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一种从临床数据存储库获取、规范化和管理电子健康记录(EHR)数据以研究压疮结果的方法。

An Approach to Acquiring, Normalizing, and Managing EHR Data From a Clinical Data Repository for Studying Pressure Ulcer Outcomes.

作者信息

Padula William V, Blackshaw Leon, Brindle C Tod, Volchenboum Samuel L

机构信息

William V. Padula, PhD, MS, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland. Leon Blackshaw, Masters of Science in Analytics Program, Graham School, University of Chicago, Chicago, Illinois. C. Tod Brindle, RN, MSN, CWOCN, Wound and Ostomy Consultant Nurse, Virginia Commonwealth University Health System, Richmond, Virginia. Samuel L. Volchenboum, MD, PhD, MS, Assistant Professor of Pediatrics and Director of Informatics, University of Chicago Medicine, Chicago, Illinois.

出版信息

J Wound Ostomy Continence Nurs. 2016 Jan-Feb;43(1):39-45. doi: 10.1097/WON.0000000000000185.

Abstract

Changes in the methods that individual facilities follow to collect and store data related to hospital-acquired pressure ulcer (HAPU) occurrences are essential for improving patient outcomes and advancing our understanding the science behind this clinically relevant issue. Using an established electronic health record system at a large, urban, tertiary-care academic medical center, we investigated the process required for taking raw data of HAPU outcomes and submitting these data to a normalization process. We extracted data from 1.5 million patient shifts and filtered observations to those with a Braden score and linked tables in the electronic health record, including (1) Braden scale scores, (2) laboratory outcomes data, (3) surgical time, (4) provider orders, (5) medications, and (6) discharge diagnoses. Braden scores are important measures specific to HAPUs since these scores clarify the daily risk of a hospitalized patient for developing a pressure ulcer. The other more common measures that may be associated with HAPU outcomes are important to organize in a single data frame with Braden scores according to each patient. Primary keys were assigned to each table, and the data were processed through 3 normalization steps and 1 denormalization step. These processes created 8 tables that can be stored efficiently in a clinical database of HAPU outcomes. As hospitals focus on organizing data for review of HAPUs and other types of hospital-acquired conditions, the normalization process we describe in this article offers directions for collaboration between providers and informatics teams using a common language and structure.

摘要

各个医疗机构收集和存储与医院获得性压疮(HAPU)发生情况相关数据的方法变化,对于改善患者预后以及深化我们对这一临床相关问题背后科学的理解至关重要。我们利用一家大型城市三级医疗学术医学中心现有的电子健康记录系统,研究了获取HAPU结果原始数据并将这些数据提交至规范化流程所需的过程。我们从150万个患者轮班中提取数据,并将观察结果筛选至具有Braden评分以及电子健康记录中相关联表格的那些数据,这些表格包括:(1)Braden量表评分;(2)实验室检查结果数据;(3)手术时间;(4)医嘱;(5)用药情况;以及(6)出院诊断。Braden评分是HAPU特有的重要指标,因为这些评分明确了住院患者发生压疮的每日风险。其他可能与HAPU结果相关的更常见指标,按照每位患者与Braden评分一起整理在单个数据框架中也很重要。为每个表格分配主键,并对数据进行3步规范化和1步反规范化处理。这些过程创建了8个表格,可有效存储在HAPU结果的临床数据库中。随着医院专注于整理数据以审查HAPU及其他类型的医院获得性病症,我们在本文中描述的规范化流程为医疗服务提供者和信息学团队之间使用共同语言和结构进行协作提供了指导方向。

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