A model for multidimensional efficiency analysis of public hospital management

Abstract

Introduction: Multidimensional efficiency analysis can provide important insights into the performance of hospitals.In this paper, we propose a multidimensional model based on Data Envelopment Analysis (DEA) to investigate and compare the efficiency of public hospitals in Brazil. Methods: Data from 21 public hospitals were collected from public databases (OECD -Organization for Economic Co-operation and Development; SIH-SUS -SUS Hospital Information System, Datasus, Brazil). Four inputs (Number of medical and non-medical staff, Annual revenue, Number of beds, Average length of patient hospitalization), four Variables of Influence (Type of hospital, Accredited hospital, Number of medical specialties, Resources from government) and four Outputs (Number of outpatient care services, Number of hospitalizations, Number of surgeries, Number of exams) were used to feed the DEA model. Results: Seven hospital units reach 100% efficiency and, according to DEA, can be considered efficient units. Two units were considered "almost efficient" and the remaining twelve units perform poorly, considering the data supplied to the DEA model. As a whole, the average efficiency of the hospitals investigated was 79% (0.79). Conclusion: A very heterogeneous performance has been found among the Brazilian public hospitals investigated. Besides, the reasonably low average efficiency seems to indicate that the system has a large potential for improvement in almost all areas associated with the input and output variables investigated in this paper.Keywords Hospital efficiency, Data Envelopment Analyses, Public hospital.This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.How to cite this article: Soares AB, Pereira AA, Milagre ST. A model for multidimensional efficiency analysis of public hospital management.

A Literature review on the Identification of Variables for Measuring Hospital Efficiency in the Data Envelopment Analysis (DEA)

“…The number of beds often considered as the capital of the hospital (Omrani et al, 2018). The number of beds in this case are chronic care beds and special care beds (Soares et al, 2017). An effective bed allocation planning, such as considering the number of beds by the size of the hospital could have an impact on calculating efficiency and have a role for hospital management restriction on access and optimum use of resources is the main challenge of development in all organizations.…”

“…Human resources have the most important role in the health service system. The number of doc- (Soares et al, 2017) also midwives (Şahin & İlgün, 2018)for the pre-PHAs period, 24 provinces in 2010, 27 provinces from 2010 to 2011, and 32 provinces from 2011 to 2012 were assessed as efficient. From 2012, the year of implementation, to 2013, the number of efficient provinces dropped to 16.…”

“…DEA can be used in DEAP 2.1 (Tim Coelli Inc.) and to knowing its interpretation can be used SPSS (SPSS Inc., USA) and Frontier Analyst fourth version (Banxia Software Ltd, UK). There are some important term form DEA (Soares et al, 2017): Decision-Making Unit (DMU) is a main unit which efficiency is analyzed. In the case of hospital efficiency assessment, the DMU is hospital; Input is an available resources in the DMU; Output is an impact or result of the process of running the DMU; The efficiency score is a calculated value as a result of an efficiency assessment.…”

Improvement of Innovation Ability of Hospital Managers and Construction of Competitive Strategy

“…The questionnaire survey found that managers could provide available evidence for hospital decision-making and make the best decision in evidence-based decision-making based on hexagon evidence source. Soares et al [10] used a multidimensional model based on data envelopment analysis to analyze the performance of 21 public hospitals in Brazil and found that seven hospitals achieved 100% efficiency and the average efficiency of all hospitals was 79%. Kuhlmann et al [11] conducted a study on hospital management in Russia.…”

Método Análisis Envolvente de Datos y Redes Neuronales en la Evaluación y Predicción de la Eficiencia Técnica de Pequeñas Empresas Exportadoras

“…Otros autores han desarrollado la técnica en diversos contextos como la evaluación de desempeño (Lins, et al, 2007), la evaluación eficiencia económica (Heidari, et al, 2011), la eficiencia gerencial (Tsay, et al, 2017), así como la evaluación de esquemas optimizados (Zhou, et al, 2015). Otras investigaciones han utilizado AED para el análisis de eficiencia multidimensional (Soares, et al, 2017) así como los procesos de internacionalización de mercados (Cano, et al, 2017).Matemáticamente podemos aseverar que El Análisis Envolvente de Datos es un modelo de optimización consistente en una función objetivo h 0 (Ecuación 1) que representa un índice de eficiencia, y un conjunto de restricciones conformadas por ecuaciones y/o inecuaciones que expresan condiciones limitantes para el sistema (Ecuación 2). Para lo anterior la función objetivo se establece mediante el cociente de las variables de salida o resultados y las variables de entrada o recursos de las empresas o entidades objeto de estudio.…”