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Supplementary figure: A clinical decision support tool for metabolic dysfunction-associated steatohepatitis in real-world clinical settings: a mixed-method implementation research study protocol

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posted on 2024-09-20, 11:30 authored by Jesse Fishman, Theresa Alexander, Yestle Kim, Iris Kindt, Patricia Mendez

These are peer-reviewed supplementary materials for the article 'A clinical decision support tool for metabolic dysfunction-associated steatohepatitis in real-world clinical settings: a mixed-method implementation research study protocol' published in the Journal of Comparative Effectiveness Research.

  • Supplementary Figure 1A-B

Aim: A clinical decision support (CDS) tool for metabolic dysfunction-associated steatohepatitis (MASH) was developed to align health systems with clinical guidelines detailed in the MASH Clinical Care Pathway and improve patients’ proactive self-management of their disease. The tool includes a provider-facing web-based application and a mobile application (app) for patients. This protocol outlines a pilot study that will systematically evaluate the implementation of the tool in real-world clinical practice settings. Materials & methods: This implementation research study will use a simultaneous mixed-methods design and is guided by the Consolidated Framework for Implementation Research. The CDS tool for MASH will be piloted for ≥3 months at multiple US-based sites with eligible gastroenterologists and hepatologists (n = 5–10 per site) and their patients (n = 50–100 per site) with MASH or suspected MASH. Each pilot site may choose one or all focus areas within the tool (i.e., risk stratification, screening and referral, or patient care management), based on on-site capabilities. Prior to and at the end of the pilot period, providers and patients will complete quantitative surveys and partake in semi-structured interviews. Outcomes will include understanding the feasibility of implementing the tool in real-world clinical settings, its effectiveness in increasing patient screenings and risk stratification for MASH, its ability to improve provider and patient knowledge of MASH, barriers to adoption of the tool and the tool’s capacity to enhance patient engagement and satisfactionwith their care. Conclusion: Findings will inform the scalable implementation of the tool to ensure patients at risk for MASH are identified early, referred to specialty care when necessary and managed appropriately. Successful integration of the patient app can contribute to better health outcomes for patients by facilitating their active participation in the management of their condition.

Funding

This work was supported by Madrigal Pharmaceuticals, Inc. Publication costs were funded by Madrigal Pharmaceuticals, Inc.

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