Integrated Analysis of Healthcare Efficiency: A Systematic Review

Abstract

Data Envelopment Analysis (DEA) has been used as a performance measurement tool in efficiency assessment of healthcare systems. However, over the years, researchers and health practitioners presented the theoretical and methodological limitations of DEA that limits the full view of healthcare efficiency. To address these limitations, a commonly used strategy is to integrate other statistical methods and techniques with DEA to provide better efficiency evaluation. This paper reviews 57 studies with DEA applications in the healthcare industry to illustrate the integrated analysis of healthcare efficiency. With DEA as the central method, regression models in conjunction with statistical tests are commonly used. Input-oriented radial DEA models using predominantly capacity-related inputs and activity-related outputs and following either constant return to scale or variable return to scale assumptions are mostly applied to measure healthcare efficiency.

Going beyond health efficiency: What really matters?

“…As described above, in the literature the efficiency of a country's hospitals is measured more often than the health system as a whole. Consequently, papers that review the literature on the measurement of healthcare efficiency also emphasize hospitals . Varabyova and Müller systematize previous works on the efficiency of healthcare systems in different countries by reviewing 22 such studies conducted before August 2014.…”

“…Because of its characteristics, Data Envelopment Analysis (DEA) is the approach most widely used to measure the efficiency of healthcare systems . However, environmental factors also influence health systems, so in addition to the main DEA method, regression models are often used in conjunction with statistical tests in order to give a more comprehensive analysis and to determine the impact of environment on efficiency or inefficiency . Thus, a two‐stage DEA is often used to explain differences in efficiency, the first stage being a classic efficiency evaluation and the second stage consisting of statistical tests and analyses.…”

Measuring Efficiency of the New Zealand District Health Boards: An Empirical Research Using Two‐Stage Data Envelopment Analysis

“…x jz = the amount of input j used by z th DHB; y iz = the amount output i provided by z th DHB; u i = weight assigned to output i; v j = weight assigned to input j The above model in ratio form does not indicate whether the sums of weighted inputs are minimised (input-oriented) or whether instead the sums of weighted outputs are maximised (output-oriented). In the healthcare sector, the input-oriented model is often used as there is a wide acceptance that managers and policy-makers generally have more control over inputs than outputs and that more priority is put on costs than increasing healthcare demand (O'Neill et al, 2008;Cantor & Poh, 2018). Therefore, we also employ an input orientation in the analysis that follows.…”

“…However, it seems that the variables used to measure efficiency in health care vary by circumstances, authors' rationale and availability of data. For hospitals, capital investment, labour and other operating expenses are the main inputs, whereas inpatients and outpatients are the key outputs (O'Neill et al, 2008;Cantor & Poh, 2018). Regarding primary care, the outputs might be activities (number of visits or examinations), quality indicators or health outcomes (Pelone et al, 2015).…”

Measuring Technical Efficiency of Hospitals Using Data Envelopment Analysis: A Review

“…Literature has shown that DEA were popular method of measuring hospital efficiency (Cantor & Poh, 2018;O'Neill, Rauner, Heidenberger, & Kraus, 2008). Several studies were used the DEA model to estimate hospitals efficiency.…”