Liu Luwei, Kang Min-Jeoung, Sainlaire Michael, Lowenthal Graham, Martel Tanya, Cho Sandy, Furlong Debra, Gilles-Fowler Wadia, Goncalves Luciana Schleder, Herlihy Lisa, Baris Veysel Karani, Massaro Jacqueline, Melanson Beth, Morrow Lori D, Wolski Paula, Song Wenyu, Dykes Patricia C
Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Harvard Medical School, Boston, MA, USA.
AMIA Annu Symp Proc. 2025 May 22;2024:738-747. eCollection 2024.
The complexity of health care processes present significant challenges for using Electronic Health Records (EHR) data to build high fidelity phenotypes. This study leverages a healthcare process modeling (HPM) approach to enable understanding of EHR-based pressure injury (PrI) data patterns needed for building a standardized PrI phenotyping pipeline. The PrI HPM was developed and validated using mixed methods, including exploratory sequential design, through interdisciplinary collaboration among clinical experts, data scientists, database analysts, and informaticians. zThe qualitative analysis identified the dynamics between PrI care and the associated clinical documentation processes. The quantitative analysis identified inherent challenges and limitations of the PrI data. The PrI HPM includes three moderating factors: system configuration, hospital policy, and nurse's individual workflow. We further incorporated the HPM into the PrI phenotype development process to address phenotyping challenges. Moreover, we suggested a set of standardizable recommendations to address PrI phenotyping challenges.
医疗保健流程的复杂性给利用电子健康记录(EHR)数据构建高保真表型带来了重大挑战。本研究采用医疗保健流程建模(HPM)方法,以深入了解构建标准化压力性损伤(PrI)表型分析流程所需的基于EHR的PrI数据模式。通过临床专家、数据科学家、数据库分析师和信息学家之间的跨学科合作,采用包括探索性序列设计在内的混合方法,开发并验证了PrI HPM。定性分析确定了PrI护理与相关临床文档流程之间的动态关系。定量分析确定了PrI数据固有的挑战和局限性。PrI HPM包括三个调节因素:系统配置、医院政策和护士的个人工作流程。我们进一步将HPM纳入PrI表型开发过程,以应对表型分析挑战。此外,我们提出了一套标准化建议,以应对PrI表型分析挑战。