Abstract
ObjectivePerformance indicators are used to evaluate the quality of healthcare services. The majority of these, however, are derived solely from administrative data and rarely incorporate feedback from patients who receive services. Recently, our research team developed person-centred quality indicators (PC-QIs), which were co-created with patients. It is unknown whether these PC-QIs are associated with unplanned healthcare use following discharge from hospital.DesignA retrospective, cross-sectional study.MethodsSurvey responses were obtained from April 2014 to September 2020 using the Canadian Patient Experiences Survey - Inpatient Care instrument. Logistic regression models were used to predict the link between eight PC-QIs and two outcomes; unplanned readmissions within 30 days and emergency department visits within 7 days.ResultsA total of 114 129 surveys were included for analysis. 6.0% of respondents (n=6854) were readmitted within 30 days, and 9.9% (n=11 287) visited an emergency department within 7 days of their index discharge. In adjusted models, ‘top box’ responses for communication between patients and physicians (adjusted OR (aOR)=0.82, 95% CI: 0.77 to 0.88), receiving information about taking medication (aOR=0.86, 95% CI: 0.80 to 0.92) and transition planning at hospital discharge (aOR=0.79, 95% CI: 0.73 to 0.85) were associated with lower odds of emergency department visit.Likewise, ‘top box’ responses for overall experience (aOR=0.87, 95% CI: 0.82 to 0.93), communication between patients and physicians (aOR=0.73, 95% CI: 0.67 to 0.80) and receiving information about taking medication (aOR=0.90, 95% CI: 0.83 to 0.98), were associated with lower odds of readmission.ConclusionsThis study demonstrates that patient reports of their in-hospital experiences may have value in predicting future healthcare use. In developing the PC-QIs, patients indicated which elements of their hospital care matter most to them, and our results show agreement between subjective and objective measures of care quality. Future research may explore how current readmission prediction models may be augmented by person-reported experiences.
Subject
Public Health, Environmental and Occupational Health,Health Policy,Leadership and Management
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