Identifying the >1 million individuals with familial hypercholesterolemia (FH) in the U.S. will lead to reduced morbidity and mortality due to atherosclerotic cardiovascular disease. To achieve population health impact of identifying individuals with this genetic condition, systematic cascade testing to identify all affected at-risk relatives must also commence. However, both under-identification of index patients, and low uptake of cascade testing, limits the potential population health impact. Therefore, this proposal will address these critical gaps in translational cardiovascular medicine by studying 1) innovative index patient identification methods via both phenotypic algorithms that utilize electronic health record (EHR) data, and genomic analysis of next-generation sequencing data; 2) the effectiveness of patient-centered approaches for family communication assistance to promote patient activation toward cascade testing uptake; and 3) feasibility, acceptability, and cost of these methods using an implementation science framework towards the goal of defining best practices for FH identification and cascade testing. This study is a collaboration between Geisinger and The FH Foundation. We will utilize Geisinger's MyCode Community Health Initiative (MyCode), a biobank linked to the EHR available for research, which has >200,000 patient-participants enrolled with exome sequencing on ~93,000, with tens of thousands more anticipated over the course of this study.
In Aim 1, we will evaluate FH identification methods, including two phenotype-based algorithms, which will be applied to the EHR of MyCode participants. We will also assess the ability to detect FH through exome sequencing in the same cohort and will critically evaluate the comparative positive and negative predictive values of each method. By utilizing interrelatedness data available via MyCode, high-throughput phenotyping on relatives' EHR data will be performed to augment each algorithm's performance.
In Aim 2, we will utilize design thinking to develop novel, patient-centered family communication and cascade testing strategies to activate patients to uptake cascade testing, the primary outcome of Aim 2, which will be measured by laboratory records from Invitae and by relatives' self-report. These novel approaches will be presented to FH probands in a prospective, observational comparative effectiveness study.
In Aim 3, guided by Proctor's conceptual model for implementation research, we will evaluate implementation outcomes at the system, clinician, and patient levels to create a model for integrated FH care. This will be accomplished via qualitative research including interviews and focus groups of FH patients, their at-risk relatives, and FH healthcare providers as well as intervention mapping. The main outcomes to be collected are feasibility and acceptability. Microcosting analysis will also be performed to inform cost impact. These evaluations will inform the development of a standardized FH identification and cascade testing protocol acceptable to individuals and health systems that can be disseminated widely to positively impact the health and well-being of individuals at risk of FH.
Familial hypercholesterolemia is the most common genetic cardiovascular condition and leads to heart attack, stroke, and premature death when untreated, with >1 million individuals with FH in the U.S. who have not yet been diagnosed with this preventable condition. While FH has been noted as a public health concern by the CDC, data on the best way to identify patients with FH and activate their at-risk relatives to undergo cascade testing is lacking. We propose to test and optimize methods to identify patients with FH, strategies to improve family communication and FH cascade testing uptake, and evaluate the implementation outcomes of feasibility, acceptability, and cost at the system, clinician, and patient levels to create an exportable model for FH identification and cascade testing that can be implemented across broad healthcare settings.
