BackgroundHospital mortality, readmission and length of stay (LOS) are commonly used measures for quality of care. We aimed to disentangle the correlations between these interrelated measures and propose a new way of combining them to evaluate the quality of hospital care.MethodsWe analyzed administrative data from the Global Comparators Project from 26 hospitals on patients discharged between 2007 and 2012. We correlated standardized and risk-adjusted hospital outcomes on mortality, readmission and long LOS. We constructed a composite measure with 5 levels, based on literature review and expert advice, from survival without readmission and normal LOS (best) to mortality (worst outcome). This composite measure was analyzed using ordinal regression, to obtain a standardized outcome measure to compare hospitals.ResultsOverall, we observed a 3.1% mortality rate, 7.8% readmission rate (in survivors) and 20.8% long LOS rate among 4,327,105 admissions. Mortality and LOS were correlated at the patient and the hospital level. A patient in the upper quartile LOS had higher odds of mortality (odds ratio = 1.45, 95% confidence interval 1.43–1.47) than those in the lowest quartile. Hospitals with a high standardized mortality had higher proportions of long LOS (r = 0.79, p < 0.01). Readmission rates did not correlate with either mortality or long LOS rates. The interquartile range of the standardized ordinal composite outcome was 74–117. The composite outcome had similar or better reliability in ranking hospitals than individual outcomes.ConclusionsCorrelations between different outcome measures are complex and differ between hospital- and patient-level. The proposed composite measure combines three outcomes in an ordinal fashion for a more comprehensive and reliable view of hospital performance than its component indicators.
Tracheal cancer is under-recognized and under-treated. Early diagnosis, access to interventional bronchoscopy, and surgical treatment in specialist units may improve the survival of patients with this condition.
Mortality following head and neck cancer surgery shows variation across different resection strata. We propose an Informatics-based Framework for Outcomes Surveillance (IFOS) in Head and Neck Surgery for perpetual quality assurance, using the local hospital coding data or its collated destination, the national administrative dataset.
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