Effect of clinical decision support for severe hypercholesterolemia on low-density lipoprotein cholesterol levels.

Severe hypercholesterolemia/possible familial hypercholesterolemia (FH) is relatively common but underdiagnosed and undertreated. We investigated whether implementing clinical decision support (CDS) was associated with lower low-density lipoprotein cholesterol (LDL-C) in patients with severe hypercholesterolemia/possible FH (LDL-C ≥ 190 mg/dL). As part of a pre-post implementation study, a CDS alert was deployed in the electronic health record (EHR) in a large health system comprising 3 main sites, 16 hospitals and 53 clinics. Data were collected for 3 months before ('silent mode') and after ('active mode') its implementation. Clinicians were only able to view the alert in the EHR during active mode. We matched individuals 1:1 in both modes, based on age, sex, and baseline lipid lowering therapy (LLT). The primary outcome was difference in LDL-C between the two groups and the secondary outcome was initiation/intensification of LLT after alert trigger. We identified 800 matched patients in each mode (mean ± SD age 56.1 ± 11.8 y vs. 55.9 ± 11.8 y; 36.0% male in both groups; mean ± SD initial LDL-C 211.3 ± 27.4 mg/dL vs. 209.8 ± 23.9 mg/dL; 11.2% on LLT at baseline in each group). LDL-C levels were 6.6 mg/dL lower (95% CI, -10.7 to -2.5; P = 0.002) in active vs. silent mode. The odds of high-intensity statin use (OR, 1.78; 95% CI, 1.41-2.23; P < 0.001) and LLT initiation/intensification (OR, 1.30, 95% CI, 1.06-1.58, P = 0.01) were higher in active vs. silent mode. Implementation of a CDS was associated with lowering of LDL-C levels in patients with severe hypercholesterolemia/possible FH, likely due to higher rates of clinician led LLT initiation/intensification.

Clinician Perspectives on Clinical Decision Support for Familial Hypercholesterolemia.

Familial Hypercholesterolemia (FH) is underdiagnosed in the United States. Clinical decision support (CDS) could increase FH detection once implemented in clinical workflows. We deployed CDS for FH at an academic medical center and sought clinician insights using an implementation survey. In November 2020, the FH CDS was deployed in the electronic health record at all Mayo Clinic sites in two formats: a best practice advisory (BPA) and an in-basket alert. Over three months, 104 clinicians participated in the survey (response rate 11.1%). Most clinicians (81%) agreed that CDS implementation was a good option for identifying FH patients; 78% recognized the importance of implementing the tool in practice, and 72% agreed it would improve early diagnosis of FH. In comparing the two alert formats, clinicians found the in-basket alert more acceptable (p = 0.036) and more feasible (p = 0.042) than the BPA. Overall, clinicians favored implementing the FH CDS in clinical practice and provided feedback that led to iterative refinement of the tool. Such a tool can potentially increase FH detection and optimize patient management.

Education and electronic medical records and genomics network, challenges, and lessons learned from a large-scale clinical trial using polygenic risk scores.

Polygenic risk scores (PRS) have potential to improve health care by identifying individuals that have elevated risk for common complex conditions. Use of PRS in clinical practice, however, requires careful assessment of the needs and capabilities of patients, providers, and health care systems. The electronic Medical Records and Genomics (eMERGE) network is conducting a collaborative study which will return PRS to 25,000 pediatric and adult participants. All participants will receive a risk report, potentially classifying them as high risk (∼2-10% per condition) for 1 or more of 10 conditions based on PRS. The study population is enriched by participants from racial and ethnic minority populations, underserved populations, and populations who experience poorer medical outcomes. All 10 eMERGE clinical sites conducted focus groups, interviews, and/or surveys to understand educational needs among key stakeholders-participants, providers, and/or study staff. Together, these studies highlighted the need for tools that address the perceived benefit/value of PRS, types of education/support needed, accessibility, and PRS-related knowledge and understanding. Based on findings from these preliminary studies, the network harmonized training initiatives and formal/informal educational resources. This paper summarizes eMERGE's collective approach to assessing educational needs and developing educational approaches for primary stakeholders. It discusses challenges encountered and solutions provided.

Returning integrated genomic risk and clinical recommendations: The eMERGE study.

PURPOSE: Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk. METHODS: To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results. RESULTS: GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022. CONCLUSION: Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

A pragmatic clinical trial of cascade testing for familial hypercholesterolemia.

PURPOSE: We compared new cases detected per index case in familial hypercholesterolemia (FH) families with or without an identifiable monogenic etiology. METHODS: We enrolled 52 FH probands with a pathogenic variant (FHg+) in LDLR, APOB, or PCSK9 and 73 probands without such a variant (FHg-). After direct contact by the study team, family members (FMs) of FHg+ probands could opt-in for genetic testing and FMs of FHg- probands were asked to provide a lipid profile. New cases were defined as presence of a pathogenic variant in FHg+ families and as low-density lipoprotein cholesterol ≥155 mg/dL in FHg- families. RESULTS: Of 71 FHg+ probands seen by a genetic counselor, 52 consented and identified 253 FMs (111 consented and were tested, yielding 48 new cases). Of 101 FHg- probands who received counseling, 73 consented and identified 295 FMs (63 consented and were tested, yielding 17 new cases). New case detection per index case was significantly greater in FHg+ than in FHg- families (0.92 vs 0.23), a result of higher cascade testing uptake (43.9 vs 21.4%) and yield (43.2 vs 27.0%) in the former. CONCLUSION: New case detection rate was significantly higher in FH families with a monogenic etiology than in those without such an etiology owing to greater uptake and yield of cascade testing.

Web-Based Tool (FH Family Share) to Increase Uptake of Cascade Testing for Familial Hypercholesterolemia: Development and Evaluation.

BACKGROUND: Familial hypercholesterolemia, a prevalent genetic disorder, remains significantly underdiagnosed in the United States. Cascade testing, wherein individuals diagnosed with familial hypercholesterolemia- probands-contact their family members to inform them of their risk for familial hypercholesterolemia, has low uptake in the United States. Digital tools are needed to facilitate communication between familial hypercholesterolemia probands and their family members and to promote sharing of familial hypercholesterolemia-related risk information. OBJECTIVE: We aimed to create and evaluate a web-based tool designed to enhance familial communication and promote cascade testing for familial hypercholesterolemia. METHODS: A hybrid type 1 implementation science framework and a user-centered design process were used to develop an interactive web-based tool-FH Family Share-that enables familial hypercholesterolemia probands to communicate information about their familial hypercholesterolemia diagnosis with at-risk relatives. Probands can also use the tool to draw a family pedigree and learn more about familial hypercholesterolemia through education modules and curated knowledge resources. Usability guidelines and standards were taken into account during the design and development of the tool. The initial prototype underwent a cognitive walkthrough, which was followed by usability testing with key stakeholders including genetic counselors and patients with familial hypercholesterolemia. Participants navigated the prototype using the think-aloud technique, and their feedback was used to refine features of the tool. RESULTS: Key themes that emerged from the cognitive walkthrough were design, format, navigation, terminology, instructions, and learnability. Expert feedback from the cognitive walkthrough resulted in a rebuild of the web-based tool to align it with institutional standards. Usability testing with genetic counselors and patients with familial hypercholesterolemia provided insights on user experience, satisfaction and interface design and highlighted specific modifications that were made to refine the features of FH Family Share. Genetic counselors and patients with familial hypercholesterolemia suggested inclusion of the following features in the web-based tool: (1) a letter-to-family-member email template, (2) education modules, and (3) knowledge resources. Surveys revealed that 6 of 9 (67%) genetic counselors found information within FH Family Share very easy to find, and 5 of 9 (56%) genetic counselors found information very easy to understand; 5 of 9 (56%) patients found information very easy to find within the website, and 7 of 9 (78%) patients found information very easy to understand. All genetic counselors and patients indicated that FH Family Share was a resource worth returning to. CONCLUSIONS: FH Family Share facilitates communication between probands and their relatives. Once informed, at-risk family members have the option to seek testing and treatment for familial hypercholesterolemia.

Genomic considerations for FHIR®; eMERGE implementation lessons.

Structured representation of clinical genetic results is necessary for advancing precision medicine. The Electronic Medical Records and Genomics (eMERGE) Network's Phase III program initially used a commercially developed XML message format for standardized and structured representation of genetic results for electronic health record (EHR) integration. In a desire to move towards a standard representation, the network created a new standardized format based upon Health Level Seven Fast Healthcare Interoperability Resources (HL7® FHIR®), to represent clinical genomics results. These new standards improve the utility of HL7® FHIR® as an international healthcare interoperability standard for management of genetic data from patients. This work advances the establishment of standards that are being designed for broad adoption in the current health information technology landscape.

An Implementation Science Framework to Develop a Clinical Decision Support Tool for Familial Hypercholesterolemia.

Electronic health record (EHR)-based clinical decision support (CDS) can address the low awareness and undertreatment of familial hypercholesterolemia (FH), a disorder associated with a markedly increased risk of coronary heart disease. We aimed to incorporate provider perspectives into the development and implementation of a CDS tool for FH. An implementation science framework and a user-centered design process were used to create a CDS tool for FH. Primary care physicians and specialist physicians participated in qualitative interviews, usability testing and an implementation survey. The CDS was configured in two formats-a best practice alert (BPA) and an in-basket message and subsequently deployed in the EHR in silent mode. The key themes that emerged from the analysis of interview transcripts included understanding and awareness of FH, clinical workflow, physician preferences and value of CDS tools, perspectives on patient needs and values and dissemination and implementation. Recommendations related to usability included preferred CDS format and placement, content, timing and frequency, and level of alert urgency/prioritization. In response to the survey, 84.6% of physicians agreed that the CDS would improve early FH diagnosis and 92.3% agreed that it would help them identify and manage FH patients. Physician feedback led to iterative CDS refinement. In summary, we developed a CDS tool for FH using an implementation science framework and physician feedback. Initial deployment revealed a significant burden of FH and the potential for the CDS tool to have a large impact.

Implementation Science to Increase Adoption of Genomic Medicine: An Urgent Need.

Advances in genomics have the potential to improve human health [...].

Deploying Clinical Decision Support for Familial Hypercholesterolemia.

Objective: Familial hypercholesterolemia (FH), a prevalent genomic disorder that increases risk of coronary heart disease, remains significantly underdiagnosed. Clinical decision support (CDS) tools have the potential to increase FH detection. We describe our experience in the development and implementation of a genomic CDS for FH at a large academic medical center. Methods: CDS development and implementation were conducted in four phases: (1) development and validation of an algorithm to identify "possible FH"; (2) obtaining approvals from institutional committees to develop the CDS; (3) development of the initial prototype; and (4) use of an implementation science framework to evaluate the CDS. Results: The timeline for this work was approximately 4 years; algorithm development and validation occurred from August 2018 to February 2020. During this 4-year period, we engaged with 15 stakeholder groups to build and integrate the CDS, including health care providers who gave feedback at each stage of development. During CDS implementation six main challenges were identified: (1) need for multiple institutional committee approvals; (2) need to align the CDS with institutional knowledge resources; (3) need to adapt the CDS to differing workflows; (4) lack of institutional guidelines for CDS implementation; (5) transition to a new institutional electronic health record (EHR) system; and (6) limitations of the EHR related to genomic medicine. Conclusion: We identified multiple challenges in different domains while developing CDS for FH and integrating it with the EHR. The lessons learned herein may be helpful in streamlining the development and deployment of CDS to facilitate genomic medicine implementation.

New Case Detection by Cascade Testing in Familial Hypercholesterolemia: A Systematic Review of the Literature.

BACKGROUND: The prevalence of familial hypercholesterolemia is 1 in 250, but <10% of patients are diagnosed. Cascade testing enables early detection of cases through systematic family tracing. Establishment of familial hypercholesterolemia cascade testing programs in the US could be informed by approaches used elsewhere. METHODS: We conducted a systematic review of published studies in the English language of cascade testing for familial hypercholesterolemia, which reported the number of index cases and number of relatives tested and specified methods of contacting relatives and testing modalities methods utilized. For each study, we calculated yield (proportion of relatives who test positive) and new cases per index case, to facilitate comparison. RESULTS: We identified 10 studies from the literature that met inclusion criteria; the mean number of probands and relatives per study was 242 and 826, respectively. The average yield was 44.76% with a range of 30% to 60.5%, and the mean new cases per index case was 1.65 with a range of 0.22 to 8.0. New cases per index case tended to be greater in studies that used direct contact versus indirect contact (2.06 versus 0.86), tested beyond first-degree relatives versus only first-degree relatives (3.65 versus 0.80), used active sample collection versus collection at clinic (4.11 versus 1.06), and utilized genetic testing versus biochemical testing (2.47 versus 0.42). CONCLUSIONS: New case detection in familial hypercholesterolemia cascade testing programs tended to be higher with direct contact of relatives, testing beyond first-degree relatives, in-home-based sample collection, and genetic testing. These findings should be helpful for establishing cascade testing programs in the United States.