Primary care physician experiences utilizing a family health history tool with electronic health record–integrated clinical decision support: an implementation process assessment

Abstract

Family health history (FHH) screening plays a key role in disease risk identification and tailored disease prevention strategies. Primary care physicians (PCPs) are in a frontline position to provide personalized medicine recommendations identified through FHH screening; however, adoption of FHH screening tools has been slow and inconsistent in practice. Information is also lacking on PCP facilitators and barriers of utilizing family history tools with clinical decision support (CDS) embedded in the electronic health record (EHR). This study reports on PCPs' initial experiences with the Genetic and Wellness Assessment (GWA), a patient-administered FHH screening tool utilizing the EHR and CDS. Semi-structured interviews were conducted with 24 PCPs who use the GWA in a network of communitybased practices. Four main themes regarding GWA implementation emerged: benefits to clinical care, challenges in practice, CDS-specific issues, and physician-recommended improvements. Sub-themes included value in improving patient access to genetic services, inadequate time to discuss GWA recommendations, lack of patient follow-through with recommendations, and alert fatigue. While PCPs valued the GWA's clinical utility, a number of challenges were identified in the administration and use of the GWA in practice. Based on participants' recommendations, iterative changes have been made to the GWA and workflow to increase efficiency, upgrade the CDS process, and provide additional education to PCPs and patients. Future studies are needed to assess a diverse sample of physicians' and patients' perspectives on the utility of FHH screening utilizing EHR-based genomics recommendations.

Prevalence and Correlates of Family Cancer History Knowledge and Communication Among US Adults

“…Despite these barriers, opportunities exist for improving patient–provider communication about FCH and supporting these discussions at the point of care ( 25 , 26 ). These opportunities include training on communication skills for health care providers and system-level interventions that include standardization of key elements of a precise family history (eg, cancer types, age at onset), consistent information structures for health history intake, and integration of family health history data into patients’ electronic health records for clinical decision support ( 26 ).…”

“…To this end, digital tools, such as the US Surgeon General’s My Family Health Portrait, could be promoted to support tracking of family health history ( 29 – 31 ). However, effective use of family cancer histories will entail supporting communication among individuals, families, and health care providers as well as health care systems–level support for systematic FCH collection and clinical decision making ( 8 , 17 , 26 ). Continued surveillance of FCH communication behavior is recommended as personalized medicine advances and access to genetic testing expands among the population.…”

Primary Care Physician Experiences with Integrated Population-Scale Genetic Testing: A Mixed-Methods Assessment

“…Using a learning healthcare system model [ 34 ], we have been able to identify the needs of key stakeholders and develop potential solutions for programmatic improvement. Previous PCP feedback elicited through formal assessments of other genomic initiatives at our institution has been key in informing processes, workflows and educational efforts implemented in the DNA-10K [ 35 , 36 ]. Moving forward, it will be important to continually elicit feedback from PCP genomic ambassadors and other stakeholders so we can continue to iterate and improve both the user experience and accessibility of personalized medicine to all patients.…”

Strategic vision for improving human health at The Forefront of Genomics

“…To make genomic information readily accessible and broadly useful to clinicians, user-friendly electronic health record-based clinical decision support tools must be created to interact with a variety of clinical data from electronic health record and other data systems (for example, laboratory, pharmacy, and radiology) as well as non-computable reports, such as those provided as portable document format (PDF) files 43,44 . These efforts require well-curated, highly integrated, and up-to-date knowledgebases that connect genomic information to clinical characteristics, other phenotypic data, and information on family health history 45 . Reliable risk-stratification and prevention algorithms, including polygenic risk scores (PRSs) 46 , must be developed and should incorporate both common and rare genomic variants from a broad range of population subgroups, phenotypic data, and environmental information into the risk modelling 47 .…”