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A principal components analysis of factors associated with successful implementation of an LVAD decision support tool

机译：与LVAD决策支持工具成功实施相关的因素分析

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A central goal among researchers and policy makers seeking to implement clinical interventions is to identify key facilitators and barriers that contribute to implementation success. Despite calls from a number of scholars, empirical insights into the complex structural and cultural predictors of why decision aids (DAs) become routinely embedded in health care settings remains limited and highly variable across implementation contexts. We examined associations between “reach”, a widely used indicator (from the RE-AIM model) of implementation success, and multi-level site characteristics of nine LVAD clinics engaged over 18?months in implementation and dissemination of a decision aid for left ventricular assist device (LVAD) treatment. Based on data collected from nurse coordinators, we explored factors at the level of the organization (e.g. patient volume), patient population (e.g. health literacy; average sickness level), clinician characteristics (e.g. attitudes towards decision aid; readiness for change) and process (how the aid was administered). We generated descriptive statistics for each site and calculated zero-order correlations (Pearson’s?r) between all multi-level site variables including cumulative reach at 12?months and 18?months for all sites. We used principal components analysis (PCA) to examine any latent factors governing relationships between and among all site characteristics, including reach. We observed strongest inclines in reach of our decision aid across the first year, with uptake fluctuating over the second year. Average reach across sites was 63% (s.d.?=?19.56) at 12?months and 66% (s.d.?=?19.39) at 18?months. Our PCA revealed that site characteristics positively associated with reach on two distinct dimensions, including a first dimension reflecting greater organizational infrastructure and standardization (characteristic of larger, more established clinics) and a second dimension reflecting positive attitudinal orientations, specifically, openness and capacity to give and receive decision support among coordinators and patients. Successful implementation plans should incorporate specific efforts to promote supportive and mutually informative interactions between clinical staff members and to institute systematic and standardized protocols to enhance the availability, convenience and salience of intervention tool in routine practice. Further research is needed to understand whether “core predictors” of success vary across different intervention types.
机译：寻求实施临床干预措施的研究人员和决策者之间的核心目标是确定有助于执行成功的关键促进者和障碍。尽管来自许多学者的呼叫，但经验丰富地洞察力的结构和文化预测因子为什么决策辅助（DAS）在卫生保健环境中常规嵌入在实现上下文中仍然有限和高度变化。我们在执行成功的实施成功的“REACH”，广泛使用的指标（从重新瞄准模型）之间进行了审查的协会，九个LVAD诊所的多级别站点特征超过18个月的实施和传播左心室的决策援助辅助装置（LVAD）治疗。基于从护士协调员收集的数据，我们在组织的水平（例如患者体积），患者人口（例如健康识字率），临床医生特征（例如对决策援助的态度;改变的态度）和过程的因素（如何管理援助）。我们为每个站点生成了描述性统计数据，并在所有多级站点变量之间计算了零级相关性（Pearson？R），包括累积达到12个月和18个月的所有网站。我们使用了主成分分析（PCA）来检查所有网站特征之间和包括触及的所有网站特征之间的潜在因子。我们观察到第一年的决策援助的最强烈倾向，在第二年的摄取波动。跨地网站的平均范围为63％（S.D.?=?19.56），12个月和66％（S.D.?=?19.39），在18岁？几个月。我们的PCA透露，在两个明显的尺寸下，网站特征与达到达到的两个不同尺寸，包括反映更大的组织基础设施和标准化（更大，更熟悉的诊所）的标准化和反映积极态度取向的第二维度，具体地，开放性和能力的第二维度并获得协调员和患者之间的决策支持。成功的实施计划应纳入具体努力，以促进临床工作人员与临床工作人员之间的支持和相互信息互动，并在常规实践中提高干预工具的可用性，便利性和显着性。需要进一步研究来了解成功的“核心预测因子”是否跨不同的干预类型不同。

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