UCPERF: An Urgent Care Patient Satisfaction Instrument

Abstract

This study creates an urgent care (UC) service quality model and contextualizes a version of SERVPERF called UCPERF. In doing so, UCPERF fills a research void by examining how the service quality constructs measure healthcare patient satisfaction within an urgent care environment. Findings indicate that UCPERF is an equally effective version of the SERVPERF model; however, unlike SERVPERF, UCPERF yields a model targeted for patient satisfaction and contextualized for use in an urgent care environment. The authors believe that UCPERF allows quick assessment of competitive issues for patients and can allow greater satisfaction with service quality, which reduces the likelihood of switching healthcare providers.

• behavioral intention
• healthcare service quality
• patient satisfaction
• UCPERF
• urgent care

Additional information

Notes on contributors

G Qin

Hong Qin is an assistant professor in the College of Business Administration at the University of Texas-Pan American. She has published in the Quality Management Journal and the Decision Sciences Institute conference proceedings, and has presented her research at the INFORMS Annual Meeting and the DSI annual meeting. Her research interests include service operations, quality control, and supply chain management.

Victor R. Prybutok

Victor R. Prybutok is a regents professor of decision sciences in the Information Technology and Decision Sciences Department and associate dean of the Toulouse Graduate School at the University of North Texas. He received his bachelor's degree from Drexel University, a master's degree in bio-mathematics, a master's degree in environmental health, and a doctorate in environmental analysis and applied statistics. Prybutok is an ASQ Certified Quality Engineer (CQE), Certified Quality Auditor (CQA), Certified Manager of Quality/Organizational Excellence (CMQ/OE), and an accredited professional statistician (PSTAT^®) by the American Statistical Association. Prybutok has authored over 150 journal articles, several book chapters, and more than 160 conference presentations in information systems measurement, quality control, risk assessment, and applied statistics.

Daniel A. Peak

Daniel A. Peak is an associate professor in information technology in the Information Technology and Decision Sciences Department, College of Business Administration, at the University of North Texas. A concert pianist with bachelor's and master's degrees in piano performance, he received his doctorate in 1994 from UNT with majors in information systems and finance. He is an editor of the Journal of IT Cases and Applications Research. Peak has more than 20 years of IT consulting and planning experience working for executives of Fortune 500 companies, and has won and directed numerous production projects and research grants. He is a member of the Decision Science Institute and Association for Information Systems. Peak can be reached by email at [email protected].

Kwabena G. Boakye

Kwabena G. Boakye is an assistant professor of quantitative analysis in the College of Business Administration at Georgia Southern University. He received his doctorate in management science from University of North Texas, a master's degree in statistics from the University of Idaho, and a bachelor's degree from the KNUST, Ghana. He is an ASQ Certified Six Sigma Green Belt (CSSGB) and Black Belt (CSSBB). His research interests include quality management, statistical quality control, service operations management, logistics service quality, and applied statistics.