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pmid: 12069351
The purpose of this study was to determine which Department of Defense (DOD) active duty patient sociodemogpraphic, health status, geographic location, and utilization factors, predict overall patient satisfaction with health care in military facilities. A theoretical framework developed from patient satisfaction and social identity theories and from previous empirical findings was used to develop a model to predict patient satisfaction and delineate moderating variables. The major finding indicated in this study was the significance of patients’ characteristics in moderating their satisfaction. Principal components factor analysis and hierarchical linear regression revealed that patient specific factors predicted patients’ satisfaction after controlling for factors depicting patients’ evaluations of health system characteristics. Patient specific factors provided added, although very minimal, explanatory value to the determination of patients’ satisfaction. The study findings can aid in the development of targeted, objectively prioritized programs of improvement and marketing by ranking variables using patients’ passively derived importance schema.
Communication, Hospitals, Military, Health Services Accessibility, United States, Appointments and Schedules, Health Benefit Plans, Employee, Military Personnel, Socioeconomic Factors, Patient Satisfaction, Surveys and Questionnaires, Linear Models, Health Status Indicators, Humans, Demography, Quality Indicators, Health Care
Communication, Hospitals, Military, Health Services Accessibility, United States, Appointments and Schedules, Health Benefit Plans, Employee, Military Personnel, Socioeconomic Factors, Patient Satisfaction, Surveys and Questionnaires, Linear Models, Health Status Indicators, Humans, Demography, Quality Indicators, Health Care
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 56 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |