitalizations, tests and number of beds in the Unified Health

System (SUS) for the period 2000 to 2008.

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Introduction

Motivation

Literature Review

Methodology

Results

Concluding Remarks

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Literature Review

Efficiency Measures: The input/output definitions problem

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Artigo Insumos Produtos Marinho, 2003 Total de Leitos

Total de Hospitais Credenciados

Total da Capacidade Ambulatorial Instalada

Valor médio da Internação

Valor médio dos procedimentos ambulatoriais

Total de Internações em hospitais credenciados

Total de procedimentos ambulatoriais

Faria et al., 2008 Gastos com saúde e saneamento

Gastos com educação

Taxa de alfabetização

Esgotamento Sanitário

Inverso da taxa de mortalidade por causas hídricas

Proporção de crianças matriculadas em creches ou educação infantil

Indicador de Provimento Social

Ferreira et al., 2003 Total das despesas em saúde

Proporção da produção ambulatorial de prestadores

estaduais e federais no total da produção ambulatorial.

Proxy da complexidade do sistema de saúde

Total da produção ambulatorial em atenção básica

Total da produção ambulatorial em média e alta complexidades

Cesconetto et al., 2008 Número de Médicos

Equipe auxiliar de enfermagem

Número de altas geradas para pacientes do SUS

Lins et al., 2007 Número de Funcionários não médicos

Número de médicos

Receita média mensal proveniente do SUS

Número total de Docentes

Número de docentes com doutorado

Índice de Alta complexidade

Relação Internações / Leitos

Relação Cirurgia / Salas

Relação Consultas ambultaroriais / Salas

Número de alunos de medicina (graduação)

Número de residentes médicos

Número de mestrandos e doutorandos

Número de programas de pós-graduação/medicina

Gonçalves et al., 2007 Taxa de mortalidade

Tempo médio de permanência no hospital

Percentuais de internação relativos a neoplasias, doenças infecciosas e parasitárias

(DIP) e doenças do aparelho circulatório.

Valor médio pago pela Autorização de Internação Hospitalar (AIH médio).

Introduction

Motivation

Literature Review

Methodology

Results

Concluding Remarks

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Methodology

Battese and Coelli (1995)

Estimation of a Cost Function to evaluate the inefficiency component

The stochastic frontier for panel data is modeled as:

is governmental spending in health at time t, by unit i

is a vector of healthcare services

are variables explaining the inefficiency term

is defined by a Normal distribution truncated in

In this cost function, the Uit now defines how far the firm operates above the cost frontier.

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ititit

itititit

WzU

UVxY )exp(

itY

itx

itz

itW itz

Methodology

Data

»Annual data for 27 states from 2000 to 2008:

»Population

»Urbarnization level

»Elderly population

»Life expectancy at birth

»Illiterate population

»Water supply

»Sewage system

»Garbage collection

»GDP per capita

»Low income population

»AIDS contamination rate

»Dengue fever contamination rate

»Tegumentary Leishmanie contamination

rate

»Hansen s desease contamination rate

»Tuberculosis

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Methodology

The High Correlation problem

»Methodology based on Principal Components to avoid high correlation between series:

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Group Variables

PC_Sanitation Water supply, Sewage system, Garbage collection.

PC_Demography Population, Elderly population, Life expectancy at birth.

PC_income GDP per capita, (-)Low income population, (-) Illiterate

population, Urbanization level.

PC_ Epidemic AIDS, Dengue fever, Tegumentary Leishmanie, Hansen s

desease and Tuberculosis contamination rates.

Methodology

The High Correlation problem

Table 3: Correlation structure between groups:

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Sanitation Demography Income Epidemic

Sanitation 1.000 0.608 0.811 0.728

Demography 0.608 1.000 0.508 0.532

Income 0.811 0.508 1.000 0.503

Epidemic 0.728 0.532 0.503 1.000

Introduction

Motivation

Literature Review

Methodology

Results

Concluding Remarks

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Results

Table 4: Stochastic Frontier

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Coefficient Std Deviation P-value

Intercept -6.690 *** 0.770 0.000

Consultation 0.446 *** 0.074 0.000

Beds -0.083 . 0.049 0.086

Pathological examinations 0.286 *** 0.062 0.000

Imaging examinations 0.175 *** 0.050 0.000

Hospitalizations -0.203 * 0.091 0.026

“.” represents significance in 10%; “*” represents significance in 5%; “**” represents significance in 1%;

“***” represents significance in 0.1%.

Results

Table 4: Z-Variables

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Coefficient Std Deviation P-value

Intercept -1.243 ** 0.417 0.003

PC_Sanitation -0.159 ** 0.056 0.004

PC_Demography -0.927 *** 0.217 0.000

PC_Income 0.309 *** 0.070 0.000

PC_Epidemics[1] -0.142 *** 0.042 0.001

PC_Epidemics[2] -0.123 * 0.049 0.011

Trend 0.062 ** 0.023 0.007

sigmaSq 0.058 *** 0.016 0.000

gamma 0.762 *** 0.082 0.000

Log Likelihood 120.928

Observations 243

Cross Section Units 27

Time Units 9

Average Efficiency 0.893

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•Concerning Table 4 first part, the signs of the coefficients of the stochastic frontier

are as expected, with the exception of the negative estimate of the number of

hospitalizations and beds variables. It s possible that scale effects are causing noise in

estimating, that is, states that operate in large scale also have more hospital beds. So,

that can interfere in the results. That result is counterintuitive and will be looked into

afterwards.

•Concerning Table 4 second part - the estimated coefficients in the inefficiency

model are of particular interest to this study:

Concerning sanitation, the negative coefficient indicates that an improvement in

the variables related to sanitation such as water supply, sewers and garbage

collection are associated with a decrease in the lack of efficiency in the public

health service.

Results

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Demography has a negative coefficient, showing a direct relation between an improvement

in that coefficient and health expenditure efficiency. That phenomenon may be linked to the

system s adaptation to cater for an increase in the demand for health services due to na increasing

elderly population.

Income is significant and has a positive coefficient. Notice that a higher income per capita

enables the population to make use of private hospitals, thus reducing demand in the public health

system, which does not incite an increase in efficiency as there is a reduction in the number of

consultations, examinations, hospitalizations and beds. Conversely, the growth in the low-income

population calls for more public health service demand.

Epidemiological variables were also significant and negative results which indicate that the

public system has to adapt to the increase in the demand due to epidemics, that is, an

epidemic outbreak makes the state react more efficiently in providing health services to see to the

stricken population.

Results

Introduction

Motivation

Literature Review

Methodology

Results

Concluding Remarks

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Concluding Remarks

Public Policies Implications

•Concerning the estimated elasticities, the results show that the increase in the number of

consultations and clinical examinations leads to an augmentation in health expenditure. Furthermore,

we can see that the increase in the health service efficiency is associated with sanitation,

demographic characteristics of the population, level of income and epidemics.

•According to the criteria stablished by Law number 8.080 of 1990 act 35, the increase in the

health service demand makes the state react more efficiently in relation to those target

populations.

•However, the state s reaction does not necessarily entail providing high standards of public

health service. There is the need for research to investigate this topic carefully, using different

methodological approaches.

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Contact: __________________________________________ JANETE DUARTE Fiscal-Economic Research [email protected]

Tel.: +55 (61) 3412-2203

Thank You!


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