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International Journal of Business, Economics and Management

January 2021, Volume 8, 1, pp 19-30

Determinants of Technical Efficiency of Hospitals in Kenya: 2012-2016

Samuel Ojwang OYIEKE

Nehemiah E. OSORO

John Innocent KARAMAGI

Samuel Ojwang OYIEKE¹

Nehemiah E. OSORO² John Innocent KARAMAGI²

Jaramogi Oginga Odinga University of Science and Technology, BONDO-Kenya. ¹

Department of Economics, University of Dar-es-Salaam, Kenya. ²

on Google Scholar

on PubMed

Pages: 19-30

DOI: 10.18488/journal.62.2021.81.19.30

Article History:

Received: 14 September, 2020
Revised: 16 October, 2020
Accepted: 30 October, 2020
Published: 12 November, 2020

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Abstract:

Background: Health care is a basic human right and in the Kenyan constitution, it is the responsibility of the state to provide (GOK., 2010).The government has faced challenges of affordability, quality, availability and timely provision of health care services. Materials and Methods: The study used output oriented VRS_TE DEA model. In estimating the determinants, random effect panel regression model was used. The variables were; log of size, bed occupancy, catchment population, teaching status, average length of stay as independent variables and technical inefficiency as the dependent variable. The data was collected from the hospitals’ published data, and government statistics. Results: There was a general decline in efficiency between 2012 and 2016. VRS_TE (0.9012) was higher than CRS_TE (0.8042). The hospitals were heterogeneous in their operations. There was no hospital which was consistently efficient throughout the period. The average length of stay had significant negative relation with technical efficiency. Conclusion: Technical efficiency is negatively related with the average length of hospital stay. The hospitals should reduce the length of hospital stay through early discharge for stable cases and institute home care for follow-up and to handle the non-life threatening cases through home care.

Contribution/ Originality
This study contributes to the existing literature by using random effect model to estimate the determinants of technical efficiency. The primary contribution of this study is to demonstrate that devolution of health services positively affected health outputs and that average length of stay had significant negative effect on technical efficiency.

Keywords:

Determinants, Technical efficiency, Output oriented VRS_TE, RE panel regression.

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