Implementation of an EHR-supported multidisciplinary lipid management program for suspected familial hypercholesterolemia: Early clinical and implementation outcomes

1. Introduction

Familial hypercholesterolemia (FH) remains substantially underdiagnosed and undertreated despite the availability of effective lipid-lowering therapies and electronic health record (EHR)-based tools capable of identifying individuals at high risk for premature atherosclerotic cardiovascular disease [1,2]. Although EHR-based screening improves recognition of patients with possible FH, identification alone does not ensure treatment intensification, genetic evaluation, or longitudinal follow-up [2,3]. Consequently, implementation strategies that integrate systematic case finding with coordinated multidisciplinary management have become a priority for improving FH care [3].

To address these gaps, we implemented an EHR-supported multidisciplinary lipid management program within a large integrated health system. The program integrated EHR-supported patient identification with nurse practitioner-led lipid management, pharmacist consultation, medication optimization, genetic testing, patient education, and longitudinal follow-up. Beyond improving case identification, the program was designed to operationalize contemporary FH guideline recommendations within routine clinical practice by coordinating diagnostic evaluation, treatment intensification, and longitudinal management across multiple disciplines. This Brief Report describes the program's early implementation experience and associated clinical outcomes.

2. Methods

This prospective implementation study evaluated an EHR-supported multidisciplinary lipid management program conducted across outpatient primary care and specialty practices within a large integrated health system. Institutional Review Board approval was obtained and all participants provided informed consent. Adults with suspected FH were identified through EHR screening (94%), clinician referral (5%), and population health outreach (1%). Although the study was registered at ClinicalTrials.gov, no participants were recruited through that registry.

Initial FH classification was based on Simon Broome criteria using clinical history, family history, clinician evaluation, and available lipid measurements and was updated, when appropriate, after genetic testing. Following enrollment, participants underwent individualized cardiovascular risk assessment, medication reconciliation, lifestyle counseling, and shared decision-making regarding lipid-lowering therapy and genetic testing. The multidisciplinary program integrated nurse practitioner-led lipid management, accountable care organization pharmacist support for medication access and optimization, lifestyle and nutrition education, genetic testing through commercial laboratories when covered by insurance, and longitudinal laboratory monitoring. Medication recommendations followed the 2022 ACC Expert Consensus Decision Pathway [4] and were individualized according to baseline therapy, LDL-C response, medication tolerance, insurance coverage, and patient preferences. The primary outcome was change in LDL-C among participants completing follow-up laboratory testing. Paired LDL-C changes were evaluated using the Wilcoxon signed-rank test (p < 0.05).

3. Results

At the time of analysis, 133 participants (66.5%) had completed protocol-defined follow-up laboratory testing. Among the remaining participants, 45 (22.5%) had reached the follow-up interval but had not yet completed laboratory testing, whereas 22 (11%) had not yet reached six months of follow-up.

Between program initiation and the time of analysis, 200 participants were enrolled. Based on Simon Broome criteria, 57 (29%) met criteria for definite FH and 133 (67%) for probable FH, resulting in an FH-enriched cohort in which 95% of participants were classified as probable or definite FH. Median baseline LDL-C was 200 mg/dL (IQR 180–231).

Participants completing follow-up laboratory testing did not differ significantly from participants eligible for follow-up but without completed laboratory testing with respect to age, race, ethnicity, or Simon Broome FH classification. Participants completing follow-up were more likely to be assigned female at birth (71%vs. 47%, p = 0.003).

Genetic testing was completed in 160 participants (80%). Insurance coverage, out-of-pocket costs, and participant preference were the most common barriers to testing completion. Pathogenic variants were identified in 36 (23%), increased-risk alleles in 7 (4%), variants of uncertain significance in 31 (19%), and negative results in 86 (54%).

Medication optimization represented a major implementation component. Among participants completing follow-up, 42 initiated statin therapy, 9 changed statin therapy, 6 underwent statin dose intensification, 16 initiated ezetimibe, 23 initiated a PCSK9 inhibitor, 4 initiated inclisiran, 3 initiated bempedoic acid, and 21 initiated another lipid-lowering therapy. Medication categories were not mutually exclusive because therapy was frequently intensified sequentially. Most participants required treatment intensification despite previous recognition of hypercholesterolemia, underscoring that patient identification alone was insufficient to achieve guideline-recommended LDL-C goals. Medication optimization frequently required sequential therapy adjustments based on treatment response, medication tolerance, and insurance approval. Among participants entering the program without lipid-lowering therapy, most initiated statin treatment, while smaller numbers initiated PCSK9 inhibitor or ezetimibe therapy.

Implementation intensity included 675 in-person clinician encounters, 243 virtual encounters, 63 nutrition and education visits, 520 laboratory visits, and 134 diagnostic testing encounters. These encounters illustrate the substantial longitudinal coordination required to support medication optimization, laboratory surveillance, patient education, genetic evaluation, and ongoing treatment adjustments within routine clinical practice.

Among participants completing follow-up laboratory testing, median LDL-C decreased from 197 mg/dL (IQR 177–225) to 113 mg/dL (IQR 81–161) (p < 0.001), representing a median LDL-C reduction of 43%. Overall, 58 participants (44%) achieved LDL-C < 100 mg/dL.

4. Discussion

This early implementation experience demonstrates that an EHR-supported multidisciplinary lipid management program can successfully operationalize contemporary FH care within routine clinical practice. Rather than relying solely on EHR-based identification, the program linked systematic case finding to coordinated nurse practitioner-led lipid management, pharmacist collaboration, medication optimization, genetic testing, patient education, and longitudinal follow-up. Because this program was implemented within routine clinical operations rather than a highly controlled research environment, the findings provide insight into the practical challenges and opportunities associated with translating FH guideline recommendations into everyday preventive cardiology practice.

The program successfully enrolled an FH-enriched population, achieved high uptake of genetic testing, and supported extensive medication optimization during routine clinical care. Similar to other reports, these findings demonstrate that successful implementation required considerably more than EHR-based patient identification [5]. Participants frequently required repeated clinical encounters, medication titration, insurance navigation, laboratory monitoring, and coordinated multidisciplinary follow-up before treatment goals could be approached. These observations highlight the complexity of translating FH guideline recommendations into routine clinical practice. Collectively, these findings suggest that implementation success depended on sustained multidisciplinary coordination rather than a single clinical intervention [5,6].

From an implementation perspective, the multidisciplinary model provides a practical framework for integrating EHR-supported case identification with coordinated longitudinal management. Rather than functioning as isolated interventions, nurse practitioner-led care, pharmacist collaboration, medication optimization, genetic testing, and patient education operated as complementary components of a single clinical pathway. This integrated approach may be particularly valuable for health systems seeking scalable strategies to improve identification and management of patients with suspected FH.

4.1. Limitations

Limitations include the single integrated health system setting and incomplete follow-up laboratory testing. However, baseline demographic characteristics, Simon Broome classification, and baseline LDL-C values were generally comparable between participants completing follow-up laboratory testing and those eligible for follow-up but without completed laboratory testing, although participants completing follow-up were more frequently assigned female at birth. Differences in healthcare engagement, medication adherence, or other unmeasured clinical factors may nevertheless have influenced completion of follow-up laboratory testing. Longer-term LDL-C durability, cardiovascular outcomes, and cascade screening remain areas for future investigation.

5. Conclusions

In this early prospective implementation experience, an EHR-supported multidisciplinary lipid pathway successfully enrolled an FH-enriched cohort, achieved high uptake of genetic testing, supported extensive medication optimization, and was associated with substantial LDL-C reduction among participants completing follow-up laboratory testing. Beyond the observed clinical outcomes, the program demonstrates the feasibility of integrating EHR-supported identification with coordinated nurse practitioner-led multidisciplinary management within routine preventive cardiology practice. This implementation model may provide a practical framework for other health systems seeking to improve identification, evaluation, and longitudinal management of patients with suspected familial hypercholesterolemia.

Central Illustration

Funding

This work is supported by an unrestricted grant from Regeneron Pharmaceuticals.

Ethical review statement

This study was reviewed and approved by the Atlantic Health Institutional Review Board (IRB Protocol No. 2096455). Written informed consent was obtained from all participants.

Declaration of generative AI and AI-assisted technologies in the manuscript preparation process

During the preparation of this work, the authors used OpenAI ChatGPT for assistance with central illustration creation. The authors reviewed and edited the output as needed and take full responsibility for the content of the published article.

CRediT authorship contribution statement

Robert D. Fishberg: Writing – review & editing, Writing – original draft, Supervision, Methodology, Investigation, Conceptualization. Jeffrey N. Feldman: Writing – review & editing, Writing – original draft, Supervision, Methodology, Investigation, Conceptualization. Deatrah Dubose: Writing – review & editing, Writing – original draft, Supervision, Resources, Project administration, Methodology, Investigation, Data curation, Conceptualization. Lise Cooper: Writing – review & editing, Writing – original draft, Validation, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. John Rutledge: Writing – review & editing, Validation, Methodology, Formal analysis, Data curation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.