Seeking Intelligence from Patient Experience Using Text Mining: Analysis of Emergency Department Data

Abstract

The Hospital Consumer Assessment Health Providers and Systems survey on patient satisfaction has taken on greater significance with the introduction of the Hospital Value Based Purchase program by the Center for Medicare and Medicaid Services. Content analysis of open-ended comments by patients has seen limited use in spite of the insight in can provide into factors contributing to patient (dis)satisfaction. This article uses an emergency department setting to gain insight from patient experience.

Keywords:

• content analysis
• emergency department
• Hospital Consumer Assessment of Healthcare Providers and Systems survey
• patient satisfaction

Additional information

Notes on contributors

Padmini Varanasi

Padmini Varanasi earned her Master of Science in IT Management focusing in Business Analytics from Oakland University in 2013. She is currently working as data analyst at North American Bancard in Troy, Michigan. The current article is based on her capstone project on sentiment analysis of emergency room patient satisfaction surveys using SPSS Text Analytics. Her academic interests are data sciences and data mining.

Mohan Tanniru

Mohan Tanniru is the professor of MIS at Oakland University. He held positions as the Dean of School of Business Administration at Oakland University, the MIS Dept. Head at the University of Arizona, Director of the Applied Technology in Business Program at OU, and taught at Syracuse University and University of WI-Madison. He is received his PhD in MIS from Northwestern University and published over 80 peer-reviewed journal articles. His research interests are in decision and knowledge based systems, data analysis in health care, and IT innovation and strategy.