Using Panel Management to Identify Adult Patients With High-Risk Metabolic Dysfunction-Associated Steatotic Liver Disease/Metabolic Dysfunction-Associated Steatohepatitis Fibrosis in a Primary Care Clinic: A Pilot Study.
Sarah Householder, Andrew J Loza, Vikas Gupta, Benjamin R Doolittle
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引用次数: 0
Abstract
Background: As rates of metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) rise, national organizations have released new guidance for primary care-driven detection of patients with advanced fibrosis who are most likely to have clinically relevant morbidity. Yet time constraints, workflow, and practitioner awareness limit integration of risk identification into clinical care.
Materials and methods: At the authors' primary care clinic, they implemented a panel management strategy that utilized the electronic health record to identify patients older than 35 years of age at risk for MASLD fibrosis with abnormal Fibrosis-4 (Fib-4) scores. Using a proactive model, these patients were offered elastography-based screening and follow-up appointments focused on metabolic health, with referrals to subspecialty care when indicated.
Results: Of 855 patients older than 35 years of age, 384 were identified as having risk factors for MASLD/MASH. Of these, 53 had abnormal Fib-4 scores with no prior work-up; 29 patients consented to a shear wave elastography; 16 underwent shear wave elastography; and 6 had moderate or high results concerning for at-risk fibrosis. Twenty patients attended MASLD-focused appointments. Reluctance to pursue testing was driven by skepticism surrounding preventative medicine, perceived cost, and desire to focus on other medical problems, some of which were life-limiting.
Conclusion: Panel management represents a scalable strategy to quickly identify patients in primary care most likely to experience complications from MASLD/MASH and provides a targeted intervention to direct further management. Limitations include access to care, medical complexity, and patient acceptance.