Analysis of Family Health History Based Risk Assessment Algorithms: Classification and Data Requirements

Abstract Family Health History (FHH) is a valuable and potentially low-cost tool for risk assessment and diagnosis in patient-centered healthcare. In this study, we identified and analyzed existing FHH-based risk assessment algorithms (RAAs) for cardio-vascular disease (CVD) and colorectal cancer (CRC) to guide implementers of electronic health record (EHR) sys-tems regarding the data requirements for computing risk us-ing these algorithms. We found a core set of data elements that are required by most RAAs. While some of these data elements are available in EHR systems, the patients can be empowered to contribute the remainder. Keywords: Family history, risk assessment algorithms, data requirements. Introduction FHH-based risk assessment is not consistently used in primary care [1]. One of the reasons for this is that the data needed for calculating risk is not readily available, accurate, complete, or in a format that can be automatically processed by a computer. The goal of this study was to review and analyze FHH-based RAAs for a set of prevalent conditions that are genetically predisposed. The specific aims for the review are: 1) To iden-tify the core set of data elements required to compute the dis-ease-specific risk based on the RAAs. The set of data ele-ments may be used to guide and enhance the data collection process by EHR systems; 2) To classify the RAAs based on predefined criteria. This classification aims at providing guid-ance for prioritizing the implementation of RAAs.