This paper is in the following e-collection/theme issue:

Non-Randomized Studies (funded, eHealth) (105) Falls Prevention in the Elderly (69) Decision Support for Health Professionals (1185) Machine Learning (1465) Clinical Information and Decision Making (1407) Geroinformatics and Electronic Clinical Information/Decision Making in Geriatrics (20)

Published on in Vol 12 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48128, first published .
Effectiveness of an Emergency Department–Based Machine Learning Clinical Decision Support Tool to Prevent Outpatient Falls Among Older Adults: Protocol for a Quasi-Experimental Study

Effectiveness of an Emergency Department–Based Machine Learning Clinical Decision Support Tool to Prevent Outpatient Falls Among Older Adults: Protocol for a Quasi-Experimental Study

Effectiveness of an Emergency Department–Based Machine Learning Clinical Decision Support Tool to Prevent Outpatient Falls Among Older Adults: Protocol for a Quasi-Experimental Study

Authors of this article:

Daniel J Hekman1 Author Orcid Image ;   Amy L Cochran2 Author Orcid Image ;   Apoorva P Maru1 Author Orcid Image ;   Hanna J Barton3 Author Orcid Image ;   Manish N Shah1 Author Orcid Image ;   Douglas Wiegmann3 Author Orcid Image ;   Maureen A Smith4 Author Orcid Image ;   Frank Liao5 Author Orcid Image ;   Brian W Patterson1 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Journals

  1. Barton H, Maru A, Leaf M, Hekman D, Wiegmann D, Shah M, Patterson B. Academic Detailing as a Health Information Technology Implementation Method: Supporting the Design and Implementation of an Emergency Department–Based Clinical Decision Support Tool to Prevent Future Falls. JMIR Human Factors 2024;11:e52592 View
  2. Hekman D, Barton H, Maru A, Wills G, Cochran A, Fritsch C, Wiegmann D, Liao F, Patterson B. Dashboarding to Monitor Machine-Learning-Based Clinical Decision Support Interventions. Applied Clinical Informatics 2024;15(01):164 View