Cheng Hannah, McGovern Mark P, Garneau Hélène Chokron, Hurley Brian, Fisher Tammy, Copeland Meaghan, Almirall Daniel
Center for Behavioral Health Services and Implementation Research, Division of Public Mental Health and Population Sciences, Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Palo Alto, CA, USA.
Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Implement Sci Commun. 2022 Jul 6;3(1):72. doi: 10.1186/s43058-022-00306-1.
To combat the opioid epidemic in the USA, unprecedented federal funding has been directed to states and territories to expand access to prevention, overdose rescue, and medications for opioid use disorder (MOUD). Similar to other states, California rapidly allocated these funds to increase reach and adoption of MOUD in safety-net, primary care settings such as Federally Qualified Health Centers. Typical of current real-world implementation endeavors, a package of four implementation strategies was offered to all clinics. The present study examines (i) the pre-post effect of the package of strategies, (ii) whether/how this effect differed between new (start-up) versus more established (scale-up) MOUD practices, and (iii) the effect of clinic engagement with each of the four implementation strategies.
Forty-one primary care clinics were offered access to four implementation strategies: (1) Enhanced Monitoring and Feedback, (2) Learning Collaboratives, (3) External Facilitation, and (4) Didactic Webinars. Using linear mixed effects models, RE-AIM guided outcomes of reach, adoption, and implementation quality were assessed at baseline and at 9 months follow-up.
Of the 41 clinics, 25 (61%) were at MOUD start-up and 16 (39%) were at scale-up phases. Pre-post difference was observed for the primary outcome of percent of patient prescribed MOUD (reach) (β = 3.99; 0.73 to 7.26; p = 0.02). The largest magnitude of change occurred in implementation quality (ES = 0.68; 95% CI = 0.66 to 0.70). Baseline MOUD capability moderated the change in reach (start-ups 22.60%, 95% CI = 16.05 to 29.15; scale-ups -4.63%, 95% CI = -7.87 to -1.38). Improvement in adoption and implementation quality were moderately associated with early prescriber engagement in Learning Collaboratives (adoption: ES = 0.61; 95% CI = 0.25 to 0.96; implementation quality: ES = 0.55; 95% CI = 0.41 to 0.69). Improvement in adoption was also associated with early prescriber engagement in Didactic Webinars (adoption: ES = 0.61; 95% CI = 0.20 to 1.05).
Rather than providing an all-clinics-get-all-components package of implementation strategies, these data suggest that it may be more efficient and effective to tailor the provision of implementation strategies based on the needs of clinic. Future implementation endeavors could benefit from (i) greater precision in the provision of implementation strategies based on contextual determinants, and (ii) the inclusion of strategies targeting engagement.
为应对美国的阿片类药物危机,联邦政府史无前例地向各州和领地提供资金,以扩大预防、过量用药救援及阿片类药物使用障碍药物(MOUD)的可及性。与其他州类似,加利福尼亚州迅速分配这些资金,以在安全网、联邦合格健康中心等初级保健机构扩大MOUD的覆盖范围和采用率。在当前的实际实施工作中,向所有诊所提供了一套包含四种实施策略的方案。本研究考察了:(i)该策略方案的前后效果;(ii)这种效果在新开展(初创)与更成熟(扩大规模)的MOUD业务之间是否存在差异及如何存在差异;(iii)诊所对四种实施策略中每一种的参与程度的影响。
为41家初级保健诊所提供了四种实施策略:(1)强化监测与反馈;(2)学习协作组;(3)外部促进;(4)教学网络研讨会。使用线性混合效应模型,在基线和9个月随访时评估了RE-AIM指导下的覆盖范围、采用率和实施质量等结果。
在41家诊所中,25家(61%)处于MOUD初创阶段,16家(39%)处于扩大规模阶段。在患者开具MOUD的百分比(覆盖范围)这一主要结局上观察到前后差异(β = 3.99;0.73至7.26;p = 0.02)。变化幅度最大的是实施质量(效应量=0.68;95%置信区间=0.66至0.70)。基线MOUD能力调节了覆盖范围的变化(初创诊所为22.60%,95%置信区间=16.05至29.15;扩大规模诊所为-4.63%,95%置信区间=-7.87至-1.38)。采用率和实施质量的改善与早期处方医生参与学习协作组适度相关(采用率:效应量=0.61;95%置信区间=0.25至0.96;实施质量:效应量=0.55;95%置信区间=0.41至0.69)。采用率的改善也与早期处方医生参与教学网络研讨会相关(采用率:效应量=0.61;95%置信区间=0.20至1.05)。
这些数据表明,与其为所有诊所提供包含所有组成部分的实施策略方案,根据诊所需求定制实施策略的提供可能更高效、更有效。未来的实施工作可受益于:(i)根据背景决定因素更精确地提供实施策略;(ii)纳入针对参与度的策略。