Jahangiri, Abbas and Jahangiri, Mohammad (2019) Efficiency Analysis and Ranking of Provincial Units of Social Security Organization in Indirect Treatment Sector Using Data Envelopment Analysis Method. Depiction of Health.
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Abstract
Background and Objectives: Nowadays efficiency analysis due to identification of weaknesses, strengths and amount utilization of available resources is important. The purpose of this study was efficiency analysis and ranking of provincial units of Social Security Organization (SSO) in indirect treatment sector. Material and Methods: In this descriptive cross-sectional study, technical, managerial and scale efficiencies of SSO in 31 provinces of Iran by input oriented model of Data Envelopment Analysis (DEA) with assuming variable returns to scale were analyzed and the provinces were ranked using the Anderson-Peterson model. The input variables included number of specialized staff, number of support staff, income amount of each province and the output variables included number and cost of prescriptions that have been investigated. The required data were adapted from the 2017 SSO Statistical Yearbook and data analysis was performed using DEAP 2.1 and EMS 1.3.0 software. Results: Average scores of technical efficiency 0.880, managerial efficiency 0.818, and scale efficiency 0.928 were calculated. Based on above efficiency scores, Kohgiluyeh and Boyerahmad and Tehran ranked first and Kerman ranked last. Conclusion: In general, there is capacity of technical, managerial and scale efficiency improvement respectively 12%, 18.2% and 7.2% in indirect treatment sector of SSO. Therefore, weak and inefficient provinces should be placed in the priority of improving efficiency. This can be achieved through imitation of efficient provinces, implementing electronic prescribing and more accurate management of SSO revenues and number of human resources employed in the indirect treatment sector.
Item Type: | Article |
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Subjects: | STM Digital > Medical Science |
Depositing User: | Unnamed user with email support@stmdigital.org |
Date Deposited: | 05 Apr 2023 07:14 |
Last Modified: | 12 Aug 2024 12:05 |
URI: | http://research.asianarticleeprint.com/id/eprint/496 |