Ozkaynak Mustafa, Dziadkowiec Oliwier, Mistry Rakesh, Callahan Tiffany, He Ze, Deakyne Sara, Tham Eric
College of Nursing, University of Colorado-Denver | Anschutz Medical Campus, Aurora, CO, USA.
College of Nursing, University of Colorado-Denver | Anschutz Medical Campus, Aurora, CO, USA.
J Biomed Inform. 2015 Oct;57:386-98. doi: 10.1016/j.jbi.2015.08.018. Epub 2015 Aug 30.
The purpose of this study was to describe a workflow analysis approach and apply it in emergency departments (EDs) using data extracted from the electronic health record (EHR) system.
We used data that were obtained during 2013 from the ED of a children's hospital and its four satellite EDs. Workflow-related data were extracted for all patient visits with either a primary or secondary diagnosis on discharge of asthma (ICD-9 code=493). For each patient visit, eight different a priori time-stamped events were identified. Data were also collected on mode of arrival, patient demographics, triage score (i.e. acuity level), and primary/secondary diagnosis. Comparison groups were by acuity levels 2 and 3 with 2 being more acute than 3, arrival mode (ambulance versus walk-in), and site. Data were analyzed using a visualization method and Markov Chains.
To demonstrate the viability and benefit of the approach, patient care workflows were visually and quantitatively compared. The analysis of the EHR data allowed for exploration of workflow patterns and variation across groups. Results suggest that workflow was different for different arrival modes, settings and acuity levels.
EHRs can be used to explore workflow with statistical and visual analytics techniques novel to the health care setting. The results generated by the proposed approach could be utilized to help institutions identify workflow issues, plan for varied workflows and ultimately improve efficiency in caring for diverse patient groups.
EHR data and novel analytic techniques in health care can expand our understanding of workflow in both large and small ED units.
本研究旨在描述一种工作流程分析方法，并将其应用于急诊科，使用从电子健康记录（EHR）系统中提取的数据。
我们使用了2013年从一家儿童医院急诊科及其四个卫星急诊科获取的数据。提取了所有出院时主要或次要诊断为哮喘（ICD-9编码=493）的患者就诊的工作流程相关数据。对于每次患者就诊，确定了八个不同的先验时间戳事件。还收集了到达方式、患者人口统计学信息、分诊评分（即 acuity 级别）以及主要/次要诊断的数据。比较组按 acuity 级别2和3划分（2比3更紧急）、到达方式（救护车与步行就诊）以及地点。使用可视化方法和马尔可夫链对数据进行分析。
为证明该方法的可行性和益处，对患者护理工作流程进行了直观和定量的比较。对EHR数据的分析有助于探索不同组之间的工作流程模式和差异。结果表明，不同的到达方式、环境和 acuity 级别会导致工作流程不同。
EHR可用于通过医疗保健领域新颖的统计和可视化分析技术来探索工作流程。所提出方法产生的结果可用于帮助机构识别工作流程问题、规划不同的工作流程，并最终提高照顾不同患者群体的效率。
医疗保健中的EHR数据和新颖的分析技术可以扩展我们对大小急诊科工作流程的理解。
