Accepted for/Published in: JMIR Formative Research
Date Submitted: Oct 11, 2022
Date Accepted: Mar 28, 2023
A Novel Mobile App to Identify Multimorbid Patients in the Emergency Setting: Development and Feasibility
ABSTRACT
Background:
Multimorbidity is associated with increased risk of poor surgical outcomes among older adults.
Objective:
We created the Multimorbid Patient Identifier App (MMApp) to easily identify multimorbid patients, and tested its feasibility for use in future research and to eventually guide clinical decision making.
Methods:
We adapted a claims-based definition of multimorbidity for clinical use via a modified-Delphi method and developed MMApp. Ten residents input five hypothetical emergency general surgery patient scenarios, common among older adults, into the MMApp and examined MMApp test characteristics. To assess model feasibility, we compared the mean task completion by scenario to that of the American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator (ACS-NSQIP-SRC) using paired T-tests. We measured MMApp usability via a 17-item questionnaire.
Results:
There was no significant difference in the task completion time between the MMApp and the ACS NSQIP-SRC for scenarios A (86.3 vs 74.3 seconds, p = 0.851) or C (58.4 vs 68.9 seconds, p = 0.064), MMapp took less time for scenarios B (76.1 vs 87.4 seconds, p = 0.031) and E (20.7 vs 73 seconds, p < 0.001), and more time for scenario D (78.8 vs 58.5 seconds, p = 0.017). The MMApp identified multimorbidity with 96.7% sensitivity and 95% specificity. User feedback was positive.
Conclusions:
The MMApp did not require significantly more time to complete than the ACS NSQIP-SRC for most scenarios, with mean user times well under two minutes. Feedback was overall positive from residents regarding the usability and usefulness of this app. It would be feasible to use MMApp to identify multimorbid patients in the EGS setting for research and eventual clinical use.
Citation
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