J Clin Epidemiol
Patient perceptions of their health are often inadequately captured and explored on hospital admission where physiologic and other objective measures are the focus of attention. Therefore, we conducted a prospective study to develop and validate measures of several domains of patient-reported health status at the time of admission to a general medicine inpatient service, and to determine the value of these new measures in predicting length of stay (LOS). Within 2 hours of the time that a decision to admit a patient was made, research assistants delivered a structured interview that captured patients' current symptoms, functional status, mood, and perceived health. Interviews were conducted between 8 a.m. and 11 p.m., 5 days per week from July 1996 through June 1997. During this time, there were 3621 unique patients admitted to the medicine service; 2672 (74%) of these patients were eligible for an interview. Eighty-eight percent of the 2672 eligible patients were interviewed. In addition to the patient-reported measures captured through the structured interview, the acute physiology score (APS) of the APACHE II was calculated for all subjects. The internal consistency (i.e., Cronbach's alpha) of the scales was 0.76 or greater and concurrent validity (i.e., correlation) of the patient-reported measures with the APS was 0.01 to 0.13. Overall perceived health was correlated 0.20 to 0.45 with symptoms and functional status, and was correlated 0.07 with the APS. The patient- reported measures performed comparably to the APS in predicting LOS (R- square = 0.08). When the patient-reported measures and the APS were included in the same model, the R-square was 0.14. These analyses suggest that patient-reported measures of health and function on admission hold validity, and that responses to as few as 15 questions can provide data that may help to explain differences in length of a hospital stay.
350, Activities of Daily Living, Affect, APACHE, Attention, Bias (Epidemiology), decision, differences, Female, Health, Health Status, hospital, Human, Indiana, Interviews, Length of Stay, Length of Stay: statistics & numerical data, Male, Medicine, Middle Age, patient, Patient Admission, Patients, Perception, perceptions, physiology, Predictive Value of Tests, Prospective Studies, Questionnaires: standards, Regression Analysis, Reproducibility of Results, Research, ResNet, response, Support,U.S.Gov't,P.H.S.