Follow-up Interactive Long-Term Expert Ranking (FILTER): a crowdsourcing platform to adjudicate risk for survivorship care

OBJECTIVES: To develop an online crowdsourcing platform where oncologists and other survivorship experts can adjudicate risk for complications in follow-up. MATERIALS AND METHODS: This platform, called Follow-up Interactive Long-Term Expert Ranking (FILTER), prompts participants to adjudicate risk between each of a series of pairs of synthetic cases. The Elo ranking algorithm is used to assign relative risk to each synthetic case. RESULTS: The FILTER application is currently live and implemented as a web application deployed on the cloud. DISCUSSION: While guidelines for following cancer survivors exist, refinement of survivorship care based on risk for complications after active treatment could improve both allocation of resources and individual outcomes in long-term follow-up. CONCLUSION: FILTER provides a means for a large number of experts to adjudicate risk for survivorship complications with a low barrier of entry.