Abstract
Patient satisfaction survey has been widely adopted by healthcare providers to gauge their service quality and initiate process improvement actions. Usually, summary statistics from the survey results such as means, percentile ranks, and correlation coefficients are analysed for operational decisions. This paper presents a novel approach, using rough set theory, to analyse patient satisfaction survey data collected from a medium-sized community hospital in USA. The advantages of this approach lie in its ability to process data with vagueness and uncertainty, data reduction capability, and strong interpretation ability of decision rules. In this paper, a set of useful managerial rules were derived, based on which the hospital obtained insightful information on how to improve its service quality.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Healthcare Technology and Management
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
