Graduate Program in Computer Science (PPGIa), Pontifícia Universidade Católica do Paraná (PUCPR), Curitiba, Brazil; Instituto Federal do Paraná, Curitiba, Brazil.
Graduate Program in Production and Systems Engineering (PPGEPS), Pontifícia Universidade Católica do Paraná (PUCPR), Curitiba, Brazil.
J Biomed Inform. 2020 Nov;111:103582. doi: 10.1016/j.jbi.2020.103582. Epub 2020 Sep 30.
To describe a method of analysis for understanding the health care process, enriched with information on the clinical and profile characteristics of the patients. To apply the proposed technique to analyze an ischemic stroke dataset.
We analyzed 4,830 electronic health records (EHRs) from patients with ischemic stroke (2010-2017), containing information about events realized during treatment and clinical and profile information of the patients. The proposed method combined process mining techniques with data analysis, grouping the data by primary care units (PCU - units responsible for the primary care of patients residing in a geographical area).
A novel method, named process, data, and management (PDM) analysis method was used for ischemic stroke data and it provided the following outcomes: health care process for patients with ischemic stroke with time statistics; analysis of potential factors for slow hospital admission indicating an increase in the time to hospital admission of 3.4 h (mean value) for patients with an origin at the urgent care center (UCC) - 30% of patients; analysis of PCUs with distinct secondary stroke rates indicating that the social class of patients is the main difference between them; and the visualization of risk factors (before the stroke) by the PCU to inform the health manager about the potential of prevention.
PDM analysis describes a step-by-step method for combining process analysis with data analysis considering a management focus. The results obtained on the stroke context can support the definition of more refined action plans by the health manager, improving the stroke health care process and preventing new events.
When a patient is diagnosed with ischemic stroke, immediate treatment is needed. Moreover, it is possible to prevent new events to some degree by monitoring and treating risk factors. PDM analysis provides an overview of the health care process with time, combining elements that affect the treatment flow and factors, which can indicate a potential for preventing new events. We also can apply PDM analysis in different scenarios, when there is information about activities from treatment flow and other characteristics related to the treatment or the prevention of the analyzed disease. The management focus of the results aids in the formulation of service policies, action plans, and resource allocation.
描述一种分析方法,用于理解医疗保健过程,并丰富患者的临床和特征信息。将提出的技术应用于分析缺血性脑卒中数据集。
我们分析了 4830 份来自缺血性脑卒中患者(2010-2017 年)的电子健康记录(EHR),其中包含治疗期间实现的事件以及患者的临床和特征信息。所提出的方法将流程挖掘技术与数据分析相结合,按初级保健单位(PCU-负责居住在地理区域内的患者初级保健的单位)对数据进行分组。
一种名为流程、数据和管理(PDM)分析方法的新方法被用于缺血性脑卒中数据,它提供了以下结果:缺血性脑卒中患者的医疗保健流程及其时间统计;分析导致住院时间延长的潜在因素,表明来自急救中心(UCC)的患者的住院时间平均延长 3.4 小时(30%的患者);分析具有不同二次中风率的 PCU,表明患者的社会阶层是它们之间的主要区别;以及通过 PCU 可视化风险因素(中风前),告知卫生经理预防的潜力。
PDM 分析描述了一种将流程分析与数据分析相结合的分步方法,同时考虑管理重点。在中风背景下获得的结果可以支持卫生经理制定更精细的行动计划,改善中风医疗保健流程并预防新事件。
当患者被诊断出患有缺血性脑卒中时,需要立即进行治疗。此外,通过监测和治疗风险因素,在某种程度上可以预防新事件。PDM 分析提供了一个具有时间的医疗保健流程概述,将影响治疗流程的元素和因素结合在一起,可以指示预防新事件的潜力。我们还可以将 PDM 分析应用于不同的场景,当有关于治疗流程的活动信息和与所分析疾病的治疗或预防相关的其他特征时。结果的管理重点有助于制定服务政策、行动计划和资源分配。