Comparison of Hospitals in Jakarta as Decision-Making Unit for Technical Efficiency and Cost Values: Application of DEA and SFA

Main Article Content

Dyah Retno Wati
Vorasith Sornsrivichai
Sopin Jirakiattikul
Amorn Rodklai

Abstract

The implementation of national health insurance in Indonesia in 2014 as an effort to provide universal health care was known as
the BPJS program. It was named after the responsible agency: Badan Penyelenggara Jaminan Sosial (Health Social Security Administrator). In its early years of implementation, it was indicated that it was not financially optimal because it made a significant financial loss. Therefore, this research was conducted to examine the efficiency level of several hospitals in Jakarta from a technical and cost perspective. The 2018 data was obtained from the Ministry of Health and BPJS. The survey covered 36 hospitals from various regions in Jakarta and was analyzed using Data Envelopment Analysis and Stochastic Frontier Analysis. DEA Solver LV 8 and Frontier 4.1 were the primary tools in this study. There were two significant results of this study. First, most hospitals in Jakarta were efficient in terms of technical efficiency score of DEA (0.73) and SFA (0.52), whereas cost efficiency was mediocre with a score of DEA (0.56) and SFA (0.50). Second, three indices (regional technical efficiency score, regional cost efficiency score, and ownership cost efficiency score) showed similar patterns for DEA and SFA efficiency scores except for the ownership technical efficiency index. It is recommended that the government should immediately improve the centralized national database for hospitals and decide strategic policy to arrange for cooperation between hospitals primarily by sharing their data on hospitals’ load and staff availability.

Article Details

How to Cite
1.
Wati DR, Sornsrivichai V, Jirakiattikul S, Rodklai A. Comparison of Hospitals in Jakarta as Decision-Making Unit for Technical Efficiency and Cost Values: Application of DEA and SFA. Health Sci J Thai [Internet]. 2023 Jul. 17 [cited 2024 Dec. 5];5(3):47-55. Available from: https://he02.tci-thaijo.org/index.php/HSJT/article/view/260407
Section
Original articles

References

Fried HO, Schmidt SS, Lovell CK, editors. The measurement of productive efficiency: techniques and applications. Oxford university press; 1993.

Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision-making units. European journal of operational research. 1978; 2(6): 429-444.

Sherman HD. Hospital efficiency measurement and evaluation: empirical test of a new technique. Medical care. 1984; 22(10): 922-938.

Bogetoft P, Otto L, Bogetoft P, Otto L. Data envelopment analysis DEA. Benchmarking with DEA, SFA, and R. 2011; 81-113.

Procházková J. Efficiency of hospitals in the Czech Republic: DEA & SFA applications.

Katharakis G, Katharaki M, Katostaras T. An empirical study of comparing DEA and SFA methods to measure hospital units’ efficiency. International Journal of Operational Research. 2014; 21(3): 341-364.

Djamhuri A, Amirya M. Indonesian Hospital under the “BPJS” Scheme: A War in a Narrower Battlefield. Jurnal Akuntansi Multiparadigma. 2015; 6(3): 341-349.

Abdurachman E, Eni Y, Furinto A, Warganegara D, So IG. Hospital Efficiency in Indonesia with Frontier Analysis. KnE Social Sciences. 2019: 167-175.

Sari W. Indonesia and the challenge of improving services in public hospitals via performance measurement (Doctoral dissertation, University of Canberra).

Puenpatom RA, Rosenman R. Efficiency of Thai provincial public hospitals during the introduction of universal health coverage using capitation. Health Care Management Science. 2008: 319-338.

Klangrahad C. Evaluation of Thailand’s regional hospital efficiency: An application of data envelopment analysis. ICICM 2017: Proceedings of the 7th International Conference on Information Communication and Management; 2017 Aug 28-30; Moscow, Russia. United States: The Association for Computing Machinery; 2017. p. 104-109.

Tian D. Hospital technical efficiency: comparison of financial and non-financial input variables (Doctoral dissertation, Chulalongkorn University); 2011.