Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Apr 4, 2022
Open Peer Review Period: Apr 4, 2022 - May 30, 2022
Date Accepted: Sep 25, 2022
(closed for review but you can still tweet)
Managing Critical Patient-Reported Outcome Measures in Oncology Settings: System Development and Retrospective Study
ABSTRACT
Background:
Remote monitoring programs based on the collection of Patient-Reported Outcomes (PROs) data are increasing in adoption within oncology practices.
Objective:
In a first-of-its-kind study, we sought to design, describe and evaluate a closed-loop alerting and communication system focused on managing PROs related alerts in cancer care.
Methods:
We designed and developed a novel solution using agile software development methodology by incrementally building new capabilities. We evaluated these new features using participatory design and the Fit between Individuals, Task, and Technology (FITT) framework.
Results:
Eight questionnaires were implemented using alerting features resulting in an alert rate of 7.8% (36,838/470,841) with 13.2% (10,965/82,544) patients triggering at least one alert. Alerts were reviewed by 501 staff spanning across 191 care teams. 100% of the alerts were reviewed with an average response time of 1 hour during standard business hours. The most severe (red) alerts were documented 57% of the time, compared to unlabeled alerts 28%, signaling clinician concordance with alert thresholds.
Conclusions:
A PRO-based alert and communication system has some initial benefits in reviewing clinically meaningful PROs data in a reasonable amount of time. We discuss key system design considerations, workflow integration and mitigating potential impact on care team burden. Introduction of a PROs based alert and communication system provides a reliable mechanism for care teams to review and respond to patient symptoms quickly. The system was standardized across many different oncology settings, demonstrating system flexibility. Future studies will focus on formally evaluating system usability through qualitative methods.
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