Technical Efficiency, Productivity, and Determinants of Technical Inefficiency of Local Hospitals in Oman: Using Data Envelopment Analysis
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Oman Local Hospital, Technical Efficiency, Productivity, Data Envelopment Analysis, Tobit Model, Malmquist Productivity Indices, Oman
Abstract
The purpose of this study is to evaluate the technical efficiency, productivity, and determinants of technical inefficiency in local hospitals in Oman, which are facing increasing resource constraints. Effective utilization of hospital resources is crucial for improving service delivery, ensuring equitable access, and maintaining the quality of healthcare. The study employs an input-oriented Data Envelopment Analysis (DEA) approach to assess the technical efficiency of 29 local hospitals under constant returns to scale (CRS), variable returns to scale (VRS), and scale efficiency (SE) using data from 2018. Additionally, a Tobit regression model is used to identify the determinants of hospital inefficiency, and the DEA-based Malmquist Productivity Index (MPI) is applied to panel data from 2015 to 2018 to measure Total Factor Productivity Change (TFPCH). The findings reveal that 75.8% of the local hospitals were technically efficient under VRS and SE assumptions, while 79.3% achieved technical efficiency under the CRS assumption. The average technical efficiency scores under CRS, VRS, and SE were 96%, 97%, and 99%, respectively. The Tobit model indicates that the number of physicians and pharmacists negatively impacts the VRS efficiency score, while the number of outpatient visits has a positive effect. Productivity growth of 18.1% was observed over the study period, mainly driven by a 42.6% increase in technological change. The study concludes that while most local hospitals in Oman are technically efficient, there is still room for improvement. The findings imply that targeted interventions, such as optimizing the allocation of human resources and leveraging technological advancements, could enhance the overall efficiency and productivity of the healthcare system in Oman.
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References
Ahmed, S., Hasan, M. Z., Laokri, S., Jannat, Z., Ahmed, M. W., Dorin, F., ... Khan, J. A. (2019). Technical efficiency of public district hospitals in Bangladesh: A data envelopment analysis. Cost Effectiveness and Resource Allocation, 17(1), 1-10. https://doi.org/10.1186/s12962-019-0183-6
Alatawi, A. D., Niessen, L. W., & Khan, J. A. (2020). Efficiency evaluation of public hospitals in Saudi Arabia: An application of data envelopment analysis. BMJ Open, 10(1), e031924. https://doi.org/10.1136/bmjopen-2019-031924
Alrashidi, A. N. (2016). Data envelopment analysis for measuring the efficiency of head trauma care in England and Wales (Doctoral dissertation, University of Salford, United Kingdom).
Banker, R. D., & Natarajan, R. (2008). Evaluating contextual variables affecting productivity using data envelopment analysis. Operations Research, 56(1), 48-58. https://doi.org/10.1287/opre.1070.0460
Canberra, A. (2006). Alcohol and Other Drug Treatment Services in Australian Capital Territory. Australian Institute of Health and Welfare.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2(6), 429-444. https://doi.org/10.1016/0377-2217(78)90138-8
Coelli, T. J., Rao, D. S. P., O'Donnell, C. J., & Battese, G. E. (2005). An Introduction to Efficiency and Productivity Analysis. Springer Science & Business Media.
Cylus, J., Papanicolas, I., Smith, P. C., & World Health Organization. (2016). Health system efficiency: How to make measurement matter for policy and management. World Health Organization. Regional Office for Europe.
Farrell, M. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253-281. https://doi.org/10.2307/2343100
Faruk, O., & Rahaman, A. (2015). Measuring efficiency of conventional life insurance companies in Bangladesh and takaful life insurance companies in Malaysia: A non-parametric approach. Management Studies and Economic Systems, 2(2), 129-144. https://doi.org/10.12816/0019398
Kamil, W., Kruger, E., & Tennant, M. (2021). Utilisation of dental services of older people in Australia: An economic explanatory model based on cost and geographic location. Geriatrics, 6(4), 1-12. https://doi.org/10.3390/geriatrics6040102
Kirigia, J. M., Mensah, O. A., Mwikisa, C., Asbu, E. Z., Emrouznejad, A., Makoudode, P., & Hounnankan, A. (2010). Technical efficiency of zone hospitals in Benin. The African Health Monitor, 12, 30-39. https://doi.org/10.1186/s13561-017-0161-7
Küçük, A., Özsoy, V. S., & Balkan, D. (2020). Assessment of technical efficiency of public hospitals in Turkey. European Journal of Public Health, 30(2), 230-235. https://doi.org/10.1093/eurpub/ckz143
MOH. (2014). Health Vision 2050. Retrieved from https://www.moh.gov.om/documents/16506/119833/Health+Vision+2050/7b6f40f3-8f93-4397-9fde-34e04026b829
MOH. (2019). Oman. Annual Health Report 2018. Retrieved from https://www.moh.gov.om/en/web/statistics/-/-2019
Mwihia, F. K., M'Imunya, J. M., Mwabu, G., Kioko, U. M., & Estambale, B. B. (2018). Technical efficiency in public hospitals in Kenya: A two-stage data envelopment analysis. International Journal of Economics and Finance, 10(6), 141-160. https://doi.org/10.5539/ijef.v10n6p141
NCSI. (2020). Statistical Year Book 2019. Retrieved from https://www.ncsi.gov.om/Elibrary/LibraryContentDoc/bar_Statistical%20Year%20Book_%207-5-2020_3d83f732-9fdf-4523-a64d-8c9dac8c19cb.pdf
Newbrander, W., Barnum, H., Kutzin, J., & World Health Organization. (1992). Hospital economics and financing in developing countries. Retrieved from
Ramanathan, R. (2005). Operations assessment of hospitals in the Sultanate of Oman. International Journal of Operations & Production Management, 25(1), 39-54. https://doi.org/10.1108/01443570510572231
Ruggiero, J. (1996). Efficiency of educational production: An analysis of New York school districts. The Review of Economics and Statistics, 78(3), 499-509. https://doi.org/10.2307/2109797
Sena, V. (1999). Stochastic frontier estimation: A review of the software options. Journal of Applied Econometrics, 14(5), 579-586. https://doi.org/10.1002/(SICI)1099-1255(199909/10)14:5
Simar, L., & Wilson, P. W. (2000). A general methodology for bootstrapping in non-parametric frontier models. Journal of Applied Statistics, 27(6), 779-802. https://doi.org/10.1080/02664760050081951
Wealth, S. C. f. t. R. o. C. (1997). Data envelopment analysis: A technique for measuring the efficiency of government service delivery. Retrieved from https://www.pc.gov.au/research/supporting/data-envelopment-analysis/dea.pdf
World Health Organization (WHO). (2010). Efficiency. Retrieved from https://www.who.int/health_financing/topics/efficiency/en/
Zere, E. (2000). Hospital efficiency in Sub-Saharan Africa: Evidence from South Africa.
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