Evaluation of the implementation of the Expanded Prostate Cancer Index Composite for Clinical Practice (EPIC-CP) across the province of Ontario.
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188 Background: EPIC-CP, a prostate cancer Patient-Reported Outcome Measure (PROM), was implemented across Ontario’s 14 Regional Cancer Centres (RCCs) using a phased roll-out approach. This approach enabled implementation and evaluation in enrolled centres, with the aim of using the results to improve implementation in both the enrolled regions and those preparing to implement. The objective was to analyze formative evaluation results and identify opportunities for improvement in implementation. Methods: Surveys were developed for patients and providers to capture attitudes and experiences regarding EPIC-CP. Data collection was initiated approximately three months post-implementation, with three RCCs evaluated concurrently in ‘waves’. Descriptive analyses were performed to summarize the survey data. Results: To date, nine RCC’s have completed the formative evaluation with 104 providers and 517 patients responding to the surveys. Providers reported challenges with data flow (44% always or mostly received EPIC-CP results in a timely manner) and with responding to specific symptoms (27% and 29% reported that they are very confident in treating/managing sexual function and emotional issues respectively). Although 54% of providers acknowledged that using EPIC-CP should be part of their role, 46% indicated that it has added little or no value to their practice. In contrast, 75% of patients reported that EPIC-CP made it easier to communicate symptoms to their care team, which suggests that patients find EPIC adds value. Patient comments identified gaps such as educational resources for symptom management and additional support when completing the PROM. Conclusions: Opportunities to improve the patient and provider experience with EPIC-CP include: developing educational resources, addressing issues with technology and data flow, and identifying factors that influence provider uptake. These results will be used to design resources and support to improve the process for implementing EPIC-CP in later waves.
