Saleh Mollahaliloglu, Sahin Kavuncubasi, Fikriye Yilmaz, Mustafa Z. Younis, Fatih Simsek, Mustafa Kostak, Selami Yildirim and Emeka Nwagwu
Turkish Ministry of Health (MoH) has Health Transformation Program (HTP). The purpose of this program has been to modify the structure of the current system in order to enhance…
Abstract
Purpose
Turkish Ministry of Health (MoH) has Health Transformation Program (HTP). The purpose of this program has been to modify the structure of the current system in order to enhance health system productivity, quality, and access in the Turkish health system. The paper aims to discuss these issues.
Design/methodology/approach
To measure the productivity, a data envelopment analysis-based Malmquist index approach was employed.
Findings
Results showed that the overall HTP have had a considerable positive impact on the productivity of general hospitals.
Research limitations/implications
The limitation is the availability of some data that might not be collected or reported to the MoH in Turkey.
Practical implications
This research’s findings will have an impact on reforming the health care system in Turkey to be competitive and efficient as possible.
Social implications
The research will have implication on reducing cost and provide value to the Turkish population.
Originality/value
This is one of the very few articles that targeted the efficiency of hospital system in Turkey.
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Adnan Kisa, Fikriye Yilmaz, Mustafa Z. Younis, Sahin Kavuncubasi, Korkut Ersoy and Patrick A. Rivers
Poor people often experience a delay in meeting their healthcare needs due to their economic situation. As a result, delayed diagnoses and treatment may increase disease severity…
Abstract
Purpose
Poor people often experience a delay in meeting their healthcare needs due to their economic situation. As a result, delayed diagnoses and treatment may increase disease severity, increase the risk of death, and enhance disease transmission in the community. The purpose of this paper is to provide important information about health service delays among the poorest people in Turkey.
Design/methodology/approach
A field study is conducted among the 92 poorest households in the Etimesgut region of Ankara in order to ascertain any delays in health services among the poor, as well as the factors related to those delays.
Findings
The results of the study show that 87 percent of the households lived on a daily income of US$2.15, and that household member's delay seeking healthcare services an average of 4.66±1.17 times in the past year. Reasons for delaying or not seeking healthcare services included the following: participants thought they would get better without doing anything (7.6 percent), by using traditional herbs (12.7 percent), by using pharmaceuticals already on hand (11.4 percent), the health facility was too far away (5.1 percent), and inability to pay (63.3 percent). Significant associations are found between the delaying behaviors, socioeconomic characteristics of households, and health status.
Practical implications
At the end of the study, policy suggestions are provided for improving medical care seeking behaviors and treatment compliance among the poor.
Originality/value
Poverty is a complex and multidimensional phenomenon that consists of income insufficiency, lack of education, malnutrition, and poor health. The relationship between poverty and poor health impacts those who live in poverty as well as communities, organizations and entire countries. Reducing health disparities and decreasing delays and difficulties in access to health care among poor households are important goals.
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Bayram Şahin, Gülnur İlgün and Seda Sönmez
This study aims to identify the efficiency scores of hospitals affiliated to the Ministry of Health in Turkey between the years of 2010–2015 at provincial level and to reveal the…
Abstract
Purpose
This study aims to identify the efficiency scores of hospitals affiliated to the Ministry of Health in Turkey between the years of 2010–2015 at provincial level and to reveal the factors that affect the efficiency scores.
Design/methodology/approach
The two-stage data envelopment analysis (DEA) method was used to achieve the study purpose. In the first stage, DEA method based on input-oriented Charnes–Cooper–Rhodes (CCR) model was performed to calculate the efficiency scores of public hospitals at the provincial level between 2010 and 2015, and in the second stage, Tobit regression and linear regression analyses were used to identify whether the efficiency scores of provinces are affected by the input, output and control variables.
Findings
Upon the analysis, the average efficiency scores of 81 provinces by years were found to vary between 0.79 and 0.89. According to both regression analyses, all of the input and output variables were found to have significant effects on the efficiency scores of provinces while only the population of province among the control variables was identified as the factor with an effect on the efficiency scores of provinces (p < 0.05).
Practical implications
The results of this study are thought to guide health policymakers and managers in terms of both determining efficient and inefficient hospitals at the provincial level and revealing which variables should be taken into account in order to increase efficiency.
Originality/value
The study differs from previous studies on the efficiency of hospitals. First, although previous studies were generally descriptive studies to determine the efficiency level of hospitals, this study is an analytical study that tries also to show the factors affecting the efficiency of hospitals. In addition, while examining the effect of input and output variables on efficiency scores, control variables were also included in the study.
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The purpose of this paper is to examine the relative efficiency and productivity of hospitals during the health reform process.
Abstract
Purpose
The purpose of this paper is to examine the relative efficiency and productivity of hospitals during the health reform process.
Design/methodology/approach
Data envelopment analyses method (DEA) with the input‐oriented variable‐returns‐to‐scale model was used to calculate efficiency scores. Malmquist total factor productivity index approach was then employed to calculate productivity of hospitals. Data of 101 hospitals was extracted from databases of the Ministry of Health, Vietnam from the years 1998 to 2006.
Findings
There was evidence of improvement in overall technical efficiency from 65 per cent in 1998 to 76 per cent in 2006. Hospitals' productivity progressed around 1.4 per cent per year, which was mainly due to the technical efficiency improvement. Furthermore, provincial hospitals were more technically efficient than their central counterparts and hospitals located in different regions performed differently.
Originality/value
The paper provides an insight in the performance of Vietnamese public hospitals that has been rarely examined before and contributes to the existing literature of hospital performance in developing countries
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Niloufar Ghafari Someh, Mir Saman Pishvaee, Seyed Jafar Sadjadi and Roya Soltani
Assessing the performance of medical laboratories plays an important role in the quality of health services. However, because of imprecise data, reliable results from laboratory…
Abstract
Purpose
Assessing the performance of medical laboratories plays an important role in the quality of health services. However, because of imprecise data, reliable results from laboratory performance cannot be obtained easily. The purpose of this paper is to illustrate the use of interval network data envelopment analysis (INDEA) based on sustainable development indicators under uncertainty.
Design/methodology/approach
In this study, each medical diagnostic laboratory is considered as a decision-making unit (DMU) and an INDEA model is used for calculating the efficiency of each medical diagnostic laboratory under imprecise inputs and outputs. The proposed model helps provide managers with effective performance scores for deficiencies and business improvements. The proposed model with realistic efficiency scores can help administrators manage their deficiencies and ultimately improve their business.
Findings
The results indicate that uncertainty can lead to changes in performance scores, rankings and performance classifications. Therefore, the use of DEA models under certainty can be potentially misleading.
Originality/value
The contribution of this study provides useful insights into the use of INDEA as a modeling tool to aid managerial decision-making in assessing efficiency of medical diagnostic laboratories based on sustainable development indicators under uncertainty.
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Yong Joo Lee and Seong-Jong Joo
Data envelopment analysis (DEA) is based on the production possibility set that involves the process of converting resources or inputs to outputs. Accordingly, most DEA models…
Abstract
Purpose
Data envelopment analysis (DEA) is based on the production possibility set that involves the process of converting resources or inputs to outputs. Accordingly, most DEA models include endogenous variables and need an additional step to find the influence of exogenous variables on the process. The purpose of this paper is to examine the relationship between the efficiency scores of DEA and the exogenous variables using truncated regression analysis with double bootstrapping along with two additional methods.
Design/methodology/approach
First, the authors employ DEA for benchmarking the comparative efficiency of the health care institutes. Next, the authors run and compare truncated, ordinary least square (OLS) and Tobit regression analysis using the double bootstrapping algorithm for finding the influence of exogenous variables on the efficiency of the health care institutes.
Findings
The authors confirmed the amount of bias for the Tobit and OLS regression models, which was caused by serially correlated errors. Accordingly, the authors chose results from the truncated regression model with double bootstrapping for examining the influence of exogenous or environment variables on the efficiency scores.
Research limitations/implications
The study includes cross-sectional data on health care institutes in the state of Washington, USA. Collecting data in various states or regions over time is left for future studies.
Practical implications
In this study, three exogenous variables such as Medicaid revenues, locations of health care institutes and ownership types are significant for explaining the relationship between the efficiency scores and a group of the exogenous variables. Managers and policy makers need to pay attention to these variables along with endogenous variables for promoting the sustainability of the health care institutes.
Originality/value
The study demonstrates the usefulness of the truncated regression analysis with double bootstrapping for confirming the relationship between the efficiency scores of DEA and a group of exogenous variables, which is rare in the DEA literature.
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This study aims to explore the nexus of equality and efficiency by considering public hospitals' development dynamics, capacity and technology indicators.
Abstract
Purpose
This study aims to explore the nexus of equality and efficiency by considering public hospitals' development dynamics, capacity and technology indicators.
Design/methodology/approach
Data was collected from the Ministry of Health Public Hospital Almanacs from 2014 to 2017. The Gini index (GI) is used to estimate the inequality of distribution of hospital performance indicators. A bias-corrected efficiency analysis is calculated to obtain efficiency scores of public hospitals for the year 2017. A path analysis is then constructed to better identify patterns of causation among a set of development, equality and efficiency variables.
Findings
A redefined path model highlights that development dynamics, equality and efficiency are causally related and health technology (path coefficient = 0.57; t = 19.07; p < 0.01) and health services utilization (path coefficient = 0.24; t = 8; p < 0.01) effects public hospital efficiency. The final path model fit well (X2/df = 50.99/8 = 6; RMSEA = 0.089; NFI = 0.95; CFI = 0.96; GFI = 0.98; AGFI = 0.94). Study findings indicate high inequalities in distribution of health technologies (GI > 0.85), number of surgical operations (GI > 0.70) and number of inpatients (GI > 0.60) among public hospitals for the years 2014–2017.
Originality/value
Study results highlight that, hospital managers should prioritize equal distribution of health technology and health services utilization indicators to better orchestrate equity-efficiency trade-off in their operations.