Dataset Information

Lessons learned from an enterprise-wide clinical datathon.

ABSTRACT: In 2020, Baylor College of Medicine held a datathon to inform potential users of a new data warehouse, allow users to address clinical questions, identify warehouse capabilities and limitations, foster collaborations, and engage trainees. Senior faculty selected proposals based on feasibility and impact. Selectees worked with Information Technology for 2 months and presented findings. A survey of participants showed diverse levels of experience, high perceived value of the datathon, high rates of collaboration, and significant increases in knowledge. A datathon can promote familiarity with a new data warehouse, guide data warehouse improvement, and promote collaboration.

SUBMITTER: Zimolzak AJ

PROVIDER: S-EPMC9794964 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Lessons learned from an enterprise-wide clinical datathon.

Zimolzak Andrew J AJ Davila Jessica A JA Punugoti Vamshi V Balasubramanyam Ashok A Klotman Paul E PE Petersen Laura A LA Rochat Ryan H RH Liao Gloria G Laubscher Rory R RR Leiber Lee L Amos Christopher I CI

Journal of clinical and translational science 20220824 1

In 2020, Baylor College of Medicine held a datathon to inform potential users of a new data warehouse, allow users to address clinical questions, identify warehouse capabilities and limitations, foster collaborations, and engage trainees. Senior faculty selected proposals based on feasibility and impact. Selectees worked with Information Technology for 2 months and presented findings. A survey of participants showed diverse levels of experience, high perceived value of the datathon, high rates o ...[more]

PMID: 36590351

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Project description:IntroductionThe United States Veterans Health Administration (VHA) Office of Rural Health funds Enterprise-Wide Initiatives (system-wide initiatives) to spread promising practices to rural Veterans. The Office requires that evaluations of Enterprise-Wide Initiatives use the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. This presents a unique opportunity to understand the experience of using RE-AIM across a series of evaluations. The authors conducted a study to document the benefits and pitfalls of using RE-AIM, capture the variety of ways that the team captured the elements of RE-AIM, and develop recommendations for the future use of RE-AIM in evaluation.Materials and methodsThe authors first conducted a document review to capture pre-existing information about how RE-AIM was used. They subsequently facilitated two focus groups to gather more detailed information from team members who had used RE-AIM. Finally, they used member-checking throughout the writing process to ensure accurate data representation and interpretation and to gather additional feedback.ResultsFour themes emerged from the document review, focus groups, and member checking. RE-AIM: provides parameters and controls the evaluation scope, "buckets" are logical, plays well with other frameworks, and can foster collaboration or silo within a team. Challenges and attributes for each RE-AIM dimension were also described.DiscussionOverall, participants reported both strengths and challenges to using RE-AIM as an evaluation framework. The overarching theme around the challenges with RE-AIM dimensions was the importance of context. Many of these benefits and challenges of using RE-AIM may not be unique to RE-AIM and would likely occur when using any prescribed framework. The participants reported on the RE-AIM domains in a variety of ways in their evaluation reports and were not always able capture data as originally planned. Recommendations included: start with an evaluation framework (or frameworks) and revisit it throughout the evaluation, consider applying RE-AIM PRISM (Practical Robust Implementation Framework) to gain a broader perspective, and intentionally integrate quantitative and qualitative team members, regardless of the framework used.

Dataset Information

Lessons learned from an enterprise-wide clinical datathon.

Publications

Lessons learned from an enterprise-wide clinical datathon.

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