Improving detection and management of familial hypercholesterolaemia in Australian general practice

Implementation science and genetic testing for familial hypercholesterolemia

PURPOSE OF REVIEW

Familial hypercholesterolemia is a treatable genetic disorder of cholesterol metabolism. Genetic testing is the most specific method for diagnosing familial hypercholesterolemia, but it remains underutilized. Implementation science aims to bridge the gap between evidence and practice and, thereby, support improved familial hypercholesterolemia care. This review presents the current evidence on the use of implementation science to improve the use of genetic testing for familial hypercholesterolemia.

RECENT FINDINGS

Recent research has focused on developing implementation strategies to improve the use of genetic testing, particularly cascade testing of at-risk blood relatives of known familial hypercholesterolemia cases. Stakeholder informed strategies aimed at improving communication between families and detection of familial hypercholesterolemia in primary care have been developed and implemented. Findings demonstrate implementation science methods can help remove barriers and improve the uptake of cascade genetic testing.

SUMMARY

Significant gaps in familial hypercholesterolemia care emphasize the importance of practical and realistic approaches to improve the detection of this preventable cause of premature heart disease, and recent efforts using implementation science have shown some promising results. More implementation science studies are needed that address the considerable gaps in familial hypercholesterolemia care, including the underutilization of genetic testing, so that all individuals receive the best clinical care.

Developing a national implementation strategy for enhancing the detection of familial hypercholesterolemia: An Australian experience

BACKGROUND

Familial hypercholesterolemia (FH) is a common and treatable inherited condition of cholesterol metabolism that increases cardiovascular health risk. Less than 10% of people with FH have been detected and few receive recommended treatment.

OBJECTIVE

We report on the development of a national implementation strategy for enhancing the detection of FH in Australia.

METHODS

A modified intervention mapping study was conducted, through workshops to identify barriers and facilitators of FH detection, models for detection and their objectives. Practical implementation strategies were selected using a constructivist analysis and summaries of the strategies were disseminated for feedback. A case study showcase was used to monitor strategy implementation.

RESULTS

Potential models for FH detection were identified, including (1) use of pathology lab reports and recall; (2) screening in general practice, pharmacy, and Aboriginal Community Controlled Health Organizations; (3) screening in cardiovascular inpatients, outpatients, and rehabilitation; (4) universal screening; and (5) centralized coordination of primary-tertiary shared care. Implementation strategies were selected for each model to support their operationalization into routine care. A list of general implementation strategies was also produced that could support multiple models for FH detection.

CONCLUSION

We identified multiple FH detection models and strategies that would support implementation across Australia. Centralized coordination of a primary-tertiary shared care model was described as a promising approach for integrating index case detection with family cascade testing. We provide a set of implementation recommendations for policy and practice to enhance the detection of FH in Australia.

Preconception health risk factors documented in general practice electronic medical records

BACKGROUND

Documenting medical and lifestyle preconception health risk factors in electronic medical records (EMRs) could assist general practitioners (GPs) to identify those reproductive-aged women who could most benefit from preconception care (PCC). However, it is unclear to what extent PCC risk factors are identifiable in general practice records. This study aimed to determine the extent to which medical and lifestyle preconception health risk factors are documented in general practice EMRs.

METHODS

We conducted an audit of the documentation of medical and lifestyle preconception risk factors in 10 general practice EMRs in Melbourne, Australia. We retrospectively analysed the EMRs of 100 consecutive women aged 18-44 years who visited each practice between January and September 2022. Using a template informed by PCC guidelines, we extracted data from structured fields in the EMR and conducted a descriptive analysis.

RESULTS

Among the data extracted, the more commonly documented medical and lifestyle preconception health risk factors in the EMRs included smoking (79%), blood pressure (74%), alcohol consumption (63%) and body mass index (57%). Among the women audited, 14% were smokers, 24% were obese, 7% had high blood pressure, 5% had diabetes, 28% had a mental health condition, 13% had asthma, 6% had thyroid disease and 17% had been prescribed and could be using a potentially teratogenic medication.

CONCLUSIONS

Better documentation of medical and lifestyle preconception health risk factors in structured fields in EMRs may potentially assist primary care providers including GPs in identifying and providing PCC to women who could most benefit from it.

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.

A mixed methods study of the awareness and management of familial hypercholesterolaemia in Irish general practice

Introduction

Familial Hypercholesterolemia (FH) is one of the most common genetic disorders, with an estimated global prevalence of 1:200-500, which leads to premature cardiovascular disease. Nevertheless, public and professional awareness of FH is often lacking, with an estimated 20,000 largely undiagnosed cases in Ireland.

Purpose

The overall aim of the project was to test the feasibility of a model of care that would include electronic record screening, clinical assessment, and coding of possible FH patients across a network of general practices in Ireland. In addition, a secondary aim was to gauge the awareness and knowledge of FH across the network.

Methods

This study took part in multiple phases, employing a mixed methods design. The study included a validated questionnaire, tailored online educational resources, a retrospective chart review of patients with a history of elevated LDL cholesterol (LDLc) and an active review with a selection of those patients. Results were analyzed using SPSS V27, where descriptive statistics and relevant correlation tests were employed.

Results

Eighteen general practices agreed to take part in the study. In the initial survey, respondents rated their personal and practice familiarity with FH as slightly below average. Around one-third of respondents were not aware of FH guidelines. Of over 55,000 adult patient records searched, only 0.2% had a recorded FH diagnosis and 3.9% had ever had an LDLc above 4.9 mmol/l. Eight practices completed 198 chart reviews. Among these, 29.8% of patients had a family history recorded, and 22.2% had a family history of CVD recorded. Female patients had higher averages for highest and recent LDLc. Seventy patients underwent a clinical review-with 27% of these patients identified as "probable" or "definite FH." There was a statistically significant (p = 0.002) relationship between FH status and whether the patient had other CVD risk factors.

Conclusion

General practitioners in Ireland had similar levels of awareness of FH compared to findings from elsewhere. The activities discussed encouraged clinicians to consider FH when talking to their patients, especially those with elevated LDLc at an early age. Broader awareness of the condition could increase conversations about FH and benefit patient outcomes.

Healthcare worker-based opportunistic screening for familial hypercholesterolemia in a low-resource setting

Background & objective

Heterozygous familial hypercholesterolemia (FHeH) is important risk factor for premature coronary artery disease (CAD). Strategies for its diagnosis and prevalence have not been well studied in India. We performed healthcare worker-based opportunistic screening to assess feasibility for determining its prevalence.

Methods

A healthcare worker was trained in use of Dutch Lipid Clinic Network (DLCN) criteria for diagnosis of FHeH. Successive eligible individuals (n = 3000 of 3450 screened) presenting to biochemistry laboratories of two hospitals for blood lipid measurements were evaluated for FHeH. Cascade screening or genetic studies were not performed. Descriptive statistics are reported.

Results

We included 2549 participants (men 1870, women 679) not on statin therapy. Health worker screened 25–30 individuals/day in 6–10 minutes each. The mean age was 46.2±11y. Variables of DLCN criteria were more in women vs men: family history 51.1 vs 35.6%, past CAD 48.2 vs 20.1%, arcus cornealis 1.1 vs 0.3%, tendon xanthoma 0.3 vs 0.1%, and LDL cholesterol 190–249 mg/dl in 8.5 vs 2.4%, 250–329 mg/dl in 0.7 vs 0% and ≥330 mg/dl in 0.3 vs 0% (p<0.01). Definite FHeH (DLCN score >8) was in 15 (0.59%, frequency 1:170) and probable FHeH (score 6–8) in 87 (3.4%, frequency 1:29). The prevalence was significantly greater in women, age <50y and in those with hypertension, diabetes and known CAD.

Conclusions

Healthcare worker-led opportunistic screening for diagnosis of FHeH using DLCN criteria is feasible in low-resource settings. The results show significant prevalence of clinically detected definite and probable FHeH in the population studied.

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.

Improving Familial Hypercholesterolemia Diagnosis Using an EMR-based Hybrid Diagnostic Model

CONTEXT

Familial hypercholesterolemia (FH) confers a greatly increased risk for premature cardiovascular disease, but remains very underdiagnosed and undertreated in primary care populations.

OBJECTIVE

We assessed whether using a hybrid model consisting of 2 existing FH diagnostic criteria coupled with electronic medical record (EMR) data would accurately identify patients with FH in a Midwest US metropolitan healthcare system.

METHODS

We conducted a retrospective, records-based, cross-sectional study using datasets from unique EMRs of living patients. Using Structured Query Language to identify components of 2 currently approved FH diagnostic criteria, we created a hybrid model to identify individuals with FH.

RESULTS

Of 264 264 records analyzed, between 794 and 1571 patients were identified as having FH based on the hybrid diagnostic model, with a prevalence of 1:300 to 1:160. These patients had a higher prevalence of premature coronary artery disease (CAD) (38-58%) than the general population (1.8%) and higher than those having a high CAD risk but no FH (10%). Although most patients were receiving lipid-lowering therapies (LLTs), only 50% were receiving guideline-recommended high-intensity LLT.

CONCLUSION

Using the hybrid model, we identified FH with a higher clinical and genetic detection rate than using standard diagnostic criteria individually. Statin and other LLT use were suboptimal and below guideline recommendations. Because FH underdiagnosis and undertreatment are due partially to the challenges of implementing existing diagnostic criteria in a primary care setting, this hybrid model potentially can improve FH diagnosis and subsequent early access to appropriate treatment.

Statin treatment and LDL-cholesterol treatment goal attainment among individuals with familial hypercholesterolaemia in primary care

Objectives

Guidance recommends statin treatment in familial hypercholesterolaemia (FH) to achieve at least a 50% reduction in low-density lipoprotein cholesterol (LDL-C). We assessed statin prescribing rates and LDL-C treatment goal attainment among individuals with FH in primary care.

Methods

Using primary care electronic health records from the UK Clinical Practice Research Datalink, we identified adults with recorded diagnosis of FH, statin treatment and measures of LDL-C prior to (baseline) and 12 months after initiating statin treatment. The percentage change in LDL-C was determined, and then baseline and treatment characteristics were assessed by LDL-C treatment goal attainment.

Results

Of 3064 adults (mean age 50.8 years) with recorded diagnosis of FH and repeat LDL-C measures, 50% reduction in LDL-C from baseline was attained in 895 individuals (29.2%) in 12 months. Compared with those who did not attain this goal, these people were predominantly women; they were older at time of FH diagnosis (53.4 years vs 49.7 years) and first statin treatment (53.2 years vs 49.2 years) and had higher pretreatment total cholesterol (8.20 (SD 1.38) mmol/L vs 7.57 (SD 1.39) mmol/L) and pretreatment LDL-C (5.83 (SD 1.36) mmol/L vs 5.25 (SD 1.40) mmol/L). A higher proportion of individuals who attained the treatment goal was prescribed high-potency and medium-potency statins (24.3% and 71.7% vs 20.2% and 69.3%, respectively).

Conclusions

Less than a third of individuals on statin treatment for FH in the community achieve recommended reductions in LDL-C. Greater awareness and optimisation of treatment for FH using higher-potency statins are needed.

Comparing the performance of the novel FAMCAT algorithms and established case-finding criteria for familial hypercholesterolaemia in primary care

OBJECTIVE

Familial hypercholesterolaemia (FH) is a common inherited disorder causing premature coronary heart disease (CHD) and death. We have developed the novel Familial Hypercholesterolaemia Case Ascertainment Tool (FAMCAT 1) case-finding algorithm for application in primary care, to improve detection of FH. The performance of this algorithm was further improved by including personal history of premature CHD (FAMCAT 2 algorithm). This study has evaluated their performance, at 95% specificity, to detect genetically confirmed FH in the general population. We also compared these algorithms to established clinical case-finding criteria.

METHODS

Prospective validation study, in 14 general practices, recruiting participants from the general adult population with cholesterol documented. For 260 participants with available health records, we determined possible FH cases based on FAMCAT thresholds, Dutch Lipid Clinic Network (DLCN) score, Simon-Broome criteria and recommended cholesterol thresholds (total cholesterol >9.0 mmol/L if ≥30 years or >7.5 mmol/L if <30 years), using clinical data from electronic and manual extraction of patient records and family history questionnaires. The reference standard was genetic testing. We examined detection rate (DR), sensitivity and specificity for each case-finding criteria.

RESULTS

At 95% specificity, FAMCAT 1 had a DR of 27.8% (95% CI 12.5% to 50.9%) with sensitivity of 31.2% (95% CI 11.0% to 58.7%); while FAMCAT 2 had a DR of 45.8% (95% CI 27.9% to 64.9%) with sensitivity of 68.8% (95% CI 41.3% to 89.0%). DLCN score ≥6 points yielded a DR of 35.3% (95% CI 17.3% to 58.7%) and sensitivity of 37.5% (95% CI 15.2% to 64.6%). Using recommended cholesterol thresholds resulted in DR of 28.0% (95% CI 14.3% to 47.6%) with sensitivity of 43.8% (95% CI 19.8% to 70.1%). Simon-Broome criteria had lower DR 11.3% (95% CI 6.0% to 20.0%) and specificity 70.9% (95% CI 64.8% to 76.5%) but higher sensitivity of 56.3% (95% CI 29.9% to 80.2%).

CONCLUSIONS

In primary care, in patients with cholesterol documented, FAMCAT 2 performs better than other case-finding criteria for detecting genetically confirmed FH, with no prior clinical review required for case finding.

TRIAL REGISTRATION NUMBER

NCT03934320.