S Cournane1, D Byrne2, D O'Riordan2, B Fitzgerald2, B Silke2. 1. From the Medical Physics and Bioengineering Department, Division of Internal Medicine and Office of the CEO, St. James's Hospital, Dublin 8, Ireland scournane@stjames.ie. 2. From the Medical Physics and Bioengineering Department, Division of Internal Medicine and Office of the CEO, St. James's Hospital, Dublin 8, Ireland.
Abstract
BACKGROUND: Chronic disabling disease is present in nearly 90% of emergency medical admissions. We have examined its impact on outcomes and costs in one institution, using a database of episodes collected prospectively over 12 years. METHODS: All emergency admissions (66,933 episodes; 36,271 patients) to St James' Hospital over a 12-year period (2002-13) were evaluated in relation to 30-day in-hospital mortality, length of stay (LOS) and hospital costs. Predictor variables (identified univariately) were entered into a multi-variable logistic regression model to predict 30-day in-hospital mortality. The data were also modelled as count data (absolute LOS, total cost) using zero-truncated Poisson regression. RESULTS: Acute illness severity was the best independent predictor of mortality; chronic disabling disease was an independent predictor (P < 0.001) for patients with 4+ disabling conditions. Age, adjusted for other predictors, was only independently predictive of mortality for patient 85+ years. Chronic disabling disease was an independent predictor of LOS increasing linearly with incidence rate ratios of 1.35 (95% CI: 1.29, 1.42), 1.59 (95% CI: 1.51, 1.66), 1.73 (95% CI: 1.65, 1.83) and 1.74 (95% CI: 1.65, 1.84) for those with 1, 2, 3 or 4+ disabling conditions, respectively. Age, as a predictor of LOS was strongly correlated with the presence of disabling disease. Chronic disabling disease independently predicted costs non-linearly; those with 2 or more disabling conditions had particularly high total hospital costs. CONCLUSION: Chronic disabling disease is an independent predictor of hospital LOS and costs in unselected emergency admissions; adjusted for illness severity, it is only a mortality predictor for those with multiple disabling conditions.
BACKGROUND: Chronic disabling disease is present in nearly 90% of emergency medical admissions. We have examined its impact on outcomes and costs in one institution, using a database of episodes collected prospectively over 12 years. METHODS: All emergency admissions (66,933 episodes; 36,271 patients) to St James' Hospital over a 12-year period (2002-13) were evaluated in relation to 30-day in-hospital mortality, length of stay (LOS) and hospital costs. Predictor variables (identified univariately) were entered into a multi-variable logistic regression model to predict 30-day in-hospital mortality. The data were also modelled as count data (absolute LOS, total cost) using zero-truncated Poisson regression. RESULTS: Acute illness severity was the best independent predictor of mortality; chronic disabling disease was an independent predictor (P < 0.001) for patients with 4+ disabling conditions. Age, adjusted for other predictors, was only independently predictive of mortality for patient 85+ years. Chronic disabling disease was an independent predictor of LOS increasing linearly with incidence rate ratios of 1.35 (95% CI: 1.29, 1.42), 1.59 (95% CI: 1.51, 1.66), 1.73 (95% CI: 1.65, 1.83) and 1.74 (95% CI: 1.65, 1.84) for those with 1, 2, 3 or 4+ disabling conditions, respectively. Age, as a predictor of LOS was strongly correlated with the presence of disabling disease. Chronic disabling disease independently predicted costs non-linearly; those with 2 or more disabling conditions had particularly high total hospital costs. CONCLUSION: Chronic disabling disease is an independent predictor of hospital LOS and costs in unselected emergency admissions; adjusted for illness severity, it is only a mortality predictor for those with multiple disabling conditions.
Authors: Julie Redfern; Karice Hyun; Anna Singleton; Nashid Hafiz; Rebecca Raeside; Lissa Spencer; Bridie Carr; Ian Caterson; John Cullen; Cate Ferry; Karla Santo; Alison Hayes; Regina W M Leung; Simon Raadsma; Jessica Swinbourne; Jin G Cho; Meredith King; Mary Roberts; Cindy Kok; Christine Jenkins; Clara Chow Journal: BMJ Open Date: 2019-03-01 Impact factor: 2.692
Authors: Sara Campagna; Alberto Borraccino; Gianfranco Politano; Alfredo Benso; Marco Dalmasso; Valerio Dimonte; Maria Michela Gianino Journal: Int J Health Policy Manag Date: 2021-10-01