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Updated: May 26, 2025

Study of Experimental Organ Donation Models for Lung Transplantation
Published on: March 15, 2024
Feasibility and Optimization of Donation Advisor: a Decision Support Tool for Deceased Organ Donation and
Sonny Dhanani1,2, Rashi Ramchandani2, Jill Allan3
1Division of Critical Care, Department of Pediatrics, The Children's Hospital of Eastern Ontario, University of Ottawa, Ottawa, ON, Canada.
Background:
This study aimed to evaluate the ability of Donation Advisor (DA), a validated clinical decision support tool that uses continuous monitoring, variability analysis, and predictive models, to (i) predict likelihood of successful donation after circulatory determination of death (DCD) before withdrawal of life-sustaining measures (WLSM), and (ii) describe ischemia during WLSM in DCD patients.
Methods:
Eligible patients were screened at the 5 sites where DA was implemented. DA reports were generated in real time but shown to clinicians after the donation was complete (noninterventional). Clinicians were interviewed for improvement of the tool.
Results:
We enrolled 34 donor patients in the study; 27 had DCD attempts and 20 proceeded to organ recovery. DA reports were generated before WLSM in all 27 attempted DCD patients (100%) while post-WLSM ischemia reports were generated in 26 of 27 DCD attempts (96%). Nineteen of 34 involved clinicians completed interviews, 10 from intensive care, and 9 from transplantation team members. Following a user-centered design approach, feedback was used to create 5 versions. Revisions included additions, removals, clarifications, and formatting changes; the number of revisions decreased with each amendment. The report's predictive scores were found to be useful by most practitioners (83%). We identified barriers and drivers to use the report in future practice, some of which may be addressed through improved education and awareness.
Conclusions:
DA can be deployed in real time during the DCD process. The usefulness and usability of the DA report has improved through user feedback; both barriers and drivers to implementation exist.
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