Data Envelopment Analysis for Relative Efficiency Measurement of Chinese Hospitals: A Systematic Review

The purpose was to explore the gap between China and the international world in efficiency measurement of hospitals with Data Envelopment Analysis, and to improve the standardization of healthcare efficiency measurement in China. A systematic review was conducted using appropriate search strategies. Studies were included containing DEA approaches regarding general hospital efficiency, published in international literature and in both Chinese and English about Chinese hospitals from January 2004 to October 2014. The results showed that statistical significances were found in indicators such as number of DMUs, percentage of allocative efficiency studies, ratio of studies with multiple years, number of studies with monetary indicators in input and output sets, etc. The statistical insignificance in some indicators such as the number of input and output indicators were also found among China, Europe, USA and others. Some problems were found in current DEA-based hospital efficiency studies in China, such as inappropriate selection of input-output indicators, no bias-correction on efficiency scores, etc. The standardization of DEA methods applied in China’s hospital efficiency research needs to be improved. Chinese researchers should pay more attention to latest international research findings, so as to keep pace with the cutting edge hospital efficiency research

Estudos de eficiência em saúde no Brasil por análise envoltória de dados: revisão integrativa

Introduction: The technique known as Data Envelopment Analysis (DEA) is important management tool to assist administrators, managers and managers in planning and evaluation of the quality of services provided to society in the most diverse segments and levels of health care, strengthening and directing decision-making to reach the health efficiency. Objectives: Update the state of the art and present an overview of the applicability of studies that used DEA to assess health efficiency in Brazil, considering the most used decision-making units (DMUs). Methods: It is of an integrative literature review, carried out from a bibliographic survey, with articles collected in Scielo, Lilacs, Medline, PubMed, Scopus and Portal de Capes periodicals. Results: For analysis were identified 42 articles evaluating the health efficiency in Brazil that used the DEA methodology. 47.6% (20) of the publications are concentrated in the years 2012 to 2014. The decision-making units (DMUs) presented in the analyzed studies were: regional health department, microregion, health plan operator, clinical research, basic health unit and laboratory of pathological anatomy (2.4% or 1 article each); state (14.3% or 6 articles); municipality (33.3% or 14 articles); hospital, (38.1% or 16 articles). In municipal evaluations, there was greater concentration of studies in the South and Southeast regions. 69.0% (29 articles) used the model DEA-VRS and 16.7% (7) DEA-CRS. 78.6% (33 articles) had output orientation and 19.0% (8) they were input-oriented. Discussion: The scope of DEA applications in Brazil and the methodology has been improving in recent years. Although the hospital prevails in literature as the most frequently studied DMU, we found a small difference numerical in comparison with works that used the municipality as DMU (only 2 articles or 4.8%). This result indicates a trend, already signaled in other studies, of growing search for the evaluation of efficiency related to municipal management, with a view to implementation of new health policies and programs focused on expanding and improving the access to primary care. Conclusion: We envision a change in applicability and contribution of the DEA methodology in health in Brazil, which may become a trend in coming years, which consists of evaluating the efficiency analysis within the scope of management municipal, targeting primary health care.Introdução: A técnica conhecida como Análise Envoltória de Dados (DEA) é importante ferramenta de gestão ao auxiliar administradores, gerentes e gestores no planejamento e na avaliação da qualidade dos serviços prestados à sociedade nos mais diversos segmentos e níveis de atenção em saúde, robustecendo e direcionando a tomada de decisão para alcance da eficiência em saúde. Objetivos: Atualizar o estado de arte e apresentar um panorama da aplicabilidade dos estudos que utilizaram DEA para avaliar a eficiência em saúde no Brasil, considerando as unidades tomadores de decisão (DMUs) mais utilizadas. Métodos: Trata-se de uma revisão integrativa da literatura, realizada a partir de levantamento bibliográfico, com artigos coletados nas bases de dados Scielo, Lilacs, Medline, PubMed, Scopus e Portal de Periódicos da Capes. Resultados: Foram identificados para análise 42 artigos de avaliação da eficiência em saúde no Brasil que utilizaram a metodologia DEA. 47,6% (20) das publicações estão concentradas nos anos de 2012 a 2014. As unidades tomadoras de decisão (DMUs) apresentadas nos estudos analisados foram: direção regional de saúde, microrregião, operadora de plano de saúde, pesquisa clínica, unidade básica de saúde e laboratório de anatomia patológica (2,4% ou 1 artigo, cada); estado (14,3% ou 6 artigos); município (33,3% ou 14 artigos); hospital, (38,1% ou 16 artigos). Nas avaliações municipais, houve maior concentração de estudos nas regiões Sul e Sudeste. 69,0% (29 artigos) utilizaram o modelo DEA-VRS e 16,7% (7) DEA-CRS. 78,6% (33 artigos) tinham orientação a output e 19,0% (8) eram orientados a input. Discussão: É grande o escopo de aplicações de DEA no Brasil e a metodologia vem se aprimorando nos últimos anos. Apesar do hospital prevalecer na literatura como DMU mais frequentemente estudada, constatamos uma pequena diferença numérica na comparação com trabalhos que usaram o município como DMU (apenas 2 artigos ou 4,8%). Tal resultado indica uma tendência, já sinalizada em outros estudos, da busca crescente pela avaliação de eficiência relacionada à gestão municipal, tendo em vista a implementação de novas políticas e programas de saúde com foco na ampliação e melhoria do acesso à atenção primária. Conclusão: Vislumbramos uma mudança na aplicabilidade e contribuição da metodologia DEA em saúde no Brasil, que pode vir a se tornar tendência nos próximos anos, a qual consiste na avaliação de análise de eficiência no âmbito da gestão municipal, tendo como alvo a atenção primária em saúde

Avaliação de desempenho e integração docente-assistencial nos hospitais universitários

OBJECTIVE: To assess the performance and integration between the health care and teaching dimensions in Brazilian university hospitals. METHODS: A network data envelopment analysis (DEA) model was designed to measure the performance of federal university hospitals, which enables the relationship between the teaching and health care dimensions to be considered simultaneously. Data from the Ministry of Education Information System of University Hospitals, in the second semester of 2003, were used. Results of the network model were compared to those of classical DEA models to assess the advantages of the new methodological proposal. RESULTS: The efficiency of the hospitals assessed varied between 0.19 and 1.00 (mean = 0.54). The dimensional score showed that hospitals prioritize the gain in health care efficiency. It was observed that there was a need to double the number of medical students and increase the number of residents by 14% to obtain efficiency in the teaching dimension. CONCLUSIONS: The model was useful for both unit managers, aiming to integrate teaching and health care, and regulatory organizations, when defining policies and incentives.OBJETIVO: Evaluar el desempeño y la integración entre las dimensiones de asistencia y de enseñanza de los hospitales universitarios brasileros. MÉTODOS: Un modelo de data envelopment analysis en redes (network DEA) fue elaborado para contrastar el desempeño de hospitales universitarios federales, permitiendo considerar la relación entre las dimensiones de enseñanza y de asistencia, simultáneamente. Fueron utilizados los datos del Sistema de Información de los Hospitales Universitarios del Ministerio de Educación de Brasil, correspondientes al segundo semestre de 2003, y los resultados del modelo network fueron comparados con aquellos modelos DEA tradicionales para evaluación de las ventajas de la nueva propuesta metodológica. RESULTADOS: La eficiencia de los hospitales evaluados varió entre 0,19 y 1,00 (promedio=0,54). El escore dimensional mostró que los hospitales priorizan la ganancia de eficiencia asistencial. Se observó que, para obtener eficiencia en la dimensión de enseñanza, hay necesidad de duplicar el número de alumnos de medicina y de aumentar los residentes en 14% para que se tornen eficientes en la dimensión de enseñanza. CONCLUSIONES: El modelo mostró utilidad de aplicación tanto para los gestores de las unidades, buscando la integración docente-asistencial, como para los órganos reguladores, en la definición de políticas e incentivos.OBJETIVO: Avaliar o desempenho e a integração entre as dimensões de assistência e de ensino dos hospitais universitários brasileiros. MÉTODOS: Um modelo de data envelopment analysis em redes (network DEA) foi elaborado para aferir o desempenho de hospitais universitários federais, o qual permite considerar a relação entre as dimensões de ensino e de assistência, simultaneamente. Foram utilizados os dados do Sistema de Informação dos Hospitais Universitários do Ministério da Educação, referentes ao segundo semestre de 2003, e os resultados do modelo network foram comparados àqueles dos modelos DEA tradicionais para avaliação das vantagens da nova proposta metodológica. RESULTADOS: A eficiência dos hospitais avaliados variou entre 0,19 e 1,00 (média = 0,54). O escore dimensional mostrou que os hospitais priorizam o ganho de eficiência assistencial. Observou-se que há necessidade de dobrar o número de alunos de medicina e de aumentar os residentes em 14% para que se tornem eficientes na dimensão de ensino. CONCLUSÕES: O modelo mostrou utilidade de aplicação tanto para os gestores das unidades, visando à integração docente-assistencial, como para os órgãos reguladores, na definição de políticas e incentivos

Dynamic network data envelopment analysis for university hospitals evaluation

OBJETIVO Desenvolver ferramenta de avaliação de eficiência de hospitais universitários federais de perfil geral. MÉTODOS A análise envoltória de dados, técnica de programação linear, constrói uma fronteira de melhores práticas pela comparação da produção observada dadas as quantidades de recursos despendidas. O modelo é orientado a produto, e considera retornos variáveis de escala. A análise envoltória de dados em redes considera variáveis de ligação que pertencem a mais de uma dimensão (no modelo, médicos residentes, internações ajustadas e projetos de pesquisa). A análise envoltória de dados dinâmica usa variáveis de transporte (no modelo, receita) para analisar o deslocamento da fronteira em anos subsequentes. Os dados foram coletados do sistema de informações do MEC, 2010 a 2013. RESULTADOS Os escores médios de assistência, ensino e pesquisa no período foram: 58,0%, 86,0% e 61,0%, respectivamente. Em 2012, ano de melhor desempenho, para que todas as unidades atingissem a fronteira, seria necessário aumento médio de consultas de 65,0%; de internações, de 34,0%; de alunado de graduação, de 12,0%, de residência multiprofissional, de 13,0%, de pós-graduação, de 48,0%; de projetos de pesquisa, de 7,0%; além de queda de 9,0% de residentes médicos. No mesmo ano, para melhora da fronteira de produção assistencial, seria necessária a injeção de um aporte adicional de receita de 0,9%. Observou-se progressão da eficiência no ensino; oscilação na assistência e estagnação na pesquisa na avaliação dinâmica. CONCLUSÕES O modelo proposto gera parâmetros de planejamento e programação em saúde pública por meio do cálculo dos escores de eficiência e das projeções necessárias para alcance das fronteiras de melhores práticas.OBJECTIVE To develop an assessment tool to evaluate the efficiency of federal university general hospitals. METHODS Data envelopment analysis, a linear programming technique, creates a best practice frontier by comparing observed production given the amount of resources used. The model is output-oriented and considers variable returns to scale. Network data envelopment analysis considers link variables belonging to more than one dimension (in the model, medical residents, adjusted admissions, and research projects). Dynamic network data envelopment analysis uses carry-over variables (in the model, financing budget) to analyze frontier shift in subsequent years. Data were gathered from the information system of the Brazilian Ministry of Education (MEC), 2010-2013. RESULTS The mean scores for health care, teaching and research over the period were 58.0%, 86.0%, and 61.0%, respectively. In 2012, the best performance year, for all units to reach the frontier it would be necessary to have a mean increase of 65.0% in outpatient visits; 34.0% in admissions; 12.0% in undergraduate students; 13.0% in multi-professional residents; 48.0% in graduate students; 7.0% in research projects; besides a decrease of 9.0% in medical residents. In the same year, an increase of 0.9% in financing budget would be necessary to improve the care output frontier. In the dynamic evaluation, there was progress in teaching efficiency, oscillation in medical care and no variation in research. CONCLUSIONS The proposed model generates public health planning and programming parameters by estimating efficiency scores and making projections to reach the best practice frontier

Performance evaluation of nonhomogeneous hospitals : the case of Hong Kong hospitals

Throughout the world, hospitals are under increasing pressure to become more efficient. Efficiency analysis tools can play a role in giving policymakers insight into which units are less efficient and why. Many researchers have studied efficiencies of hospitals using data envelopment analysis (DEA) as an efficiency analysis tool. However, in the existing literature on DEA-based performance evaluation, a standard assumption of the constant returns to scale (CRS) or the variable returns to scale (VRS) DEA models is that decision-making units (DMUs) use a similar mix of inputs to produce a similar set of outputs. In fact, hospitals with different primary goals supply different services and provide different outputs. That is, hospitals are nonhomogeneous and the standard assumption of the DEA model is not applicable to the performance evaluation of nonhomogeneous hospitals. This paper considers the nonhomogeneity among hospitals in the performance evaluation and takes hospitals in Hong Kong as a case study. An extension of Cook et al. (2013) [1] based on the VRS assumption is developed to evaluated nonhomogeneous hospitals' efficiencies since inputs of hospitals vary greatly. Following the philosophy of Cook et al. (2013) [1], hospitals are divided into homogeneous groups and the product process of each hospital is divided into subunits. The performance of hospitals is measured on the basis of subunits. The proposed approach can be applied to measure the performance of other nonhomogeneous entities that exhibit variable return to scale

Organizational Performance Measurement: A Study in a Pubic University Hospital

Este trabalho teve como objetivo avaliar como elementos do sistema de avaliação de desempenho organizacional são utilizados na rotina gerencial de um hospital universitário. Para atingir os objetivos de pesquisa foi utilizada a metodologia de estudo de caso único, tendo como fontes de dados uma entrevista com o gestor responsável pela avaliação de desempenho e pesquisa documental. Os resultados encontrados demonstraram que ainda que a avaliação de desempenho na instituição estudada apresente grande parte das características que, segundo a literatura, um sistema de avaliação deve conter, alguns desafios persistem. Isto é, mesmo que exista a relação direta da avaliação de desempenho com os resultados financeiros da instituição, o alto nível de participação da alta administração e dos setores da instituição na avaliação de desempenho, alguns problemas existem. O principal deles é o desalinhamento na escolha e categorização de alguns indicadores quando confrontados com a missão e objetivos. Propõe-se que podem ser causas desse desalinhamento a existência de feedback pontual e não global do sistema de avaliação de desempenho (SAD), o foco prioritário em controles e não em metas e objetivos e a orientação prioritária à legitimação e controle do SAD sobre a tomada de decisão estratégica.This study aim to evaluate the organizational prerformance measurement system from a university hospital daily routine. To achieve the objectives of this research, the methodology of single case study was used, and as data sources an interview with the manager responsible for performance evaluation and documentary research. The results demonstrated that the performance measurement system had a lot of characteristics foreseen by the academic literature, challenges still may arise. Although the existence of direct relationship between performance measurement results with the financial results along with the high of involvement of senior management and departments of the institution with the performance measurement activities, some challenges were identified. The main one is related to the misalignment between the selection and categorization of some indicators and the organizational goals. Such disalignment may be caused by the existence of punctual feedback instead of global ones, priority focus on control and not in establishing goals, and priority approach for the measurement system usage in legitimacy and control and not in the strategic decision making

Advancing efficiency analysis using data envelopment analysis: the case of German health care and higher education sectors

The main goal of this dissertation is to investigate the advancement of efficiency analysis through DEA. This is practically followed by the case of German health care and higher education organizations. Towards achieving the goal, this dissertation is driven by the following research questions: 1.How the quality of the different DEA models can be evaluated? 2.How can hospitals’ efficiency be reliably measured in light of the pitfalls of DEA applications? 3.In measuring teaching hospital efficiency, what should be considered? 4.At the crossroads of internationalization, how can we analyze university efficiency? Both the higher education and the health care industries are characterized by similar missions, organizational structures, and resource requirements. There has been increasing pressure on universities and health care delivery systems around the world to improve their performance during the past decade. That is, to bring costs under control while ensuring high-quality services and better public accessibility. Achieving superior performance in higher education and health care is a challenging and intractable issue. Although many statistical methods have been used, DEA is increasingly used by researchers to find best practices and evaluate inefficiencies in productivity. By comparing DMU behavior to actual behavior, DEA produces best practices frontier rather than central tendencies, that is, the best attainable results in practice. The dissertation primarily focuses on the advancement of DEA models primarily for use in hospitals and universities. In Section 1 of this dissertation, the significance of hospital and university efficiency measurement, as well as the fundamentals of DEA models, are thoroughly described. The main research questions that drive this dissertation are then outlined after a brief review of the considerations that must be taken into account when employing DEA. Section 2 consists of a summary of the four contributions. Each contribution is presented in its entirety in the appendices. According to these contributions, Section 3 answers and critically discusses the research questions posed. Using the Translog production function, a sophisticated data generation process is developed in the first contribution based on a Monte Carlo simulation. Thus, we can generate a wide range of diverse scenarios that behave under VRS. Using the artificially generated DMUs, different DEA models are used to calculate the DEA efficiency scores. The quality of efficiency estimates derived from DEA models is measured based on five performance indicators, which are then aggregated into two benchmark-value and benchmark-rank indicators. Several hypothesis tests are also conducted to analyze the distributions of the efficiency scores of each scenario. In this way, it is possible to make a general statement regarding the parameters that negatively or positively affect the quality of DEA estimations. In comparison with the most commonly used BCC model, AR and SBM DEA models perform much better under VRS. All DEA applications will be affected by this finding. In fact, the relevance of these results for university and health care DEA applications is evident in the answers to research questions 2 and 4, where the importance of using sophisticated models is stressed. To be able to handle violations of the assumptions in DEA, we need some complementary approaches when units operate in different environments. By combining complementary modeling techniques, Contribution 2 aims to develop and evaluate a framework for analyzing hospital performance. Machin learning techniques are developed to perform cluster analysis, heterogeneity, and best practice analyses. A large dataset consisting of more than 1,100 hospitals in Germany illustrates the applicability of the integrated framework. In addition to predicting the best performance, the framework can be used to determine whether differences in relative efficiency scores are due to heterogeneity in inputs and outputs. In this contribution, an approach to enhancing the reliability of DEA performance analyses of hospital markets is presented as part of the answer to research question 2. In real-world situations, integer-valued amounts and flexible measures pose two principal challenges. The traditional DEA models do not address either challenge. Contribution 3 proposes an extended SBM DEA model that accommodates such data irregularities and complexity. Further, an alternative DEA model is presented that calculates efficiency by directly addressing slacks. The proposed models are further applied to 28 universities hospitals in Germany. The majority of inefficiencies can be attributed to “third-party funding income” received by university hospitals from research-granting agencies. In light of the fact that most research-granting organizations prefer to support university hospitals with the greatest impact, it seems reasonable to conclude that targeting research missions may enhance the efficiency of German university hospitals. This finding contributes to answering research question 3. University missions are heavily influenced by internationalization, but the efficacy of this strategy and its relationship to overall university efficiency are largely unknown. Contribution 4 fills this gap by implementing a three-stage mathematical method to explore university internationalization and university business models. The approach is based on SBM DEA methods and regression/correlation analyses and is designed to determine the relative internationalization and relative efficiency of German universities and analyze the influence of environmental factors on them. The key question 4 posed can now be answered. It has been found that German universities are relatively efficient at both levels of analysis, but there is no direct correlation between them. In addition, the results show that certain locational factors do not significantly affect the university’s efficiency. For policymakers, it is important to point out that efficiency modeling methodology is highly contested and in its infancy. DEA efficiency results are affected by many technical judgments for which there is little guidance on best practices. In many cases, these judgments have more to do with political than technical aspects (such as output choices). This suggests a need for a discussion between analysts and policymakers. In a nutshell, there is no doubt that DEA models can contribute to any health care or university mission. Despite the limitations we have discussed previously to ensure that they are used appropriately, these methods still offer powerful insights into organizational performance. Even though these techniques are widely popular, they are seldom used in real clinical (rather than academic) settings. The only purpose of analytical tools such as DEA is to inform rather than determine regulatory judgments. They, therefore, have to be an essential part of any competent regulator’s analytical arsenal

Avaliação de desempenho financeiro de organizações hospitalares prestadoras de serviços de saúde ao SUS

Trabalho de Conclusão de Curso (graduação)—Universidade de Brasília, Faculdade de Economia, Administração, Contabilidade e Gestão de Políticas Públicas, Departamento de Ciências Contábeis e Atuariais, 2018.A presente pesquisa relata uma avaliação de desempenho de hospitais prestadores de serviços ao Sistema Único de Saúde (SUS). Analisa 50 hospitais (entre hospitais públicos e privados) em doze estados brasileiros, cujas demonstrações financeiras correspondem ao ano base de 2016. Foram desenvolvidos cinco modelos de análise a partir do estudo de Guerra (2011), utilizando-se diferentes combinações de indicadores financeiros: liquidez corrente, índice geral de endividamento, participação do capital de terceiros, dias de dinheiro em caixa, prazo médio de pagamento e prazo médio de recebimento como inputs; e margem operacional, giro dos ativos e retorno sobre os ativos como outputs. De forma geral, os resultados apresentados corroboram as inferências de Guerra (2011) e Souza et al. (2016), ao constatar que os hospitais com o melhor desempenho possuem mais de 150 leitos e são privados sem fins lucrativos (filantrópicos). Ademais, o perfil da gestão financeira desses hospitais é configurado por pouca dependência do capital de terceiros, alta liquidez dos ativos de curto prazo, baixo índice de endividamento, alta rotatividade dos ativos, margem operacional positiva e razoável retorno líquido dos ativos.The present research reports a performance evaluation of hospitals that provide services to the Unified Health System (SUS). It analyzes 50 hospitals (between public and private hospitals) in twelve Brazilian states, whose financial statements correspond to the base year of 2016. Five models of analysis were developed based on Guerra's (2011) study, using different combinations of financial indicators: current liquidity, general indebtedness index, participation of third-party capital, days cash on hand, average repayment term and average term of receipt as inputs; and operating margin, asset turnover and return on assets as outputs. In general, the results presented corroborate the inferences of Guerra (2011) and Souza et al. (2016), noting that the hospitals with the best performance have more than 150 beds and are private non-profit (philanthropic). In addition, the financial management profile of these hospitals is characterized by low reliance on third-party capital, high liquidity of short-term assets, low indebtedness, high turnover of assets, positive operating margin and reasonable net return on assets

Novo modelo e velhos problemas : análise da eficiência do gasto em recursos humanos na criação do serviço social autônomo Instituto Hospital de Base do Distrito Federal

Dissertação (mestrado)—Faculdade de Economia, Administração, Contabilidade e Gestão De Políticas Públicas, Programa de Pós-Graduação em Ciências Contábeis, 2018.Em meio a um cenário de crise no âmbito da saúde pública do Distrito Federal, promoveu-se a transformação do Hospital de Base em um serviço social autônomo denominado Instituto Hospital de Base do Distrito Federal (IHBDF). O novo arranjo, inspirado em elementos de modelos de administração pública gerencial, visa a solucionar questões como a ineficiência, a insuficiente oferta de serviços de saúde e o elevado gasto com recursos humanos. Tendo em vista esse contexto, a pesquisa analisa os desdobramentos da criação do IHBDF sob a ótica da eficiência do gasto com recursos humanos. Trata-se de uma pesquisa descritiva, com a utilização da Análise Envoltória de Dados (DEA) e com a adoção seguintes variáveis: i) gasto com recursos humanos (GRH); ii) número de cirurgias realizadas (CIR) e iii) número de consultas ambulatoriais realizadas (CSA). A análise abrangeu 240 decision making units (DMUs), que correspondem aos meses observados. Os períodos analisados podem ser segregados em dois grupos: a) modelo tradicional (2008 - 2017), cujos dados foram fornecidos pela Secretaria de Saúde do DF e b) novo modelo (2018 – 2027), o qual abrange os dados projetados. Além da utilização do DEA, investigou-se a existência de informações contábeis no processo decisório acerca da criação do Instituto. Efetuou-se uma consulta via e-SIC à Casa Civil do Distrito Federal e realizou-se a análise de treze documentos relacionados ao processo legislativo concernente ao Projeto de Lei nº 1486/2017. Os resultados evidenciaram que, considerando as metas estabelecidas no contrato de gestão, a criação do IHBDF não promove a superação dos denominados velhos problemas, como a ineficiência e a insuficiente oferta de serviços de saúde. Tendo em vista a ausência de informações contábeis no processo decisório, sugere-se haver uma relação entre os resultados de eficiência observados e a utilização de informações dessa natureza no âmbito das tomadas de decisão. Além disso, depreende-se que o uso e a divulgação de informações contábeis no âmbito de processos decisórios no setor público convergem com preceitos da reforma gerencial da administração pública e vão ao encontro dos princípios da boa governança.In the middle of a crisis scenario in the public health service of Distrito Federal, the Hospital de Base was transformed into an autonomous social service called Instituto Hospital de Base do Distrito Federal (IHBDF). The new arrangement, inspired by elements of models of public administration management, aims to solve issues such as inefficiency, insufficient health services availability and high spending on human resources. Considering this context, this research analyzes the development of the IHBDF from the point of view of the efficiency of human resources expenditure. It deals with a descriptive research, using Data Envelopment Analysis (DEA) and adopting the following variables: i) human resources expenditure (GRH); ii) the number of surgeries (CIR) and iii) the number of outpatient consultations (CSA). The analysis covered 240 decision-making units (DMUs), which correspond to the observed months. The analyzed periods can be segregated into two groups: a) traditional model (2008 - 2017), whose data were provided by the Health Department of Distrito Federal and b) new model (2018 - 2027), which covers the projected data. In addition to the use of the DEA, we verified the existence of accounting information in the decision-making process regarding the creation of the Institute. We made a consultation through the e-SIC platform to the Civil House of Distrito Federal and we analyzed thirteen documents related to the legislative process concerning the Bill 1486/2017. The results showed that, considering the goals established in the management contract, the creation of the IHBDF does not promote the overcoming of the so-called old problems, such as inefficiency and the and insufficient availability of health services. Considering the lack of accounting information in the decision-making process, we suggest a relationship between efficient results and the use of information of this nature in decision-making. Furthermore, we argue that the use and disclosure of accounting information in the public sector decision-making process converge with the precepts of management reform in public administration and are in accordance with the principles of good governance

Gestão em saúde pública : produtividade e eficiência dos hospitais universitários federais

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Economia, Administração e Contabilidade, Programa de Pós-Graduação em Economia, Mestrado Profissional em Economia, 2017.Esta dissertação propõe-se a avaliar a eficiência e produtiva dos Hospitais Universitários Federais – HUFs vinculados ao MEC, participantes do REHUF e cadastrados no SIMEC/REHUF. Foram analisados o quantitativo de 33 HUFs dos 50 hospitais universitários vinculados ao MEC. Para a realização deste trabalho foram utilizados dados secundários, por meio do acesso â base de dados do Cadastro Nacional de Estabelecimentos a Saúde (CNESNet), Datasus, TABWIN SAI, SIH/ DATA SUS/ MS do Ministério da Saúde e fonte de dados da Empresa Brasileira de Serviços Hospitalares – EBSERH, referente aos anos de 2014 a 2016. O instrumento para o cálculo da eficiência foi obtido com o método de análise envoltória de dados (DEA), com retornos constantes de escala, modelo este introduzido por Charnes, Cooper e Rhodes (CCR) em 1978. Posteriormente, foi estendido por Banker, Charnes e Cooper (BCC) em 1984 para incluir retornos variáveis de escala. Cada um desses dois Modelos pode ser desenhado sob duas formas de maximizar a eficiência: 1º. Reduzir o consumo de insumos, mantendo o nível de produção, ou seja, orientado ao insumo. 2º. aumentar a produção, dados os níveis de insumos, ou seja, orientado ao produto (ROSANO-PENA, 2008, p. 92). O instrumento para o cálculo da produtividade foi adquirido o índice de Malmquist proposto para a análise do comportamento do consumidor, em 1953 por Malmquist. Porém, a introdução de Malmquist no contexto da teoria da produção foi apresentado por Caves, Chistensen e Diewert (1982), com o objetivo de mensurar as mudanças de produtividade entre dois períodos de tempo. Verifica-se que o índice de Malmquist (Mo) resulta na decomposição da multiplicação entre o emparelhamento e o deslocamento da fronteira: Mo = (emparelhamento) x (deslocamento da fronteira). Vale destacar que o modelo DEA é um método determinístico não estocástico e, dessa maneira, a avaliação do desempenho dos programas torna-se mais objetivo.This dissertation proposes to evaluate the efficiency and productive of the Federal University Hospitals - HUFs linked to the MEC, participants of the REHUF and registered in the SIMEC/REHUF. We analyzed the quantitative of 33 HUFs of the 50 university hospitals linked to the MEC. For the accomplishment of this work, secondary data were used, through access to the database of the National Register of Health Establishments (CNESNet), Datasus, TABWIN SAI, SIH/DATASUS/MS of the Ministry of Health and data source of the Company The Brazilian Institute of Hospital Services - EBSERH, referring to the years 2014 to 2016. The instrument for the calculation of efficiency was obtained with the method of data involution analysis (DEA), with constant returns of scale, introduced by Charnes, Cooper, and Rhodes (CCR) in 1978. Subsequently, it was extended by Banker, Charnes and Cooper (BCC) in 1984 to include variable returns of scale. Each of these two models can be designed in two ways to maximize efficiency: 1º. Reduce the consumption of inputs, maintaining the level of production, that is, oriented to the input. 2º. To increase production, given the levels of inputs, that is, product-oriented (ROSANOPENA, 2008, p.92). The instrument for calculating productivity was acquired the Malmquist index proposed for the analysis of consumer behavior in 1953 by Malmquist. However, the introduction of Malmquist in the context of production theory was presented by Caves, Chistensen and Diewert (1982), in order to measure productivity changes between two periods of time. It is seen that the Malmquist index (Mo) results in the decomposition of the multiplication between the pairing and the displacement of the boundary: Mo = (pairing) x (border displacement). It is worth mentioning that the DEA model is a non-stochastic deterministic method and, in this way, the evaluation of program performance becomes more objective