Central Texas Veterans Health System, Temple, Texas, USA.
Sue & Bill Gross School of Nursing, University of California Irvine, Irvine, California, USA.
J Nurs Scholarsh. 2023 Nov;55(6):1238-1247. doi: 10.1111/jnu.12926. Epub 2023 Aug 21.
The Clinical Nurse Leader (CNL) care model is a different way of organizing frontline nursing care delivery in contrast to the traditional "staff nurse" model and is increasingly being adopted by health systems across the United States and abroad. However, variability in implementation and outcomes has been noted across health settings.
A recently validated CNL Practice Model provides an explanatory pathway for CNL model integration into practice. The purpose of this study was to identify and compare patterns of empirical correspondence to the CNL Practice Model and predict their influence on implementation success.
We conducted a secondary analysis of a 2015 national-level study with clinicians and administrators involved with CNL initiatives in their health system. A psychometrically validated CNL Practice Survey was used to collect data measuring the presence (0%-100%) of the five domains of the CNL Practice Model (organizational readiness, CNL structuring, CNL practices, outcomes, and value) and one measure of CNL implementation success. We modeled the complex hierarchical structure of the data using a Bayesian multilevel regression mixed modeling approach. A zero-one-inflated beta distribution, a mixture of Bernoulli distributions for the minimum and maximum responses and a beta distribution for the responses between the minimum and maximum, was used to fit success ratings in the model.
A total of 920 participants responded, 540 (59%) provided success scores. The model captured ratings skewed toward upper bound, while also adequately modeling data between the minimum and maximum values. The Bayesian model converged and gave estimates for all hierarchical parameters, which would likely have failed to converge in a pure maximum likelihood framework. The variability around success score across CNL Practice Model element ratings was greatest at the component level, 0.29 (0.18-0.48), compared to either the domain level, 0.16 (0.01-0.54), or the item level, 0.09 (0.01-0.17). The components most predictive of implementation success were (a) consensus CNL model can close gaps, (b) organization level implementation strategy, and (c) alignment of empirical CNL microsystem level structuring to the model's conceptualization.
Findings provide further empirical evidence to support the explanatory pathway proposed by the CNL Practice Model and identified specific organizational readiness and CNL workflow structures that are critical antecedents predictive of CNL practice manifestation and production of expected outcomes. Findings indicate actionable implementation evidence that can be successfully adopted across real-world healthcare settings to achieve safer and higher quality patient care.
CNL integrated care delivery is a frontline nursing care model that is being increasingly adopted by health systems across the United States and abroad. However, variability in CNL implementation and outcomes has been noted across health settings, limiting its evidence base. Findings of this study contribute a better understanding about the variability of CNL practice and outcomes found in the literature and contribute empirical and conceptual clarity about the relationships between modes of CNL implementation and successful adoption in healthcare settings.
临床护士领导者（CNL）护理模式是一种与传统“护士”模式不同的组织前线护理服务提供方式，越来越多地被美国和国外的医疗系统采用。然而，在不同的医疗环境中已经注意到实施和结果的可变性。
最近经过验证的 CNL 实践模型为 CNL 模型融入实践提供了解释途径。本研究的目的是确定和比较与 CNL 实践模型的经验对应模式，并预测它们对实施成功的影响。
我们对 2015 年一项全国性研究进行了二次分析，该研究涉及参与其医疗系统中 CNL 计划的临床医生和管理人员。使用经过心理测量验证的 CNL 实践调查来收集数据，该数据衡量了 CNL 实践模型的五个领域（组织准备、CNL 结构、CNL 实践、结果和价值）的存在（0%-100%）以及 CNL 实施成功的一个衡量标准。我们使用贝叶斯多层次回归混合建模方法对数据的复杂层次结构进行建模。使用零一膨胀 beta 分布、最小和最大响应的伯努利分布混合物以及最小和最大之间的响应的 beta 分布来拟合模型中的成功评分。
共有 920 名参与者做出了回应，其中 540 名（59%）提供了成功评分。该模型捕获了偏向上限的评分，同时也充分模拟了最小和最大之间的数据。贝叶斯模型收敛，并为所有层次参数提供了估计值，这些参数在纯最大似然框架中可能无法收敛。在 CNL 实践模型要素评分方面，成功评分的变异性在组件级别最大，为 0.29（0.18-0.48），而在域级别为 0.16（0.01-0.54），或在项目级别为 0.09（0.01-0.17）。最能预测实施成功的组件是（a）共识 CNL 模型可以缩小差距，（b）组织层面的实施策略，以及（c）经验性 CNL 微观系统层面结构与模型概念化的一致性。
研究结果进一步提供了支持 CNL 实践模型提出的解释途径的实证证据，并确定了特定的组织准备和 CNL 工作流程结构，这些结构是预测 CNL 实践表现和产生预期结果的关键前提。研究结果表明，在现实医疗环境中，可以成功采用有针对性的实施证据，以实现更安全、更高质量的患者护理。
CNL 综合护理服务是一种正在被美国和国外的医疗系统越来越多地采用的前沿护理服务模式。然而，在不同的医疗环境中已经注意到 CNL 的实施和结果存在可变性，限制了其证据基础。本研究的结果有助于更好地理解文献中发现的 CNL 实践和结果的可变性，并为 CNL 实施模式与医疗环境中成功采用之间的关系提供实证和概念上的明确性。
