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基于区域卫生信息交换(HIE)数据对急诊科频繁使用者的综合观察

A Comprehensive View of Frequent Emergency Department Users Based on Data from a Regional HIE.

作者信息

Saef Steven Howard, Carr Christine Marie, Bush Jeffrey S, Bartman Marc T, Sendor Adam B, Zhao Wenle, Su Zemin, Zhang Jingwen, Marsden Justin, Arnaud J Christophe, Melvin Cathy L, Lenert Leslie, Moran William P, Mauldin Patrick D, Obeid Jihad S

机构信息

From the Divisions of Emergency Medicine and General Internal Medicine and Geriatrics, the Department of Public Health Sciences, the South Carolina Clinical and Translational Research Institute, and the Center for Biomedical Informatics, Medical University of South Carolina, Charleston.

出版信息

South Med J. 2016 Jul;109(7):434-9. doi: 10.14423/SMJ.0000000000000488.

Abstract

OBJECTIVES

A small but significant number of patients make frequent emergency department (ED) visits to multiple EDs within a region. We have a unique health information exchange (HIE) that includes every ED encounter in all hospital systems in our region. Using our HIE we were able to characterize all frequent ED users in our region, regardless of hospital visited or payer class. The objective of our study was to use data from an HIE to characterize patients in a region who are frequent ED users (FEDUs).

METHODS

We constructed a database from a cohort of adult patients (18 years old or older) with information in a regional HIE for a 1-year period beginning in April 2012. Patients were defined as FEDUs (those who made four or more visits during the study period) and non-FEDUs (those who made fewer than four ED visits during the study period). Predictor variables included age, race, sex, payer class, county of residence, and International Classification of Diseases, Ninth Revision codes. Bivariate (χ(2)) and multivariate (logistic regression) analyses were performed to determine associations between predictor variables and the outcome of being a FEDU.

RESULTS

The database contained 127,672 patients, 12,293 (9.6%) of whom were FEDUs. Logistic regression showed the following patient characteristics to be significantly associated with the outcome of being a FEDU: age 35 to 44 years; African American race; Medicaid, Medicare, and dual-pay payer class; and International Classification of Diseases, Ninth Revision codes 630 to 679 (complications of pregnancy, childbirth, and puerperium), 780 to 799 (ill-defined conditions), 280 to 289 (diseases of the blood), 290-319 (mental disorders), 680 to 709 (diseases of the skin and subcutaneous tissue), 710 to 739 (musculoskeletal and connective tissue disease), 460 to 519 (respiratory disease), and 520 to 579 (digestive disease). No significant differences were noted between men and women.

CONCLUSIONS

Data from an HIE can be used to describe all of the patients within a region who are FEDUs, regardless of the hospital system they visited. This information can be used to focus care coordination efforts and link appropriate patients to a medical home. Future studies can be designed to learn the reasons why patients become FEDUs, and interventions can be developed to address deficiencies in health care that result in frequent ED visits.

摘要

目的

在一个地区内,有一小部分但数量可观的患者频繁前往多个急诊科就诊。我们拥有一个独特的健康信息交换系统(HIE),涵盖了本地区所有医院系统的每一次急诊科就诊情况。利用我们的HIE,我们能够对本地区所有频繁就诊的急诊科患者进行特征描述,无论他们就诊的医院或支付方类别如何。我们研究的目的是利用HIE中的数据来描述本地区频繁就诊的急诊科患者(FEDU)的特征。

方法

我们从2012年4月开始的为期1年的区域HIE中,构建了一个包含成年患者(18岁及以上)信息的数据库。患者被分为频繁就诊的急诊科患者(FEDU,即研究期间就诊4次或更多次的患者)和非频繁就诊的急诊科患者(即研究期间急诊科就诊次数少于4次的患者)。预测变量包括年龄、种族、性别、支付方类别、居住县以及国际疾病分类第九版编码。进行了双变量(χ²)和多变量(逻辑回归)分析,以确定预测变量与成为FEDU这一结果之间的关联。

结果

该数据库包含127,672名患者,其中12,293名(9.6%)为FEDU。逻辑回归显示,以下患者特征与成为FEDU的结果显著相关:年龄35至44岁;非裔美国人种族;医疗补助、医疗保险和双重支付方类别;以及国际疾病分类第九版编码630至679(妊娠、分娩和产褥期并发症)、780至799(未明确的病症)、280至289(血液疾病)、290 - 319(精神障碍)、680至709(皮肤和皮下组织疾病)、710至739(肌肉骨骼和结缔组织疾病)、460至519(呼吸系统疾病)以及520至579(消化系统疾病)。男性和女性之间未发现显著差异。

结论

HIE中的数据可用于描述一个地区内所有FEDU患者,无论他们就诊的医院系统如何。这些信息可用于集中医疗协调工作,并将合适的患者与医疗之家联系起来。未来的研究可以设计用于了解患者成为FEDU的原因,并开发干预措施来解决导致频繁急诊科就诊的医疗保健不足问题。

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