Predicting hospitalisations related to ambulatory care sensitive conditions with machine learning for population health planning: derivation and validation cohort study

Predicting hospitalisations related to ambulatory care sensitive conditions with machine learning for population health planning: derivation and validation cohort study

Objective: To predict older adults’ risk of avoidable hospitalisation related to ambulatory care sensitive conditions (ACSC) using machine learning applied to administrative health data of Ontario, Canada. Design, setting and participants: A retrospective cohort study was conducted on a large cohort...

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Bibliographic Details
Main Authors: Yi, Seung Eun, Harish, Vinyas, Gutierrez, Jahir, Ravaut, Mathieu, Kornas, Kathy, Watson, Tristan, Poutanen, Tomi, Ghassemi, Marzyeh, Volkovs, Maksims, Rosella, Laura C.
Other Authors: School of Computer Science and Engineering
Format: Journal Article
Language:English
Published: 2022
Subjects:
Engineering::Computer science and engineering
Administrative Health Data
Ambulatory Care
Online Access:https://hdl.handle.net/10356/163265

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