EHR Alert for Fatty Liver Disease
What You Need to Know Before You Apply
What is the purpose of this trial?
This trial aims to improve the management of metabolic dysfunction-associated steatotic liver disease (MASLD) through a new electronic health record (EHR) alert. This alert assists doctors in assessing the risk of liver fibrosis (scarring) in patients with MASLD. The study will evaluate the alert's effectiveness in various clinics over time. Patients with MASLD and type 2 diabetes may be suitable candidates for this trial. As an unphased trial, it offers patients the chance to contribute to innovative healthcare solutions that could enhance future treatment strategies.
What prior data suggests that this EHR alert is safe for MASLD management?
Research has shown that electronic health record (EHR) alerts serve as a safe tool in healthcare. These alerts assist doctors by providing timely information without interrupting their workflow. Studies have not identified any safety issues directly associated with EHR alerts. They merely offer data and suggestions to healthcare providers.
For the specific EHR alert designed for metabolic dysfunction-associated steatotic liver disease (MASLD), no evidence indicates any risk to patients. EHR alerts are informational tools, not treatments that directly affect the body, and thus do not have side effects like medications might.12345Why are researchers excited about this trial?
Researchers are excited about the EHR alert for fatty liver disease because it introduces a new way to identify and assess fibrosis risk using electronic health records. Unlike traditional methods that rely on manual evaluations and patient history, this EHR alert provides automated risk assessments, potentially streamlining the diagnosis process. By integrating educational content and timely alerts directly into the clinician's workflow, it could enhance early detection and management of fatty liver disease, leading to better patient outcomes.
What evidence suggests that this EHR alert is effective for MASLD?
Research has shown that electronic health record (EHR) alerts can help doctors better manage liver diseases like metabolic dysfunction-associated steatotic liver disease (MASLD). In this trial, clinics will transition from a control phase to an intervention phase, implementing an EHR alert system. Studies have found that these alerts assist doctors in identifying and treating patients at risk for liver fibrosis, a type of liver scarring that can lead to serious health problems. By using existing patient data, the alert system can predict health issues, allowing doctors to address them sooner. This enables doctors to provide better care to patients with MASLD by acting on timely information. Overall, EHR alerts can significantly improve the treatment and monitoring of liver health.14678
Who Is on the Research Team?
Andrew Schreiner, MD, MSCR
Principal Investigator
Medical University of South Carolina
Are You a Good Fit for This Trial?
Inclusion Criteria
Timeline for a Trial Participant
Screening
Participants are screened for eligibility to participate in the trial
Control Phase
All clinics begin in the control phase before the intervention is introduced
Intervention Phase
Introduction of the MASLD fibrosis risk assessment EHR alert in a stepped wedge design
Follow-up
Participants are monitored for the implementation and effectiveness of the intervention
What Are the Treatments Tested in This Trial?
Interventions
- EHR alert
How Is the Trial Designed?
5
Treatment groups
Experimental Treatment
All clinics will begin the study in the control phase. The intervention will be introduced in 5 steps with 5-6 clinics per step at intervals of 6 months. The transition phase from the control period to the intervention period will last 1 month and provide time for rolling out educational content and access to the MASLD fibrosis risk assessment EHR alert. A computer-generated randomization program will assign clinics to one of the 5 pre-defined transition steps (months 6, 12, 18, 24, and 30).
All clinics will begin the study in the control phase. The intervention will be introduced in 5 steps with 5-6 clinics per step at intervals of 6 months. The transition phase from the control period to the intervention period will last 1 month and provide time for rolling out educational content and access to the MASLD fibrosis risk assessment EHR alert. A computer-generated randomization program will assign clinics to one of the 5 pre-defined transition steps (months 6, 12, 18, 24, and 30).
All clinics will begin the study in the control phase. The intervention will be introduced in 5 steps with 5-6 clinics per step at intervals of 6 months. The transition phase from the control period to the intervention period will last 1 month and provide time for rolling out educational content and access to the MASLD fibrosis risk assessment EHR alert. A computer-generated randomization program will assign clinics to one of the 5 pre-defined transition steps (months 6, 12, 18, 24, and 30).
All clinics will begin the study in the control phase. The intervention will be introduced in 5 steps with 5-6 clinics per step at intervals of 6 months. The transition phase from the control period to the intervention period will last 1 month and provide time for rolling out educational content and access to the MASLD fibrosis risk assessment EHR alert. A computer-generated randomization program will assign clinics to one of the 5 pre-defined transition steps (months 6, 12, 18, 24, and 30).
All clinics will begin the study in the control phase. The intervention will be introduced in 5 steps with 5-6 clinics per step at intervals of 6 months. The transition phase from the control period to the intervention period will last 1 month and provide time for rolling out educational content and access to the MASLD fibrosis risk assessment EHR alert. A computer-generated randomization program will assign clinics to one of the 5 pre-defined transition steps (months 6, 12, 18, 24, and 30).
Find a Clinic Near You
Who Is Running the Clinical Trial?
Medical University of South Carolina
Lead Sponsor
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Collaborator
National Institutes of Health (NIH)
Collaborator
Citations
Accurate prediction of all-cause mortality in patients with ...
... liver disease using electronic health records. Ann Hepatol. 2024 ... Non-alcoholic Fatty Liver Disease / diagnosis; Non-alcoholic Fatty ...
Improving diagnostic safety through STeatosis ...
MASLD (formerly nonalcoholic fatty liver disease—NAFLD) diagnosis requires documentation of hepatic steatosis (e.g., liver fat) on imaging with at least one ...
3.
liverdiseasenews.com
liverdiseasenews.com/news/algorithm-helps-diagnose-fatty-liver-disease-using-health-records/Algorithm helps to diagnose fatty liver disease using health ...
While MASLD typically doesn't cause health problems, it progresses in some cases to MASH, where excessive fat deposits start to cause ...
Electronic decision aids enhance management of primary ...
Abbreviations: eCDSS, electronic clinical decision support system; EHR, electronic health record ... fatty liver disease at risk for disease ...
Advanced Fibrosis Detection for MASLD in Primary Care
Metabolic dysfunction-associated steatotic liver disease (MASLD, formerly nonalcoholic fatty liver disease [NAFLD]) affects an estimated 1in 3 persons in ...
Accurate prediction of all-cause mortality in patients with ...
Metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed nonalcoholic fatty liver disease (NAFLD) [1,2], is defined as the presence ...
Improving diagnostic safety through steatosis identification ...
MASLD (formerly nonalcoholic fatty liver disease—NAFLD) diagnosis requires documentation of hepatic steatosis (e.g., liver fat) on imaging with ...
Real-world evidence in metabolic dysfunction-associated ...
Formerly referred to as non-alcoholic fatty liver disease (NAFLD), MASLD is a chronic liver disease characterised by the accumulation of fat in the liver ( ...
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