Design of a Scalable and Sustainable PREMMplus Patient-Facing App and Implementation in Three Healthcare Settings

The increasing use of genetic testing and the development of syndrome-specific risk models has transformed hereditary cancer risk assessment. We were funded under R01CA132829 awards (4/1/2008–present) to develop the PREMM1,2,6, and PREMM5, risk assessment models, which use family history to identify individuals with a clinically significant risk of carrying a germline pathogenic variant (PV) associated with Lynch syndrome (LS). These models are recommended by national guidelines and widely used. We subsequently developed the PREMMplus model to keep pace with the changing practice of multigene panel testing for several hereditary cancer syndromes. PREMMplus predicts risk of carrying a PV in one of 19 genes implicated in 18 hereditary cancers and was developed and validated from patient data of approximately 30,000 patients. Published in Journal of Clinical Oncology this year, the model demonstrated greater than 90% sensitivity and negative predictive values. Despite progress in the development of better methodologies for risk assessment and the fact that national guidelines recommend familial cancer risk assessment in primary care, these assessments are rarely performed, leaving many patients with hereditary cancer syndromes unidentified. Providers report multiple barriers to conducting risk assessment, including time in the clinical appointment, knowledge of risk criteria, and limited numbers of genetic counselors. Risk assessment that can provide comprehensive and systemic identification of inherited cancer risk, along with clear clinical decision support for providers is a critical unmet need. Further, this risk assessment must be integrable into clinical workflows as well as scalable and sustainable in different clinical settings. To increase access to comprehensive cancer risk assessment, we have developed a patient-facing PREMMplus electronic health application (app). We propose to use an implementation science approach to design and evaluate scalable and sustainable implementation strategies; we will conduct our implementation science study in 5500 patients from 3 different clinical health settings, each of which serves a unique population. We will refine the app and implementation strategies – tailoring them to the unique needs of each site – in a year-long pre-implementation phase. We will use mixed-methods approaches to evaluate the outcomes of this study against multiple strong theoretical frameworks. To accomplish these goals, we propose the following Specific Aims: 1) Evaluate a patient-facing PREMMplus app in different clinical care settings in a large multi-center implementation study, 2) Evaluate barriers and facilitators to systematic hereditary cancer risk assessment and refine long-term strategies for scalability and sustainability, and 3) Build EHR-compatible applications and evaluate their ability to further increase sustainability and scalability. This project will produce an approach to hereditary cancer multigene testing that is scalable and sustainable in many healthcare systems.