Assessing Clinician Engagement With a Passive Clinical Decision Support System for Liver Fibrosis Risk Stratification in a Weight Management Clinic
Authors' conclusion
This implementation strategy bundle did not achieve meaningful metabolic dysfunction-associated steatotic liver disease fibrosis risk stratification. Electronic health record-based CDSS shows promise but requires alignment with provider priorities, seamless workflow integration, and robust technical infrastructure.
Study context
- Population
- Weight management clinic visits; patients with elevated FIB-4
- Comparison
- Pre- vs postactivation of a 3-strategy implementation bundle
- Outcome
- Penetration: proportion of patients with elevated FIB-4 completing VCTE or hepatology referral
Methodological detailspre–post comparison, semi-structured provider interviews (i-PARIHS framework)
- Pre–post comparison
- Semi-structured provider interviews (i-PARIHS framework)
Main finding
As reported in the abstract
Penetration: patients with elevated FIB-4 completing VCTE or hepatology referral
- Preactivation: no vibration-controlled transient elastography (VCTE) and 2 hepatology referrals (128 elevated FIB-4 scores)
- Postactivation: 3 VCTE referrals and 2 hepatology referrals (234 elevated FIB-4 scores)
- Postactivation vs Preactivation: Fischer's exact test P value = 1.00
Further findings
Visits with automated FIB-4 scores
Visits Preactivation 3933 · Postactivation 4634
Elevated scores Preactivation 128 · Postactivation 234
Provider interviews (acceptability and feasibility) · 3 months postimplementation
- Barriers: shared responsibility with primary care, low awareness and trust in risk-stratification tools, workflow challenges, competing demands
- Educational outreach and facilitation improved clinical decision support system (CDSS) engagement; technical issues reduced it
Original publication
Assessing Clinician Engagement With a Passive Clinical Decision Support System for Liver Fibrosis Risk Stratification in a Weight Management Clinic. Endocr Pract. Published 25 April 2025. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →