UNC Health
Chapel Hill, NC
Cystic fibrosis (CF) is a life-shortening genetic disease caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. People with CF (PwCF) have become increasingly eligible for CFTR modulators (CFTRm) based on their CFTR variants and age. Early initiation is paramount, as these medications can change the CF disease course. However, with over 1,900 CFTR mutations, identifying eligible PwCF is challenging.
Some electronic health records (EHRs) offer pharmacogenomic clinical decision support (CDS). Most CDS tools alert prescribers to gene-drug metabolism interactions to mitigate adverse drug events or optimize therapeutic response but aren’t utilized to proactively identify individuals for genetic-based pharmacotherapy. CF-MAGIC (CFTR Modulator PharmacoGenomICs) was developed to streamline care for PwCF by identifying PwCF with qualifying CFTR variants to ensure timely initiation of CFTRms and proactively identifying pediatric PwCF requiring dose optimization based on age and/or weight.
During phase one, genomic indicators were created within the EHR that denote a patient’s CFTRm eligibility based on the presence of qualifying CFTR variants. These indicators are the foundation to trigger additional CDS. Next, a CFTRm eligibility best practice advisory (BPA) alert was developed to highlight eligible patients who are not currently prescribed a CFTRm. The BPA links to the CFTRm SmartSet, a dynamic set of clinical orders that populates only the appropriate CFTRm, strength/dosage form, and dose based on the individual’s genotype, age, and weight. The second phase focused on entry of all patients’ CFTR genotypes into the EHR’s genomics module, providing a discrete and reportable location in the EHR. The patients’ physical CFTR variant lab results, which are critical for insurance approval of CFTRms, were attached. In the final phase, a prospective report was developed to alert clinicians to PwCF with upcoming CFTRm eligibility based on age and to identify patients who need or will soon need dose adjustments based on age or weight.
When tested against historical CFTRm approvals and expansions, CF-MAGIC accurately identified all PwCF with eligible mutations for CFTRm, capturing patients that prior methods missed. Since implementation of the proactive CFTRm eligibility and dose optimization report, CF-MAGIC has identified three patients that will be newly eligible for elexacaftor/tezacaftor/ivacaftor that were not previously identified; one patient who had a missed dose adjustment on lumacaftor/ivacaftor; three patients currently receiving the improper dosage form based on age; and eleven patients anticipated to need dose adjustment based on weight. CF-MAGIC can now be utilized prospectively to identify eligible PwCF for future CFTRm label expansions and approvals, which are anticipated within the next few months. With a single report, CF-MAGIC will generate a list of eligible patients, significantly decreasing the time needed to identify CFTRm-eligible PwCF. This will allow for sufficient time to complete all required baseline testing and counseling and further improve time to first CFTRm prescription.
CF-MAGIC is a novel and innovative utilization of the EHR, leveraging its full potential to optimize PwCF’s care. It enables pharmacists to navigate the ever-evolving landscape of CF and precision medicine to provide care to their patients more efficiently and effectively.
Left to Right: Killian Rodgers, Michael Adams, Charissa Kam, Cameron McKinzie, John Valgus
Not Pictured: Jenny Wong, Chris Falato