Patient Satisfaction and Organizational Impact: A Hierarchical Linear Modeling Approach.
Health Marketing Quarterly
Taylor & Francis
This article presents the rationale for using multilevel analysis to address the broad environmental contexts in patient satisfaction research. This study utilized patient satisfaction data and the American Hospital Association Hospital Guide Book (2004). This study found significant contributions of individual patient attribute reactions (nursing care, physician care, etc.), and also clearly demonstrated hospital-level effects and cross-level interactions on patient satisfaction. Thus, it is clear that patient satisfaction is not solely explained by patients' attribute reactions and their demographic variables, but is also explained by patients' hospital levels. This approach would offer additional understanding in patient satisfaction research.
Health facility administration, Interviewing, Job satisfaction, Questionnaires, Telephone, Wages, Descriptive statistics, Age distribution (Demography), Factor analysis, Length of stay in hospitals, Patient satisfaction, Scale analysis (Psychology), Sex distribution (Demography), Patients' attitudes, Statistical models
Public Affairs, Public Policy and Public Administration
Koichiro Otani, B. Joon Kim, Brian Waterman, Sarah Boslaugh, W. Dean Klinkenberg, and W. Clainborne Dunagan (2012).
Patient Satisfaction and Organizational Impact: A Hierarchical Linear Modeling Approach.. Health Marketing Quarterly.29 (3), 256-269. Taylor & Francis.