Abstract
464 Background: At any given health system, there are often quality improvement (QI) projects without enough manpower to complete the work, and students and trainees who are looking for projects to work on but can’t find any. The question becomes how we connect these two groups in a win-win situation. Many job search websites use a “matching” function in which profiles of applicants are matched with requirements from employers to make connections. Our goal is to apply a similar software/data-basing solution to QI projects in healthcare systems to improve project completion rates, increase QI experience among medical students, residents, and fellows, and improve continuity of projects. Methods: We created a dual facing database, with one branch aimed at collecting projects, and the other side aimed at recruiting trainees/students. Faculty or QI departments approach the project side and are asked to provide the following types of data about their QI project: field, clinical vs basic, onsite vs virtual, role of the trainee, timing (business hours or flexible), IRB approval, description, and main point of contact. Trainees who are interested in matching a project, fill out a set of profile questions that mirror the project parameters. Trainees and projects are matched in an algorithmic order based on prioritization we have selected in discussion with faculty and student interests. One key is that the project point of contact is NOT made available until after a successful “match” to avoid “carpet bomb” emailing of faculty members. In order to fill the database we have networked with physicians, department chairs, interest group listservs, and chief residents across our hospital and medical school. Results: In our first year’s pilot run we collected 17 projects, and had profound student interest with 70 profiles filled. We limited the number of matched projects to just 5 that best fit, and received positive feedback from students and mentors. Since then we have grown the database to 47 projects and 153 students/trainee profiles. These initial promising results have also prompted the creation of a new elected position in the medical school for two Research VP’s in each class. Conclusions: We have built a clear proof of concept that virtual match making for QI projects can close the gap between unfilled projects, and trainees seeking opportunities. Although the metrics suggest that trainees seeking research are far outpacing available projects, we believe that far more projects currently exists, and a major area of improvement will be to continue to bring visibility to the database. Nonetheless without acquiring any additional funding or manpower, we are able to increase the scholarly profiles of trainees, and overall QI productive output at our institution.
Published Version
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