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Background: Relatives of probands diagnosed with familial hypercholesterolemia (FH) should undergo cascade testing for FH. Objectives: The purpose of this study was to evaluate probands' choices of innovative strategies to communicate their FH result with relatives and facilitate cascade testing uptake. Methods: Probands with an FH genetic result from the MyCode Community Health Initiative could choose to share their FH result with adult blood relatives via the Family and Healthcare Professional Packet (packet), family sharing and cascade chatbots (chatbot), and/or FH Outreach and Support Program (direct contact). Cascade testing uptake was measured as reported completion of genetic or cholesterol testing. Generalized estimating equations models were used to identify factors associated with testing. Results: One hundred seventy five probands received an FH result, median age was 58.9 (IQR: 44.9-69.3), and 58.9% were female. Probands shared information about 1,915 adult and 163 minor relatives (11.9 relatives per proband). Seventy percent of probands (121/175) selected at least one strategy for at least one adult relative. An average of 1.2 strategies was selected per adult relative. Cascade testing was completed for 26.6% (144/541) of adults with at least one strategy selected, 2.4% (33/1,374) of adults without a strategy selected, and 25.2% (41/163) of minor relatives. Factors associated with increased cascade testing uptake were selection of at least one strategy (6.32 higher odds), specifically, selection of direct contact (16.78 higher odds). Conclusions: Strategies implemented improved FH cascade testing uptake compared to previous estimates and in families where no strategy was selected. Overall uptake remains insufficient, which can be attributed to probands reluctance to select a strategy for many relatives.
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BACKGROUND: Cascade testing can be highly effective in identifying individuals with familial hypercholesterolemia (FH) and help prevent atherosclerotic cardiovascular disease. The IMPACT-FH cascade testing program offered multiple optimized implementation strategies to improve FH cascade testing uptake. OBJECTIVE: Guided by the Conceptual Model of Implementation Research, this study assessed the IMPACT-FH cascade testing program's implementation outcomes. METHODS: Implementation outcomes were assessed qualitatively and quantitatively. Interviews were conducted with 33 IMPACT-FH program participants including 15 probands, 12 relatives, and 6 healthcare professionals (HCPs). Transcripts were analyzed using thematic analysis to investigate implementation outcomes. Descriptive statistics were analyzed for scaled implementation outcome measures asked after interviews. RESULTS: Participants described adopting strategies offered in the IMPACT-FH program because they presented an opportunity to pursue low-cost FH cascade testing. Participants identified barriers to feasibility including: the complexity of disclosing an FH result and offering strategies on, inherent limitations of probands choosing strategies, confusion over testing costs, limitations sharing with relatives' clinicians, discomfort with chatbot technology, and concerns about the workload for HCPs. Participants evaluated the program positively regarding its appropriateness (Mean (M) = 4.70, Standard Deviation (SD) = 0.41), acceptability (M = 4.79, SD = 0.40), and feasibility (M = 4.24, SD = 0.53). CONCLUSION: The IMPACT-FH cascade testing program and its strategies were evaluated as valuable to adopt and highly appropriate, acceptable, and feasible by participants. Participants identified areas to enhance the program that could improve FH cascade testing uptake.
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The IMPACT-FH study implemented strategies (packet, chatbot, direct contact) to promote family member cascade testing for familial hypercholesterolemia (FH). We evaluated the impact of genetic counseling (GC) on medical outcomes, strategy selection, and cascade testing. Probands (i.e., patients with FH) were recommended to complete GC and select sharing strategies. Comparisons were performed for both medical outcomes and strategy selection between probands with or without GC. GEE models for Poisson regression were used to examine the relationship between proband GC completion and first-degree relative (FDR) cascade testing. Overall, 46.3% (81/175) of probands completed GC. Probands with GC had a median LDL-C reduction of -13.0 mg/dL (-61.0, 4.0) versus -1.0 mg/dL (-16.0, 17.0) in probands without GC (p = 0.0054). Probands with and without GC selected sharing strategies for 65.3% and 40.3% of FDRs, respectively (p < 0.0001). Similarly, 27.1% of FDRs of probands with GC completed cascade testing, while 12.0% of FDRs of probands without GC completed testing (p = 0.0043). Direct contact was selected for 47 relatives in total and completed for 39, leading to the detection of 18 relatives with FH. Proband GC was associated with improved medical outcomes and increased FDR cascade testing. Direct contact effectively identified FH cases for the subset who participated.
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Importance: Screening unselected populations for clinically actionable genetic disease risk can improve ascertainment and facilitate risk management. Genetics visits may encourage at-risk individuals to perform recommended management, but little has been reported on genetics visit completion or factors associated with completion in genomic screening programs. Objective: To identify factors associated with postdisclosure genetics visits in a genomic screening cohort. Design, Setting, and Participants: This was a cohort study of biobank data in a health care system in central Pennsylvania. Participants' exome sequence data were reviewed for pathogenic or likely pathogenic (P/LP) results in all genes on the American College of Medical Genetics and Genomics Secondary Findings list. Clinically confirmed results were disclosed by phone and letter. Participants included adult MyCode biobank participants who received P/LP results between July 2015 and November 2019. Data were analyzed from May 2021 to March 2022. Exposure: Clinically confirmed P/LP result disclosed by phone or letter. Main Outcomes and Measures: Completion of genetics visit in which the result was discussed and variables associated with completion were assessed by electronic health record (EHR) review. Results: Among a total of 1160 participants (703 [60.6%] female; median [IQR] age, 57.0 [42.1-68.5] years), fewer than half of participants (551 of 1160 [47.5%]) completed a genetics visit. Younger age (odds ratio [OR] for age 18-40 years, 2.98; 95% CI, 1.40-6.53; OR for age 41-65 years, 2.36; 95% CI, 1.22-4.74; OR for age 66-80 years, 2.60; 95% CI, 1.41-4.98 vs age ≥81 years); female sex (OR, 1.49; 95% CI, 1.14-1.96); being married (OR, 1.74; 95% CI, 1.23-2.47) or divorced (OR, 1.80; 95% CI, 1.11-2.91); lower Charlson comorbidity index (OR for score of 0-2, 1.76; 95% CI, 1.16-2.68; OR for score of 3-4, 1.73; 95% CI, 1.18-2.54 vs score of ≥5); EHR patient portal use (OR, 1.42; 95% CI, 1.06-1.89); living closer to a genetics clinic (OR, 1.64; 95% CI, 1.14-2.36 for <8.9 miles vs >20.1 miles); successful results disclosure (OR for disclosure by genetic counselor, 16.32; 95% CI, 8.16-37.45; OR for disclosure by research assistant, 20.30; 95% CI, 10.25-46.31 vs unsuccessful phone disclosure); and having a hereditary cancer result (OR, 2.13; 95% CI, 1.28-3.58 vs other disease risk) were significantly associated with higher rates of genetics visit completion. Preference to follow up with primary care was the most common reported reason for declining a genetics visit (68 of 152 patients [44.7%]). Conclusions and Relevance: This cohort study of a biobank-based population genomic screening program suggests that targeted patient engagement, improving multidisciplinary coordination, and reducing barriers to follow-up care may be necessary for enhancing genetics visit uptake.
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Genómica , Neoplasias , Adulto , Humanos , Femenino , Persona de Mediana Edad , Adolescente , Adulto Joven , Anciano , Anciano de 80 o más Años , Masculino , Estudios de Cohortes , Genómica/métodos , Exoma , PennsylvaniaRESUMEN
Background Data mining of electronic health records to identify patients suspected of familial hypercholesterolemia (FH) has been limited by absence of both phenotypic and genomic data in the same cohort. Methods and Results Using the Geisinger MyCode Community Health Initiative cohort (n=130 257), we ran 2 screening algorithms (Mayo Clinic [Mayo] and flag, identify, network, deliver [FIND] FH) to determine FH genetic and phenotypic diagnostic yields. With 29 243 excluded by Mayo (for secondary causes of hypercholesterolemia, no lipid value in electronic health records), 52 034 excluded by FIND FH (insufficient data to run the model), and 187 excluded for prior FH diagnosis, a final cohort of 59 729 participants was created. Genetic diagnosis was based on presence of a pathogenic or likely pathogenic variant in FH genes. Charts from 180 variant-negative participants (60 controls, 120 identified by FIND FH and Mayo) were reviewed to calculate Dutch Lipid Clinic Network scores; a score ≥5 defined probable phenotypic FH. Mayo flagged 10 415 subjects; 194 (1.9%) had a pathogenic or likely pathogenic FH variant. FIND FH flagged 573; 34 (5.9%) had a pathogenic or likely pathogenic variant, giving a net yield from both of 197 out of 280 (70%). Confirmation of a phenotypic diagnosis was constrained by lack of electronic health record data on physical findings or family history. Phenotypic FH by chart review was present by Mayo and/or FIND FH in 13 out of 120 versus 2 out of 60 not flagged by either (P<0.09). Conclusions Applying 2 recognized FH screening algorithms to the Geisinger MyCode Community Health Initiative identified 70% of those with a pathogenic or likely pathogenic FH variant. Phenotypic diagnosis was rarely achievable due to missing data.
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Hipercolesterolemia , Hiperlipoproteinemia Tipo II , Humanos , Registros Electrónicos de Salud , Hiperlipoproteinemia Tipo II/diagnóstico , Hiperlipoproteinemia Tipo II/epidemiología , Hiperlipoproteinemia Tipo II/genéticaRESUMEN
Introduction: Familial hypercholesterolemia (FH) is a common inherited cholesterol disorder that, without early intervention, leads to premature cardiovascular disease. Multilevel strategies that target all components of FH care including identification, cascade testing, and management are needed to address gaps that exist in FH care. We utilized intervention mapping, a systematic implementation science approach, to identify and match strategies to existing barriers and develop programs to improve FH care. Methods: Data were collected utilizing two methods: a scoping review of published literature, related to any component of FH care, and a parallel mixed method study using interviews and surveys. The scientific literature was searched using key words including "barriers" or "facilitators" and "familial hypercholesterolemia" from inception to December 1, 2021. The parallel mixed method study recruited individuals and families with FH to participate in either dyadic interviews (N = 11 dyads/22 individuals) or online surveys (N = 98 respondents). Data generated from the scoping review, dyadic interviews, and online surveys were used in the 6-step intervention mapping process. Steps 1-3 included a needs assessment, development of program outcomes and creation of evidence-based implementation strategies. Steps 4-6 included program development, implementation, and evaluation of implementation strategies. Results: In steps 1-3, a needs assessment found barriers to FH care included underdiagnosis of the condition which led to suboptimal management due to a myriad of determinants including knowledge gaps, negative attitudes, and risk misperceptions by individuals with FH and clinicians. Literature review highlighted barriers to FH care at the health system level, notably the relative lack of genetic testing resources and infrastructure needed to support FH diagnosis and treatment. Examples of strategies to overcome identified barriers included development of multidisciplinary care teams and educational programs. In steps 4-6, an NHLBI-funded study, the Collaborative Approach to Reach Everyone with FH (CARE-FH), deployed strategies that focused on improving identification of FH in primary care settings. The CARE-FH study is used as an example to describe program development, implementation, and evaluation techniques of implementation strategies. Conclusion: The development and deployment of evidence-based implementation strategies that address barriers to FH care are important next steps to improve identification, cascade testing, and management.
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Objective: To assess use of two web-based conversational agents, the Family Sharing Chatbot (FSC) and One Month Chatbot (OMC), by individuals with familial hypercholesterolemia (FH). Methods: FSC and OMC were sent using an opt-out methodology to a cohort of individuals receiving a FH genetic result. Data from 7/1/2021 through 5/12/2022 was obtained from the electronic health record and the chatbots' HIPAA-secure web portal. Results: Of 175 subjects, 21 (12%) opted out of the chatbots. Older individuals were more likely to opt out. Most (91/154, 59%) preferred receiving chatbots via the patient EHR portal. Seventy-five individuals (49%) clicked the FSC link, 62 (40%) interacted, and 36 (23%) shared a chatbot about their FH result with at least one relative. Ninety-two of the subjects received OMC, 22 (23%) clicked the link and 20 (21%) interacted. Individuals who shared were majority female and younger on average than the overall cohort. Reminders tended to increase engagement. Conclusion: Results demonstrate characteristics relevant to chatbot engagement. Individuals may be more inclined to receive chatbots if integrated within the patient EHR portal. Frequent reminders can potentially improve chatbot utilization. Innovation: FSC and OMC employ innovative digital health technology that can facilitate family communication about hereditary conditions.
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BACKGROUND: This project aimed to optimize communication strategies to support family communication about familial hypercholesterolemia (FH) and improve cascade testing uptake among at-risk relatives. Individuals and families with FH provided feedback on multiple strategies including: a family letter, digital tools, and direct contact. METHODS: Feedback from participants was collected via dyadic interviews (n = 11) and surveys (n = 98) on communication strategies and their proposed implementation to improve cascade testing uptake. We conducted a thematic analysis to identify how to optimize each strategy. We categorized optimizations and their implementation within the project's healthcare system using a Traffic Light approach. RESULTS: Thematic analysis resulted in four distinct suggested optimizations for each communication strategy and seven suggested optimizations that were suitable across all strategies. Four suggestions for developing a comprehensive cascade testing program, which would offer all optimized communication strategies also emerged. All optimized suggestions coded green (n = 21) were incorporated. Suggestions coded yellow (n = 12) were partially incorporated. Only two suggestions were coded red and could not be incorporated. CONCLUSIONS: This project demonstrates how to collect and analyze stakeholder feedback for program design. We identified feasible suggested optimizations, resulting in communication strategies that are patient-informed and patient-centered. Optimized strategies were implemented in a comprehensive cascade testing program.
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Hiperlipoproteinemia Tipo II , Humanos , Comunicación , Pacientes , Pruebas GenéticasRESUMEN
Motivating at-risk relatives to undergo cascade testing for familial hypercholesterolemia (FH) is critical for diagnosis and lifesaving treatment. As credible sources of information, clinicians can assist in family communication about FH and motivate cascade testing uptake. However, there are no guidelines regarding how clinicians should effectively communicate with probands (the first person diagnosed in the family) and at-risk relatives. Individuals and families with FH can inform our understanding of the most effective communications to promote cascade testing. Guided by the extended parallel process model (EPPM), we analyzed the perspectives of individuals and families with FH for effective messaging clinicians can use to promote cascade testing uptake. We analyzed narrative data from interviews and surveys collected as part of a larger mixed-methods study. The EPPM was used to identify message features recommended by individuals and families with FH that focus on four key constructs (severity, susceptibility, response efficacy, self-efficacy) to promote cascade testing. Participants included 22 individuals from 11 dyadic interviews and 98 survey respondents. Participants described prioritizing multiple messages that address each EPPM construct to alert relatives about their risk. They illustrated strategies clinicians could use within each EPPM construct to communicate to at-risk relatives about the importance of pursuing diagnosis via cascade testing and subsequent treatment for high cholesterol due to FH. Findings provide guidance on effective messaging to motivate cascade testing uptake for FH and demonstrates how the EPPM may guide communication with at-risk relatives about genetic risk and motivate cascade testing broadly.
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Pruebas Genéticas , Hiperlipoproteinemia Tipo II , Comunicación , Pruebas Genéticas/métodos , Humanos , Hiperlipoproteinemia Tipo II/diagnóstico , Hiperlipoproteinemia Tipo II/genética , Hiperlipoproteinemia Tipo II/terapia , Factores de RiesgoRESUMEN
BACKGROUND: Familial hypercholesterolemia (FH) is the most common cardiovascular genetic disorder and, if left untreated, is associated with increased risk of premature atherosclerotic cardiovascular disease, the leading cause of preventable death in the United States. Although FH is common, fatal, and treatable, it is underdiagnosed and undertreated due to a lack of systematic methods to identify individuals with FH and limited uptake of cascade testing. METHODS AND RESULTS: This mixed-method, multi-stage study will optimize, test, and implement innovative approaches for both FH identification and cascade testing in 3 aims. To improve identification of individuals with FH, in Aim 1, we will compare and refine automated phenotype-based and genomic approaches to identify individuals likely to have FH. To improve cascade testing uptake for at-risk individuals, in Aim 2, we will use a patient-centered design thinking process to optimize and develop novel, active family communication methods. Using a prospective, observational pragmatic trial, we will assess uptake and effectiveness of each family communication method on cascade testing. Guided by an implementation science framework, in Aim 3, we will develop a comprehensive guide to identify individuals with FH. Using the Conceptual Model for Implementation Research, we will evaluate implementation outcomes including feasibility, acceptability, and perceived sustainability as well as health outcomes related to the optimized methods and tools developed in Aims 1 and 2. CONCLUSIONS: Data generated from this study will address barriers and gaps in care related to underdiagnosis of FH by developing and optimizing tools to improve FH identification and cascade testing.