Follow-up Interactive Long-Term Expert Ranking (FILTER): a crowdsourcing platform to adjudicate risk for survivorship care
Plain-language summary
The authors built an online platform called FILTER that lets oncologists and other survivorship experts judge which cancer survivors are at higher risk of complications during long-term follow-up. Participants compare pairs of synthetic patient cases, and an Elo ranking algorithm converts these head-to-head judgments into relative risk scores. The tool is live as a cloud-based web application and is intended to help tailor survivorship care to individual risk, which the authors suggest could improve both resource allocation and patient outcomes.
Read the full paper (DOI: 10.1093/jamiaopen/ooab090).
This is a plain-language summary written for discoverability; the authoritative version is the published paper. Part of Travis Osterman's peer-reviewed publications.