Publication Type
Journal Article
Version
publishedVersion
Publication Date
5-2023
Abstract
In a prior practice and policy article published in Healthcare Science, we introduced the deployed application of an artificial intelligence (AI) model to predict longer-term inpatient readmissions to guide community care interventions for patients with complex conditions in the context of Singapore's Hospital to Home (H2H) program that has been operating since 2017. In this follow on practice and policy article, we further elaborate on Singapore's H2H program and care model, and its supporting AI model for multiple readmission prediction, in the following ways: (1) by providing updates on the AI and supporting information systems, (2) by reporting on customer engagement and related service delivery outcomes including staff-related time savings and patient benefits in terms of bed days saved, (3) by sharing lessons learned with respect to (i) analytics challenges encountered due to the high degree of heterogeneity and resulting variability of the data set associated with the population of program participants, (ii) balancing competing needs for simpler and stable predictive models versus continuing to further enhance models and add yet more predictive variables, and (iii) the complications of continuing to make model changes when the AI part of the system is highly interlinked with supporting clinical information systems, (4) by highlighting how this H2H effort supported broader Covid-19 response efforts across Singapore's public healthcare system, and finally (5) by commenting on how the experiences and related capabilities acquired from running this H2H program and related community care model and supporting AI prediction model are expected to contribute to the next wave of Singapore's public healthcare efforts from 2023 onwards. For the convenience of the reader, some content that introduces the H2H program and the multiple readmissions AI prediction model that previously appeared in the prior Healthcare Science publication is repeated at the beginning of this article.
Keywords
AI, artificial intelligence, BRAIN, Business Research Analytics Insight Network platform, H2H, Hospital to Home program, NEHR, National Electronic Health Records system
Discipline
Asian Studies | Databases and Information Systems | Health Information Technology
Research Areas
Information Systems and Management
Publication
Health Care Science
First Page
1
Last Page
11
ISBN
2771-1757
Identifier
10.1002/hcs2.44
Publisher
Wiley Open Access
Embargo Period
5-14-2023
Citation
ABISHEGANADEN, John; LEE, Kheng Hock; LOW, Lian Leng; SHUM, Eugene; GOH, Han Leong; ANG, Christine Gia Lee; WEE, Adny An Ta; and MILLER, Steven M..
Lessons learned from the hospital to home community care program in Singapore and the supporting AI multiple readmissions prediction model. (2023). Health Care Science. 1-11.
Available at: https://ink.library.smu.edu.sg/sis_research/7832
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional URL
https://doi.org/10.1002/hcs2.44
Included in
Asian Studies Commons, Databases and Information Systems Commons, Health Information Technology Commons