与邮寄粪便免疫化学测试(FIT)完成相关的临床因素:支持人员的差异作用

Melinda M. Davis, J. Schneider, Amanda F. Petrik, Edward J. Miech, Brittany Younger, Anne L. Escaron, Jennifer S Rivelli, Jamie H. Thompson, Denis B Nyongesa, G. Coronado
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引用次数: 5

摘要

目的:邮寄粪便免疫化学试验(FIT)可以促进结直肠癌(CRC)的筛查。我们试图确定可修改的临床水平因素,以区分初级保健诊所在响应集中邮寄的FIT计划时FIT完成率较高与较低。方法:我们使用来自单个城市联邦合格医疗中心的15家诊所的基线观察数据,参与了一项实用试验,以优化邮寄FIT计划。临床层面的数据包括使用由实施研究综合框架(CFIR)和FIT完成率提供的指南对领导层进行访谈。我们使用模板分析来确定解释因素,并使用配置比较方法来确定临床水平条件的特定组合,这些组合独特地区分了FIT完成率较高和较低的诊所。结果我们采访了39位临床负责人,确定了58个潜在的解释因素,代表了临床工作流程和CFIR内部设置域。临床水平FIT完成率从30%到56%不等。比率较高(≥37%)的诊所的配置模型具有以下3个与支持人员相关的因素中的任何一个:(1)在过去12个月内增加了后台或前台工作人员,(2)有工作人员帮助患者解决CRC筛查的障碍,(3)有工作人员分发fit /教育患者。低发病率诊所的模型涉及这三个因素的综合缺失。结论:三个因素与支持人员区分FIT完成率高和低的诊所有关。增加非医生支持人员,并让这些人员提供支持性服务,可能有助于诊所优化邮寄FIT筛查项目。
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Clinic Factors Associated With Mailed Fecal Immunochemical Test (FIT) Completion: The Difference-Making Role of Support Staff
PURPOSE Mailed fecal immunochemical test (FIT) programs can facilitate colorectal cancer (CRC) screening. We sought to identify modifiable, clinic-level factors that distinguish primary care clinics with higher vs lower FIT completion rates in response to a centralized mailed FIT program. METHODS We used baseline observational data from 15 clinics within a single urban federally qualified health center participating in a pragmatic trial to optimize a mailed FIT program. Clinic-level data included interviews with leadership using a guide informed by the Consolidated Framework for Implementation Research (CFIR) and FIT completion rates. We used template analysis to identify explanatory factors and configurational comparative methods to identify specific combinations of clinic-level conditions that uniquely distinguished clinics with higher and lower FIT completion rates. RESULTS We interviewed 39 clinic leaders and identified 58 potential explanatory factors representing clinic workflows and the CFIR inner setting domain. Clinic-level FIT completion rates ranged from 30% to 56%. The configurational model for clinics with higher rates (≥37%) featured any 1 of the following 3 factors related to support staff: (1) adding back- or front-office staff in past 12 months, (2) having staff help patients resolve barriers to CRC screening, and (3) having staff hand out FITs/educate patients. The model for clinics with lower rates involved the combined absence of these same 3 factors. CONCLUSIONS Three factors related to support staff differentiated clinics with higher and lower FIT completion rates. Adding nonphysician support staff and having those staff provide enabling services might help clinics optimize mailed FIT screening programs.
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