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JOURNAL ARTICLE
MULTICENTER STUDY
Patient satisfaction data as a quality indicator: a tale of two emergency departments.
Academic Emergency Medicine 2003 March
OBJECTIVE: Patient satisfaction is a commonly measured indicator of quality emergency care. However, the existing empirical literature on emergency department (ED) patient satisfaction provides little guidance on how to analyze, interpret, and use data obtained in the clinical setting. Using two EDs as examples, the authors describe practical strategies designed to identify priority areas for potential improvement.
METHODS: The authors used a cross-sectional, observational design. All patients who presented for emergency care during the designated time periods were eligible. Patients were randomly selected, contacted by telephone, and surveyed using three measures of global satisfaction, 23 perceived quality-of-care indicators, and six perceived wait times. Descriptive statistics were calculated. Comparisons were made of each of the perceived care and wait time indicators against explicitly defined acceptability criteria to determine satisfiers/dissatisfiers. Each indicator was correlated with the three global satisfaction indices. The authors integrated results obtained from applying the acceptability criteria with those obtained from the correlations to yield priority indicators for remediation and maintenance strategies.
RESULTS: For hospitals A and B, respectively, 15 (52%) and 16 (55%) of perceived care and wait time indicators failed to meet acceptability criteria. Using the correlations with overall satisfaction, the authors further narrowed the priority areas for remediation to six indicators for hospital A and three indicators for hospital B. One maintenance indicator was revealed for hospital A and four for hospital B.
CONCLUSIONS: A combination of applying explicit acceptability criteria to descriptive statistics and using correlation coefficients with overall satisfaction can help to maximize the usefulness of patient satisfaction data by uncovering priority areas. These priority areas were broken down into maintenance and remediation indicators and were found to vary considerably depending on the hospital in question. Such strategies can help to refine performance improvement efforts by targeting those domains with the greatest impact on overall satisfaction.
METHODS: The authors used a cross-sectional, observational design. All patients who presented for emergency care during the designated time periods were eligible. Patients were randomly selected, contacted by telephone, and surveyed using three measures of global satisfaction, 23 perceived quality-of-care indicators, and six perceived wait times. Descriptive statistics were calculated. Comparisons were made of each of the perceived care and wait time indicators against explicitly defined acceptability criteria to determine satisfiers/dissatisfiers. Each indicator was correlated with the three global satisfaction indices. The authors integrated results obtained from applying the acceptability criteria with those obtained from the correlations to yield priority indicators for remediation and maintenance strategies.
RESULTS: For hospitals A and B, respectively, 15 (52%) and 16 (55%) of perceived care and wait time indicators failed to meet acceptability criteria. Using the correlations with overall satisfaction, the authors further narrowed the priority areas for remediation to six indicators for hospital A and three indicators for hospital B. One maintenance indicator was revealed for hospital A and four for hospital B.
CONCLUSIONS: A combination of applying explicit acceptability criteria to descriptive statistics and using correlation coefficients with overall satisfaction can help to maximize the usefulness of patient satisfaction data by uncovering priority areas. These priority areas were broken down into maintenance and remediation indicators and were found to vary considerably depending on the hospital in question. Such strategies can help to refine performance improvement efforts by targeting those domains with the greatest impact on overall satisfaction.
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