Date of Graduation
5-2025
Document Type
Capstone
Keywords
Non-alcoholic fatty liver disease; Algorithms; Liver assessment; Fatty liver disease; Guidelines for fatty liver
Degree Name
Doctor of Nursing Practice (DNP)
Degree Level
Graduate
Advisor/Mentor
Shreve, Marilou
Committee Member
Jarrett, Anna
Abstract
Abstract
BACKGROUND
Metabolic dysfunction-associated steatotic liver disease (MASLD), also known as non-alcoholic fatty liver disease, is a growing health concern. It is a silent disease with 75% of patients being asymptomatic until reaching significant disease and having an average three-year prognosis. If caught early in the disease process, this disease can be managed successfully in the primary care setting. Primary care providers lack guidance on how to assess, diagnose, treat, and manage metabolic dysfunction-associated steatotic liver disease patients. Researchers combined clinical practice guidelines (CPG) for MASLD assessment, treatment, and management into an easy-to-use algorithm for use in the primary care setting.
AIM
To standardize assessment practices for MASLD in the primary care setting using an algorithm to improve patient outcomes.
METHODS
Descriptive and inferential statistical analysis using statistical package for the social sciences (SPSS) provided analysis of outcome measures over a four-month period. This project included analysis of pre- and post-training readiness surveys and knowledge tests using a paired T-test. Participants included fourteen healthcare professionals from a FQHC chosen from convenience and described using descriptive statistics. Bar charts and histograms are used to discuss the number of algorithm data sheets completed with FIB-4 score calculations and the number of Fibroscan referrals.
RESULTS
A statistically significant difference was observed between pre- and post-training knowledge test scores (t12.550 = 14, p < 0.001) and readiness survey scores (t5.520 = 14, p < 0.001). As a result, there was a significant increase (244%) in the number of patients assessed for risk factors for MASLD and the number of patients identified as at-risk for MASLD (n = 45) using the assessment algorithm. Although an improvement in assessment practices occurred, there was not a significant improvement in referral practices.
CONCLUSION
Metabolic dysfunction-associated steatotic liver disease is a complex disease. Providers must be provided with tools that support early MASLD detection to improve patient outcomes such as a MASLD algorithm. .
Key words: Non-alcoholic fatty liver disease; Algorithms; Liver assessment; Fatty liver disease; Guidelines for fatty liver
Core Tip: This DNP project aimed to improve patient outcomes using a MASLD assessment algorithm in the primary care setting. The goal was to align clinical practice guidelines with current clinical practice. Pre- and post-training readiness survey and knowledge test scores showed a statistically significant difference. After implementing the MASLD algorithm, assessment of patients with risk factors improved by 244% and forty-five patients were identified as being at-risk for MASLD based on their calculated FIB-4 score. However, there was no improvement in Fibroscan referral practices for patients identified as at-risk for MASLD.
Citation
Jackson, L., & Shreve, M. (2025). Improving outcomes for patients with metabolic dysfunction-associated steatotic liver disease. The Eleanor Mann School of Nursing DNP Capstone Projects. Retrieved from https://scholarworks.uark.edu/nursstudent/43
