Carr Christine Marie, Saef Steven Howard, Zhang Jingwen, Su Zemin, Melvin Cathy L, Obeid Jihad S, Zhao Wenle, Arnaud J Christophe, Marsden Justin, Sendor Adam B, Lenert Leslie, Moran William P, Mauldin Patrick D
From the Departments of Medicine, Public Health Sciences, the Division of General Internal Medicine and Geriatrics, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.
South Med J. 2016 Jul;109(7):427-33. doi: 10.14423/SMJ.0000000000000490.
Health information exchanges (HIEs) make possible the construction of databases to characterize patients as multisystem users (MSUs), those visiting emergency departments (EDs) of more than one hospital system within a region during a 1-year period. HIE data can inform an algorithm highlighting patients for whom information is more likely to be present in the HIE, leading to a higher yield HIE experience for ED clinicians and incentivizing their adoption of HIE. Our objective was to describe patient characteristics that determine which ED patients are likely to be MSUs and therefore have information in an HIE, thereby improving the efficacy of HIE use and increasing ED clinician perception of HIE benefit.
Data were extracted from a regional HIE involving four hospital systems (11 EDs) in the Charleston, South Carolina area. We used univariate and multivariable regression analyses to develop a predictive model for MSU status.
Factors associated with MSUs included younger age groups, dual-payer insurance status, living in counties that are more rural, and one of at least six specific diagnoses: mental disorders; symptoms, signs, and ill-defined conditions; complications of pregnancy, childbirth, and puerperium; diseases of the musculoskeletal system; injury and poisoning; and diseases of the blood and blood-forming organs. For patients with multiple ED visits during 1 year, 43.8% of MSUs had ≥4 visits, compared with 18.0% of non-MSUs (P < 0.0001).
This predictive model accurately identified patients cared for at multiple hospital systems and can be used to increase the likelihood that time spent logging on to the HIE will be a value-added effort for emergency physicians.
健康信息交换（HIE）使构建数据库成为可能，这些数据库可将患者表征为多系统使用者（MSU），即在1年期间内就诊于某地区一个以上医院系统急诊科（ED）的患者。HIE数据可为一种算法提供信息，该算法能突出显示那些在HIE中更有可能存在相关信息的患者，从而为急诊科临床医生带来更高产出的HIE体验，并促使他们采用HIE。我们的目标是描述那些能确定哪些急诊科患者可能是MSU，进而在HIE中有相关信息的患者特征，从而提高HIE使用的有效性，并增强急诊科临床医生对HIE益处的认知。
数据取自南卡罗来纳州查尔斯顿地区涉及四个医院系统（11个急诊科）的区域HIE。我们使用单变量和多变量回归分析来建立MSU状态的预测模型。
与MSU相关的因素包括较年轻的年龄组、双重付费保险状态、居住在农村程度更高的县，以及至少六种特定诊断之一：精神障碍；症状、体征和未明确的病症；妊娠、分娩和产褥期并发症；肌肉骨骼系统疾病；损伤和中毒；以及血液和造血器官疾病。对于在1年内多次就诊于急诊科的患者，43.8%的MSU就诊次数≥4次，而非MSU的这一比例为18.0%（P<0.0001）。
该预测模型能准确识别在多个医院系统接受治疗的患者，可用于提高急诊科医生登录HIE所花费时间的增值可能性。
