巧合分析：一种建模护士工作场所体验的新方法。
Coincidence Analysis: A Novel Approach to Modeling Nurses' Workplace Experience.
机构信息
Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, Oregon, United States.
Regenstrief Institute, Indianapolis, Indiana, United States.
出版信息
Appl Clin Inform. 2022 Aug;13(4):794-802. doi: 10.1055/s-0042-1756368. Epub 2022 Aug 31.
OBJECTIVES
The purpose of this study is to identify combinations of workplace conditions that uniquely differentiate high, medium, and low registered nurse (RN) ratings of appropriateness of patient assignment during daytime intensive care unit (ICU) work shifts.
METHODS
A collective case study design and coincidence analysis were employed to identify combinations of workplace conditions that link directly to high, medium, and low RN perception of appropriateness of patient assignment at a mid-shift time point. RN members of the study team hypothesized a set of 55 workplace conditions as potential difference makers through the application of theoretical and empirical knowledge. Conditions were derived from data exported from electronic systems commonly used in nursing care.
RESULTS
Analysis of 64 cases (25 high, 24 medium, and 15 low) produced three models, one for each level of the outcome. Each model contained multiple pathways to the same outcome. The model for "high" appropriateness was the simplest model with two paths to the outcome and a shared condition across pathways. The first path comprised of the absence of overtime and a before-noon patient discharge or transfer, and the second path comprised of the absence of overtime and RN assignment to a single ICU patient.
CONCLUSION
Specific combinations of workplace conditions uniquely distinguish RN perception of appropriateness of patient assignment at a mid-shift time point, and these difference-making conditions provide a foundation for enhanced observability of nurses' work experience during hospital work shifts. This study illuminates the complexity of assessing nursing work system status by revealing that multiple paths, comprised of multiple conditions, can lead to the same outcome. Operational decision support tools may best reflect the complex adaptive nature of the work systems they intend to support by utilizing methods that accommodate both causal complexity and equifinality.
目的
本研究旨在确定工作场所条件的组合，这些组合可独特地区分日间重症监护病房（ICU）工作班次中高、中、低注册护士（RN）对患者分配适当性的评分。
方法
采用集体案例研究设计和一致性分析，以确定与中班次时 RN 对患者分配适当性的高低感知直接相关的工作场所条件组合。研究团队的 RN 成员通过应用理论和经验知识，假设了一组 55 种工作场所条件作为潜在的差异因素。这些条件源自护理中常用的电子系统导出的数据。
结果
对 64 例（高组 25 例，中组 24 例，低组 15 例）的分析产生了 3 个模型，每个模型对应一个结果水平。每个模型都包含通向同一结果的多条路径。“高”适当性模型是最简单的模型，有两条通向结果的路径，并且有一条共享的条件。第一条路径由没有加班和午后患者出院或转科组成，第二条路径由没有加班和 RN 分配给单个 ICU 患者组成。
结论
工作场所条件的特定组合可独特地区分 RN 在中班次时对患者分配适当性的感知，这些差异化条件为增强对护士在医院工作班次期间工作经验的可观察性提供了基础。本研究通过揭示由多个条件组成的多条路径可以通向相同的结果，阐明了评估护理工作系统状态的复杂性。操作决策支持工具可能最好地反映其意图支持的工作系统的复杂适应性本质，方法同时考虑因果复杂性和等终性。
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