Stephen C. Matchett

Establishing reliability and validity of the critical care family satisfaction survey.

ObjectiveTo develop and validate the Critical Care Family Satisfaction Survey as a proxy for patient satisfaction. DesignInstrument validation study. Setting and Time FrameThe Medical Intensive Care, Shock Trauma, Acute Coronary Care, Central Nervous System, Surgical Intensive Care, and Special Care units of Lehigh Valley Hospital (Allentown, PA), for the period December 1997 through September 1998. Patients/ParticipantsOne family member for each of 237 critical care patients. Intervention(s)Content and construct validity were examined on 37 items and 6 constructs thought to measure family satisfaction with the quality of critical care in hospitals. Initially, 14 items and 1 construct were removed from the questionnaire based on this analysis. It was then administered to 237 family members. Measurements and Main Results Factor analysis and confirmatory factor analysis using path models were performed. Internal consistency using Pearson correlations and Cronbach’s alpha, and discriminant validation were also calculated. Factor analysis yielded a single eigenvalue >1 (3.712), whereas confirmatory factor analysis led to the final instrument being reduced to 20 items and 5 subscale constructs. One subscale (“Comfort”) performed poorly, indicating the possible need for a four-factor model. Subsequently, internal consistency assessed by Cronbach’s alpha was 0.9101 for the five-factor model and 0.9327 for the four-factor model. Subscale correlations were no lower than 0.750 for the five-factor model and 0.856 for the four-factor model. ConclusionsThis study provides support that the Critical Care Family Satisfaction Survey—which yields five subscales, “Assurance,” “Information,” “Proximity,” “Support,” and “Comfort”—is reliable and valid. Using five constructs rather than four is recommended because of the following: a) the internal consistency loss of 0.0226 for the “Comfort” subscale is not enough to warrant its removal, b) a four-factor questionnaire can be administered and totaled independently of this subscale, c) the need for the fifth construct is indicated by this study’s results, and d) including the extra data may allow for more detailed analysis.

THE CLINICAL MANAGEMENT DATABASE

The clinical management database utilizes ICU patient data in aggregate to examine quality of care and resource utilization at the population level. As clinicians become accountable for efficiency and quality, this type of database is essential to understand the results of care. This article reviews the challenges of evaluating cost and quality including the potential for bias and measurement error. A practical approach to starting a database is outlined with examples and suggestions.