%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 22
%N 10
%P e21367
%T Health Outcomes from Home Hospitalization: Multisource Predictive Modeling
%A Calvo,Mireia
%A González,Rubèn
%A Seijas,Núria
%A Vela,Emili
%A Hernández,Carme
%A Batiste,Guillem
%A Miralles,Felip
%A Roca,Josep
%A Cano,Isaac
%A Jané,Raimon
%+ Hospital Clínic de Barcelona, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona (UB), Villarroel 170, Barcelona, 08036, Spain, 34 932275540, ISCANO@clinic.cat
%K home hospitalization
%K health risk assessment
%K predictive modeling
%K chronic care
%K integrated care
%K modeling
%K hospitalization
%K health risk
%K prediction
%K mortality
%K clinical decision support
%D 2020
%7 7.10.2020
%9 Original Paper
%J J Med Internet Res
%G English
%X 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 Clínic 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. 
%M 33026357
%R 10.2196/21367
%U http://www.jmir.org/2020/10/e21367/
%U https://doi.org/10.2196/21367
%U http://www.ncbi.nlm.nih.gov/pubmed/33026357