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一项多成分临床护理路径(MCCP)改善基层医疗中MAFLD诊断与管理的整群随机试验:研究方案。

A cluster randomized trial of a Multicomponent Clinical Care Pathway (MCCP) to improve MASLD diagnosis and management in primary care: study protocol.

作者信息

Godwin Kyler M, Grigoryan Larissa, Thrift Aaron P, Duong Hao, Kanwal Fasiha, Giardina Traber, Kadiyala Himabindu, Zimolzak Andrew, Patidar Kavish R, El-Serag Hashem B

机构信息

Department of Medicine, Section of Health Services Research, Baylor College of Medicine, Houston, TX, USA.

Center for Innovations in Quality, Effectiveness and Safety (IQuESt), Michael E. DeBakey Veterans Affairs Medical Center, 2002 Holcombe Blvd. (152), Houston, TX, 77030, USA.

出版信息

BMC Health Serv Res. 2025 May 6;25(1):645. doi: 10.1186/s12913-025-12737-2.

Abstract

BACKGROUND

Metabolic dysfunction associated steatotic liver disease (MASLD) is the most common chronic liver disorder in the world. Most patients with MASLD are undiagnosed, untreated and unreferred. Treatment depends on diagnosis and accurate staging of fibrosis risk, and therefore screening at the primary care setting coupled with consistent, timely, evidence-based, widely accessible, and testable management processes is critical. Randomized controlled trials of methods for screening, diagnosis, severity stratification, and referral are lacking. We previously validated the MASLD clinical care pathway (MCCP), a multistep algorithmic process geared to support primary care settings in screening, diagnosis, risk stratification, and suggested referral and treatment of patients with MASLD. We will evaluate the effectiveness of the MCCP intervention compared to usual care in improving MASLD care process and patient outcomes.

METHODS

A two-arm, parallel, cluster-randomized trial will assess the effect of the MCCP intervention comprised of an e-trigger and structured provider education on screening, diagnosis, referral, and treatment for MASLD. Clusters are Veterans Affairs (VA) patient-centered primary care clinics, called Patient Aligned Care Teams (PACTs). This 4-year study will include three phases: (1) formative assessment to explore barriers to feasibility and acceptability of intervention among providers and patients and adapt MCCP for utilization by VA PACTs, (2) cluster-randomized trial to examine the effectiveness of the MCCP compared to usual care, and (3) summative evaluation to identify patient and provider characteristics associated with effectiveness of MCCP and plan for future implementation. The primary outcome will be a composite dichotomous variable for making a new MASLD diagnosis and completing severity risk stratification of MASLD. Secondary outcomes include referral and receipt of hepatology specialty care for patients with MASLD and advanced fibrosis.

DISCUSSION

Our randomized controlled trial will be the first to systematically implement the MCCP using strategies that are clinically relevant, adaptable and scalable. If successful, the MCCP will improve outcomes for patients with MASLD through early detection, accurate risk stratification, and timely treatment within primary care settings.

TRIAL REGISTRATION

This trial has been registered on clinicaltrails.gov (# NCT06671886), registration date: 10-31-2024.

摘要

背景

代谢功能障碍相关脂肪性肝病(MASLD)是全球最常见的慢性肝脏疾病。大多数MASLD患者未被诊断、未接受治疗且未被转诊。治疗取决于纤维化风险的诊断和准确分期,因此在初级保健机构进行筛查,并结合一致、及时、基于证据、广泛可及且可检验的管理流程至关重要。目前缺乏关于筛查、诊断、严重程度分层和转诊方法的随机对照试验。我们之前验证了MASLD临床护理路径(MCCP),这是一个多步骤算法流程,旨在支持初级保健机构对MASLD患者进行筛查、诊断、风险分层,并建议转诊和治疗。我们将评估与常规护理相比,MCCP干预在改善MASLD护理流程和患者结局方面的有效性。

方法

一项双臂、平行、整群随机试验将评估由电子触发和结构化提供者教育组成的MCCP干预对MASLD筛查、诊断、转诊和治疗的效果。整群为退伍军人事务部(VA)以患者为中心的初级保健诊所,称为患者对齐护理团队(PACTs)。这项为期4年的研究将包括三个阶段:(1)形成性评估,以探索提供者和患者中干预可行性和可接受性的障碍,并使MCCP适用于VA PACTs使用;(2)整群随机试验,以检验MCCP与常规护理相比的有效性;(3)总结性评估,以确定与MCCP有效性相关的患者和提供者特征,并规划未来实施。主要结局将是一个复合二分变量,用于做出新的MASLD诊断并完成MASLD严重程度风险分层。次要结局包括MASLD和晚期纤维化患者转诊并接受肝病专科护理。

讨论

我们的随机对照试验将是首个使用临床相关、可适应且可扩展策略系统实施MCCP的试验。如果成功,MCCP将通过在初级保健机构中早期检测、准确风险分层和及时治疗来改善MASLD患者的结局。

试验注册

本试验已在clinicaltrails.gov上注册(# NCT06671886),注册日期:2024年10月31日。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66bd/12054218/cc0b3b4fb786/12913_2025_12737_Fig1_HTML.jpg

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