Performance evaluation of the hospital services - a fuzzy analytic hierarchy process model

K.R. Sinimole

International Journal of Productivity and Quality Management, 2012, vol. 10, issue 1, 112-130

Abstract: Healthcare sector is a complex area unique in all its characteristics. Due to its multi dimensional nature it is very difficult to approach the measurement of the performance of healthcare by using any one method. Healthcare sector is evaluated by three categories of measurement namely, structure, process and outcome. The structure of a healthcare unit is assessed by the human and material resources available. But, process of healthcare units is difficult to measure by specific metrics, even though it is considered as the primary aspect of assessment among the measures of quality. Fuzzy analytic hierarchy process (AHP) can be used to evolve such a model. The conventional AHP method is incapable of handling the uncertainty and vagueness involved in the mapping of one's preference to an exact number or ratio. In recent years it has been observed that due to confusion in the decision makers mind, probable deviations should be integrated to the decision making process. The fuzzy model can deal with this incapability by allowing metrics that can assess intangible factors. This paper has tried to develop a fuzzy AHP model to evaluate the healthcare sector.

Keywords: fuzzy AHP; aanalytical hierarchy process; process modelling; SERVQUAL; service quality; performance; hospitals; healthcare efficiency; uncertainty; decision making. (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.inderscience.com/link.php?id=47944 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpqma:v:10:y:2012:i:1:p:112-130

Access Statistics for this article

More articles in International Journal of Productivity and Quality Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().