Volume 21, Issue 73 (10-2018)
jha 2018, 21(73): 35-48 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Papi S, Khorramabadi M, Lashgarara S. Estimating productivity of the provinces of Iran in the health sector using Fuzzy data in Imprecise Data Envelopment Analysis(IDEA). jha 2018; 21 (73) :35-48
URL: http://jha.iums.ac.ir/article-1-2663-en.html
URL: http://jha.iums.ac.ir/article-1-2663-en.html
1- Faculty of Mathematics, Razi University, Kermanshah, Iran
2- Faculty of Management and Accounting, Payame Noor University, Tehran, Iran ,m.kh.acc@pnu.ac.ir
3- Faculty of Management and Accounting, Payame Noor University, Tehran, Iran
2- Faculty of Management and Accounting, Payame Noor University, Tehran, Iran ,
3- Faculty of Management and Accounting, Payame Noor University, Tehran, Iran
Abstract: (3767 Views)
Introduction: Abstract: Increasing the productivity of health care spending is important for all countries. In order to increase productivity, input and output data can have fuzzy values. This study aimed to present a new model of inadequate envelopment analysis to determine the productivity of provinces in the health sectors, highlight productive provinces and detect sensitive indexes to increase productivity.
Methods: This descriptive-analytical study was conducted on the health system of Iran in 2016. Data were collected through library documents, Internet and the center of statistics and information technology management of medical universities. Analytical hierarchy process was used to determine health care indexes among which five indicators were extracted. Data were analyzed using inadequate envelopment analysis technique by General Algebraic Modeling System.
Results: According to the proposed model, for and, only Semnan, Kurdistan and Mazandaran provinces were considered to be efficient based on their indexes on patient satisfaction and physician-to-population ratio, and were regarded as referral units for other provinces. The two indexes of physician- to-population ratio and nurse-to-population ratio were introduced as the most and the least sensitive indicators, respectively.
Conclusions: Kurdistan, based on the most sensitive indicator, had the highest referral patients. Other provinces can increase their efficiency through improving the quality and quantity of their services, increasing patient satisfaction, continuous evaluation of performance and increasing the number of physicians working in medical universities.
Methods: This descriptive-analytical study was conducted on the health system of Iran in 2016. Data were collected through library documents, Internet and the center of statistics and information technology management of medical universities. Analytical hierarchy process was used to determine health care indexes among which five indicators were extracted. Data were analyzed using inadequate envelopment analysis technique by General Algebraic Modeling System.
Results: According to the proposed model, for and, only Semnan, Kurdistan and Mazandaran provinces were considered to be efficient based on their indexes on patient satisfaction and physician-to-population ratio, and were regarded as referral units for other provinces. The two indexes of physician- to-population ratio and nurse-to-population ratio were introduced as the most and the least sensitive indicators, respectively.
Conclusions: Kurdistan, based on the most sensitive indicator, had the highest referral patients. Other provinces can increase their efficiency through improving the quality and quantity of their services, increasing patient satisfaction, continuous evaluation of performance and increasing the number of physicians working in medical universities.
Keywords: Health, Data envelopment analysis, Efficiency, Fuzzy data, Productivity, Most productive scale size (MPSS)
Type of Study: Research |
Received: 2018/03/7 | Accepted: 2018/09/23 | Published: 2018/09/29
Received: 2018/03/7 | Accepted: 2018/09/23 | Published: 2018/09/29
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
Site Keywords
Health, Administration, Scientific Article, Iran University of Medical Sciences,
