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Multifactor efficiency in data envelopment analysis with an application to urban hospitals.
1Division of Health Management and Policy, College of Medicine, University of Iowa, Iowa City 52242-1008, USA. liam-oneill@uiowa.edu
Health Care Management Science
|August 1, 2000
Summary
This study introduces multifactor efficiency, a new Data Envelopment Analysis (DEA) method to compare hospital efficiency, especially teaching versus non-teaching hospitals. Multifactor efficiency offers enhanced performance measurement for healthcare decision-making units (DMUs).
Area of Science:
- Healthcare Management
- Operations Research
- Health Economics
Background:
- Measuring hospital efficiency is complex, particularly when comparing teaching and non-teaching institutions.
- Existing methods in Data Envelopment Analysis (DEA) face challenges in comparing specialist and non-specialist Decision-Making Units (DMUs).
Purpose of the Study:
- To introduce a novel performance measure in DEA called multifactor efficiency.
- To address the methodological difficulties in comparing diverse healthcare providers, such as teaching hospitals.
Main Methods:
- Development of multifactor efficiency as an average partial factor productivity index.
- Application of the new measure to assess the performance of 27 large, urban hospitals, including 13 teaching hospitals.
Main Results:
- Multifactor efficiency was applied to a sample of 27 hospitals, providing a new perspective on their performance.
- The results were validated by a panel of healthcare experts, confirming the utility of the new measure.
Conclusions:
- Multifactor efficiency offers significant benefits for enhancing and complementing existing DEA performance measures.
- This new approach provides a more nuanced way to evaluate and compare healthcare organizations with varying specializations.