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Supporting goal-oriented care using mobile technology: Findings from the mixed-methods trial of the ePRO tool.
Annals of Family Medicine
|January 25, 2024
Summary
Implementing an electronic Patient Reported Outcome (ePRO) tool in primary care for older adults faced recruitment challenges. Meaningfulness of the technology, not just its features, significantly impacted its adoption and perceived value.
Area of Science:
- Gerontology and Primary Care
- Digital Health Implementation
- Health Services Research
Background:
- Goal-oriented care models are increasingly used for older adults with multimorbidity.
- Implementation of these models is challenging, with digital health solutions offering potential but requiring evaluation.
- Electronic Patient Reported Outcome (ePRO) tools aim to support goal-oriented care delivery.
Purpose of the Study:
- To evaluate the implementation and effectiveness of an ePRO mobile application and portal system.
- To assess the feasibility and impact of ePRO in inter-professional primary care practices for older adults with complex needs.
Main Methods:
- A multi-method pragmatic randomized control trial with a stepped-wedge design over 15 months.
- Involved 6 primary care practices in Ontario, targeting 176 older adults with complex care needs.
- Utilized the Assessment of Quality of Life-4D for outcomes and ethnographic methods (observations, interviews) for implementation insights, analyzed via linear and qualitative methods.
Main Results:
- Recruitment challenges led to fewer sites (n=6) and participants (n=45) than planned, limiting definitive quality of life impact assessment.
- Analysis trends indicated a potential decrease in patient quality of life during both control and intervention periods.
- Ethnographic data highlighted that the perceived meaningfulness of the ePRO technology to users' lives and chronic disease management influenced adoption and value.
Conclusions:
- Implementation faced broad and unexpected challenges, particularly in aligning the technology's meaningfulness across diverse users.
- The intervention's adaptability and the need for more dynamic trial methodologies are suggested.
- Ethnographic data is crucial for understanding the underlying mechanisms driving digital health innovation adoption.
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