Background: Satisfaction with health care is one of the most widely assessed measures of hospital care quality, yet studies that account for clustering effects are uncommon. We constructed a multilevel model to identify predictors of willingness to recommend while controlling for clustering effects due to hospital and care unit. We also examined differences in predictors by care unit.
Purpose: The aim of this study was to identify factors that both influence patient perceptions of care and are potentially modifiable by the hospital delivering care.
Methodology: Our sample includes Hospital Consumer Assessment of Healthcare Providers and Systems survey data collected between July 1, 2007, and June 30, 2008, for 131 hospitals and 33,445 patients. The primary outcome was willingness to recommend the hospital to family and friends. Variables were collected at three levels: patient (Hospital Consumer Assessment of Healthcare Providers and Systems survey item responses and demographics), care unit, and hospital. Data were analyzed using multilevel modeling. We also ran a series of two-level models to explore differences in predictors by care type.
Findings: The strongest predictors of willingness to recommend, controlling for clustering effects, were items that generally reflected interpersonal aspects of care such as nursing and physician behaviors. In the two-level models, predictors of willingness to recommend overlapped across care units, but important differences were noted.
Practice Implications: Our results suggest that hospitals that wish to improve their performance would benefit most from focusing on interpersonal aspects of care. Hospitals that focus resources on improving in these areas, that assess care units separately, and that investigate the meaning and context of survey responses will be most likely to see improvements in satisfaction scores.
W. Dean Klinkenberg, PhD, is Program Evaluator, Klinkenberg Evaluation Services, St. Louis, Missouri. E-mail: email@example.com.
Sarah Boslaugh, PhD, MPH, is Performance Research Analyst, BJC HealthCare, St. Louis, Missouri.
Brian M. Waterman, MPH, is Director of Performance Analytics and Decision Support, BJC HealthCare, St. Louis, Missouri. E-mail: firstname.lastname@example.org.
Koichiro Otani, PhD, is Associate Professor, Division of Public and Environmental Affairs, Indiana University-Purdue University, Fort Wayne, Indiana.
Joe M. Inguanzo, PhD, is President and CEO, Professional Research Consultants, Omaha, Nebraska.
Jan Carolus Gnida, BA, is Director, Client Services, Professional Research Consultants, Omaha, Nebraska.
Wm. Claiborne Dunagan, MD, is Vice President, Quality, BJC Healthcare, St. Louis, Missouri, and Professor of Medicine, Washington University School of Medicine, St. Louis, Missouri.
Disclosure: This project did not receive funds from NIH, Wellcome Trust, Howard Hughes Medical Institute, or any other public or private entity beyond the institutions that the authors are affiliated with.
Because the analyses in this article were conducted as a secondary review of existing publicly reported data that were collected as part of operational quality improvement activities, this study was exempt from institutional review board review.
The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article.