Closing the gap: Identification and management of familial hypercholesterolemia in an integrated healthcare delivery system

Implications of Diagnosis Through a Machine Learning Algorithm on Management of People With Familial Hypercholesterolemia

Background

Familial hypercholesterolemia (FH) is an underdiagnosed genetic condition that leads to premature cardiovascular disease. Flag, Identify, Network, and Deliver (FIND) FH is a machine learning algorithm (MLA) developed by the Family Heart Foundation that identifies high-risk individuals in the electronic medical record for targeted FH screening.

Objectives

The purpose of this study was to characterize the FH diagnostic coding status of patients detected by a MLA screening and assess for correlations with patterns in medical management and cardiovascular outcomes.

Methods

We applied the FIND FH MLA to a retrospective, cross-sectional cohort within one large academic medical center. Individual patient charts were manually reviewed and stratified by diagnosis status. Variables including baseline characteristics, medical history, family history, laboratory values, medications, and cardiovascular outcomes were compared across diagnosis status.

Results

The MLA identified 471 patients over 5.5 years with a high probability for FH. 121 (26%) previously undiagnosed patients met criteria for having "likely FH." Those with established FH diagnoses (n = 32) had significantly more lipid panel monitoring, prescriptions for non-statin or combination lipid-lowering agents, visits with a cardiologist, and frequency of coronary artery calcium score (CACS) testing or lipoprotein(a) testing than undiagnosed patients with likely FH. The 2 groups had no significant differences in having had prior major adverse cardiovascular events. The remaining 318 patients were classified as having "suspected FH."

Conclusions

These findings suggest that implementation of a MLA approach such as FIND FH may be feasible for identifying undiagnosed individuals living with FH, as well as addressing treatment disparities in this population at increased cardiovascular risk.

Barriers to and Facilitators of Implementing Guidelines for Detecting Familial Hypercholesterolaemia in Australia

BACKGROUND

Familial hypercholesterolaemia (FH) is a genetic condition that is a preventable cause of premature cardiovascular morbidity and mortality. High-level evidence and clinical practice guidelines support preventative care for people with FH. However, it is estimated that less than 10% of people at risk of FH have been detected using any approach across Australian health settings. The aim of this study was to identify the implementation barriers to and facilitators of the detection of FH in Australia.

METHODS

Four, 2-hour virtual focus groups were facilitated by implementation scientists and a clinicians as part of the 2021 Australasian FH Summit. Template analysis was used to identify themes.

RESULTS

There were 28 workshop attendees across four groups (n=6-8 each), yielding 13 barriers and 10 facilitators across three themes: (1) patient related, (2) provider related, and (3) system related. A "lack of care pathways" and "upskilling clinicians in identifying and diagnosing FH" were the most interconnected barriers and facilitators for the detection of FH.

CONCLUSIONS

The relationships between barriers and facilitators across the patient, provider, and system themes indicates that a comprehensive implementation strategy is needed to address these different levels. Future research is underway to develop a model for implementing the Australian FH guidelines into practice.

Real-world utilization of guideline-directed genetic testing in inherited cardiovascular diseases

Background

Cardiovascular disease continues to be the leading cause of death globally. Clinical practice guidelines aimed at improving disease management and positively impacting major cardiac adverse events recommend genetic testing for inherited cardiovascular conditions such as dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), long QT syndrome (LQTS), hereditary amyloidosis, and familial hypercholesterolemia (FH); however, little is known about how consistently practitioners order genetic testing for these conditions in routine clinical practice. This study aimed to assess the adoption of guideline-directed genetic testing for patients diagnosed with DCM, HCM, LQTS, hereditary amyloidosis, or FH.

Methods

This retrospective cohort study captured real-world evidence of genetic testing from ICD-9-CM and ICD-10-CM codes, procedure codes, and structured text fields of de-identified patient records in the Veradigm Health Insights Ambulatory EHR Research Database linked with insurance claims data. Data analysis was conducted using an automated electronic health record analysis engine. Patient records in the Veradigm database were sourced from more than 250,000 clinicians serving over 170 million patients in outpatient primary care and specialty practice settings in the United States and linked insurance claims data from public and private insurance providers. The primary outcome measure was evidence of genetic testing within six months of condition diagnosis.

Results

Between January 1, 2017, and December 31, 2021, 224,641 patients were newly diagnosed with DCM, HCM, LQTS, hereditary amyloidosis, or FH and included in this study. Substantial genetic testing care gaps were identified. Only a small percentage of patients newly diagnosed with DCM (827/101,919; 0.8%), HCM (253/15,507; 1.6%), LQTS (650/56,539; 1.2%), hereditary amyloidosis (62/1,026; 6.0%), or FH (718/49,650; 1.5%) received genetic testing.

Conclusions

Genetic testing is underutilized across multiple inherited cardiovascular conditions. This real-world data analysis provides insights into the delivery of genomic healthcare in the United States and suggests genetic testing guidelines are rarely followed in practice.

Subtyping Severe Hypercholesterolemia by Genetic Determinant to Stratify Risk of Coronary Artery Disease

BACKGROUND

Severe hypercholesterolemia, defined as LDL (low-density lipoprotein) cholesterol (LDL-C) measurement ≥190 mg/dL, is associated with increased risk for coronary artery disease (CAD). Causes of severe hypercholesterolemia include monogenic familial hypercholesterolemia, polygenic hypercholesterolemia, elevated lipoprotein(a) [Lp(a)] hypercholesteremia, polygenic hypercholesterolemia with elevated Lp(a) (two-hit), or nongenetic hypercholesterolemia. The added value of using a genetics approach to stratifying risk of incident CAD among those with severe hypercholesterolemia versus using LDL-C levels alone for risk stratification is not known.

METHODS

To determine whether risk stratification by genetic cause provided better 10-year incident CAD risk stratification than LDL-C level, a retrospective cohort study comparing incident CAD risk among severe hypercholesterolemia subtypes (genetic and nongenetic causes) was performed among 130 091 UK Biobank participants. Analyses were limited to unrelated, White British or Irish participants with available exome sequencing data. Participants with cardiovascular disease at baseline were excluded from analyses of incident CAD.

RESULTS

Of 130 091 individuals, 68 416 (52.6%) were women, and the mean (SD) age was 56.7 (8.0) years. Of the cohort, 9.0% met severe hypercholesterolemia criteria. Participants with LDL-C between 210 and 229 mg/dL and LDL-C ≥230 mg/dL showed modest increases in incident CAD risk relative to those with LDL-C between 190 and 209 mg/dL (210-229 mg/dL: hazard ratio [HR], 1.3 [95% CI, 1.1-1.7]; ≥230 mg/dL: HR, 1.3 [95% CI, 1.0-1.7]). In contrast, when risk was stratified by genetic subtype, monogenic familial hypercholesterolemia, elevated Lp(a), and two-hit hypercholesterolemia subtypes had increased rates of incident CAD relative to the nongenetic hypercholesterolemia subtype (monogenic familial hypercholesterolemia: HR, 2.3 [95% CI, 1.4-4.0]; elevated Lp(a): HR, 1.5 [95% CI, 1.2-2.0]; two-hit: HR, 1.9 [95% CI, 1.4-2.6]), while polygenic hypercholesterolemia did not.

CONCLUSIONS

Genetics-based subtyping for monogenic familial hypercholesterolemia and Lp(a) in those with severe hypercholesterolemia provided better stratification of 10-year incident CAD risk than LDL-C-based stratification.

The implementation checklist: A pragmatic instrument for accelerating research-to-implementation cycles

Introduction

Learning health systems require rapid-cycle research and nimble implementation processes to maximize innovation across disparate specialties and operations. Existing detailed research-to-implementation frameworks require extensive time commitments and can be overwhelming for physician-researchers with clinical and operational responsibilities, inhibiting their widespread adoption. The creation of a short, pragmatic checklist to inform implementation processes may substantially improve uptake and implementation efficiency across a variety of health systems.

Methods

We conducted a systematic review of existing implementation frameworks to identify core concepts. Utilizing comprehensive stakeholder engagement with 25 operational leaders, embedded physician-researchers, and delivery scientists, concepts were iteratively integrated to create and implement a final concise instrument.

Results

A systematic review identified 894 publications describing implementation frameworks, which included 15 systematic reviews. Among these, domains were extracted from three commonly utilized instruments: the Quality Implementation Framework (QIF), the Consolidated Framework for Implementation Research (CFIR), and the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Iterative testing and stakeholder engagement revision of a four-page draft implementation document with five domains resulted in a concise, one-page implementation planning instrument to be used at project outset and periodically throughout project implementation planning. The instrument addresses end-user feasibility concerns while retaining the main goals of more complex tools. This instrument was then systematically integrated into projects within the Kaiser Permanente Northern California Delivery Science and Applied Research program to address stakeholder engagement, efficiency, project planning, and operational implementation of study results.

Conclusion

A streamlined one-page implementation planning instrument, incorporating core concepts of existing frameworks, provides a pragmatic, robust framework for evidence-based healthcare innovation cycles that is being broadly implemented within a learning health system. These streamlined processes could inform other settings needing a best practice rapid-cycle research-to-implementation tool for large numbers of diverse projects.

Designing implementation strategies to improve identification, cascade testing, and management of families with familial hypercholesterolemia: An intervention mapping approach

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.

How Can Implementation Science Improve the Care of Familial Hypercholesterolaemia?

PURPOSE OF REVIEW

Describe the application of implementation science to improve the detection and management of familial hypercholesterolaemia.

RECENT FINDINGS

Gaps between evidence and practice, such as underutilization of genetic testing, family cascade testing, failure to achieve LDL-cholesterol goals and low levels of knowledge and awareness, have been identified through clinical registry analyses and clinician surveys. Implementation science theories, models and frameworks have been applied to assess barriers and enablers in the literature specific to local contextual factors (e.g. stages of life). The effect of implementation strategies to overcome these factors has been evaluated; for example, automated identification of individuals with FH or training and education to improve statin adherence. Clinical registries were identified as a key infrastructure to monitor, evaluate and sustain improvements in care. The expansion in evidence supporting the care of familial hypercholesterolaemia requires a similar expansion of efforts to translate new knowledge into clinical practice.

Leveraging Healthcare System Data to Identify High-Risk Dyslipidemia Patients

PURPOSE OF REVIEW

While randomized controlled trials have historically served as the gold standard for shaping guideline recommendations, real-world data are increasingly being used to inform clinical decision-making. We describe ways in which healthcare systems are generating real-world data related to dyslipidemia and how these data are being leveraged to improve patient care.

RECENT FINDINGS

The electronic medical record has emerged as a major source of clinical data, which alongside claims and pharmacy dispending data is enabling healthcare systems the ability to identify care gaps (underdiagnosis and undertreatment) in patients with dyslipidemia. Availability of this data also allows healthcare systems the ability to test and deliver interventions at the point-of-care. Real-world data possess great potential as a complement to randomized controlled trials. Healthcare systems are uniquely positioned to not only define care gaps and areas of opportunity, but to also to leverage tools (e.g., clinical decision support, case identification) aimed at closing them.

Clinical decision support for familial hypercholesterolemia (CDS-FH): Rationale and design of a cluster randomized trial in primary care

BACKGROUND

Familial hypercholesterolemia (FH) is an underdiagnosed and undertreated genetic disorder with high risk of premature atherosclerotic cardiovascular disease and death. Clinical decision support (CDS) systems have the potential to aid in the identification and management of patients with FH. Prior studies using computer-based systems to screen patients for FH have shown promising results, but there has been no randomized controlled trial conducted. The aim of the current cluster randomized study is to evaluate if a CDS can increase the identification of FH.

METHODS

We have developed a CDS integrated in the electronic health records that will be activated in patients with elevated cholesterol levels (total cholesterol >8 mmol/L or low-density lipoprotein-cholesterol >5.5 mmol/L, adjusted for age, ongoing lipid lowering therapy and presence of premature coronary artery disease) at increased risk for FH. When activated, the CDS will urge the physician to send an automatically generated referral to the local lipid clinic for further evaluation. To evaluate the effects of the CDS, all primary care clinics will be cluster randomized 1:1 to either CDS intervention or standard care in a Swedish region with almost 500,000 inhabitants. The primary endpoint will be the number of patients diagnosed with FH at 30 months. Resource use and long-term health consequences will be estimated to assess the cost-effectiveness of the intervention.

CONCLUSION

Despite increasing awareness of FH, the condition remains underdiagnosed and undertreated. The present study will investigate whether a CDS can increase the number of patients being diagnosed with FH.

Applying implementation science to improve care for familial hypercholesterolemia

PURPOSE OF REVIEW

Improving care of individuals with familial hypercholesteremia (FH) is reliant on the synthesis of evidence-based guidelines and their subsequent implementation into clinical care. This review describes implementation strategies, defined as methods to improve translation of evidence into FH care, that have been mapped to strategies from the Expert Recommendations for Implementing Change (ERIC) compilation.

RECENT FINDINGS

A search using the term 'familial hypercholesterolemia' returned 1350 articles from November 2018 to July 2021. Among these, there were 153 articles related to improving FH care; 1156 were excluded and the remaining 37 were mapped to the ERIC compilation of strategies: assess for readiness and identify barriers and facilitators [9], develop and organize quality monitoring systems [14], create new clinical teams [2], facilitate relay of clinical data to providers [4], and involve patients and family members [8]. There were only 8 of 37 studies that utilized an implementation science theory, model, or framework and two that explicitly addressed health disparities or equity.

SUMMARY

The mapping of the studies to implementation strategies from the ERIC compilation provides a framework for organizing current strategies to improve FH care. This study identifies potential areas for the development of implementation strategies to target unaddressed aspects of FH care.

Familial Hypercholesterolemia Prevalence Among Ethnicities—Systematic Review and Meta-Analysis

Background: Heterozygous familial hypercholesterolemia (FH) is a common genetic disorder leading to premature cardiovascular disease and death as a result of lifelong high plasma low-density lipoprotein cholesterol levels, if not treated early in life. The prevalence of FH varies between countries because of founder effects, use of different diagnostic criteria, and screening strategies. However, little is known about differences in FH prevalence according to ethnicity. We aimed to investigate the ethnic distribution of FH in diverse populations and estimate the prevalence of FH according to ethnicity.

Methods: We performed a systematic review and meta-analysis, searching PubMed and Web of Science for studies presenting data on the prevalence of heterozygous FH among different ethnicities in non-founder populations. Studies with more than 100 individuals, relevant data on prevalence, ethnicity, and using the Dutch Lipid Clinical Network Criteria, Simon Broome, Making Early Diagnosis Prevents Early Death, genetic screening, or comparable diagnostic criteria were considered eligible for inclusion.

Results: Eleven general population studies and two patient studies were included in a systematic review and 11 general population studies in a random-effects meta-analysis. The overall pooled FH prevalence was 0.33% or 1:303 in 1,169,879 individuals (95% confidence interval: 0.26–0:40%; 1:385–1:250). Included studies presented data on six ethnicities: black, Latino, white, Asian, brown, and mixed/other. Pooled prevalence was estimated for each group. The highest prevalence observed was 0.52% or 1:192 among blacks (0.34–0.69%; 1:294–1:145) and 0.48% or 1:208 among browns (0.31–0.74%; 1:323–1:135) while the lowest pooled prevalence was 0.25% or 1:400 among Asians (0.15–0.35; 1:500–1:286). The prevalence was 0.37% or 1:270 among Latino (0.24–0.69%; 1:417–1:145), 0.31% or 1:323 among white (0.24–0.41%; 1:417–1:244), and 0.32% or 1:313 among mixed/other individuals (0.13–0.52%; 1:769–1:192).

Conclusion: The estimated FH prevalence displays a variation across ethnicity, ranging from 0.25% (1:400) to 0.52% (1:192), with the highest prevalence seen among the black and brown and the lowest among the Asian individuals. The differences observed suggest that targeted screening among subpopulations may increase the identification of cases and thus the opportunity for prevention.

Efficacy and safety of Qushi Huayu granule for hyperlipidemia: study protocol for a randomized, double-blind, placebo-controlled trial

Background

Hyperlipidemia has become a common chronic disease worldwide in recent years. Studies have shown that hyperlipidemia patients, especially those with a high level of serum low-density lipoprotein cholesterol (LDL-C), have a significantly higher prevalence of atherosclerosis, leading to coronary heart disease. Previous basic experiments and clinical studies have shown that Qushi Huayu granules (QSHY) reduce blood lipids in patients with non-alcoholic fatty liver disease (NAFLD) accompanied by hyperlipidemia. However, the clinical efficacy of QSHY in patients with hyperlipidemia is still lacking. This study aims to investigate the effect and safety of QSHY for hyperlipidemia.

Methods

This is a randomized, double-blind, placebo-controlled trial. A total of 210 participants will be enrolled and randomized into the QSHY or placebo granules groups in equal proportions, who will receive treatment for 24 weeks. The primary outcome will be the change in LDL-C from baseline to week 12. Secondary outcomes will be changes in other serum lipids markers, life quality measuring health surveys, and traditional Chinese medicine (TCM) pattern scale. All related tests will be measured at baseline, week 12, and week 24 after enrollment. Adverse events and the safety of intervention will be monitored and evaluated.

Discussion

We designed a clinical trial of hyperlipidemia management with QSHY, a TCM prescription. The results of this trial will present the efficacy and safety of QSHY in patients with hyperlipidemia.

Trial registration

Chinese Clinical Trial Registry ChiCTR2000034125. Registered on June 25, 2019