@Article{info:doi/10.2196/21367,
author="Calvo, Mireia
and Gonz{\'a}lez, Rub{\`e}n
and Seijas, N{\'u}ria
and Vela, Emili
and Hern{\'a}ndez, Carme
and Batiste, Guillem
and Miralles, Felip
and Roca, Josep
and Cano, Isaac
and Jan{\'e}, Raimon",
title="Health Outcomes from Home Hospitalization: Multisource Predictive Modeling",
journal="J Med Internet Res",
year="2020",
month="Oct",
day="7",
volume="22",
number="10",
pages="e21367",
keywords="home hospitalization; health risk assessment; predictive modeling; chronic care; integrated care; modeling; hospitalization; health risk; prediction; mortality; clinical decision support",
abstract="Background: Home hospitalization is widely accepted as a cost-effective alternative to conventional hospitalization for selected patients. A recent analysis of the home hospitalization and early discharge (HH/ED) program at Hospital Cl{\'i}nic de Barcelona over a 10-year period demonstrated high levels of acceptance by patients and professionals, as well as health value-based generation at the provider and health-system levels. However, health risk assessment was identified as an unmet need with the potential to enhance clinical decision making. Objective: The objective of this study is to generate and assess predictive models of mortality and in-hospital admission at entry and at HH/ED discharge. Methods: Predictive modeling of mortality and in-hospital admission was done in 2 different scenarios: at entry into the HH/ED program and at discharge, from January 2009 to December 2015. Multisource predictive variables, including standard clinical data, patients' functional features, and population health risk assessment, were considered. Results: We studied 1925 HH/ED patients by applying a random forest classifier, as it showed the best performance. Average results of the area under the receiver operating characteristic curve (AUROC; sensitivity/specificity) for the prediction of mortality were 0.88 (0.81/0.76) and 0.89 (0.81/0.81) at entry and at home hospitalization discharge, respectively; the AUROC (sensitivity/specificity) values for in-hospital admission were 0.71 (0.67/0.64) and 0.70 (0.71/0.61) at entry and at home hospitalization discharge, respectively. Conclusions: The results showed potential for feeding clinical decision support systems aimed at supporting health professionals for inclusion of candidates into the HH/ED program, and have the capacity to guide transitions toward community-based care at HH discharge. ",
issn="1438-8871",
doi="10.2196/21367",
url="http://www.jmir.org/2020/10/e21367/",
url="https://doi.org/10.2196/21367",
url="http://www.ncbi.nlm.nih.gov/pubmed/33026357"
}