Nearly half of all Americans will develop cancer at least once in their lifetime. Through improved screening and treatments, the number of cancer survivors is reaching all-time highs. However, survivorship care plans (SCPs) are inconsistently used, denying many survivors access to critical information. This study used 46,408 SCPs generated from 2007 to 2016 and applied machine learning to identify predictors of SCP creation, including cancer type, type of physician, and healthcare center where they received care, as well as regional variations in care plan creation. Identifying these disparities in SCP use is a critical first step in efforts toward expanding access to survivorship care planning. Using a convenience sample of survivors, it is possible to model the factors that predict generation of SCPs either by the survivor or by a healthcare provider. This study identifies several important disparities both survivor intrinsic such as cancer type, as well as treatment associated and geographic differences in SCP generation. Identifying these disparities at the national level across cancer types will allow for more targeted recommendations to improve SCP creation and dissemination in underserved groups.
Keywords: cancer; cancer survivor; health disparities; survivorship; survivorship care plans.
Copyright © 2020 Benci, Vachani, Hampshire, Bach, Arnold-Korzeniowski, Metz and Hill-Kayser.