title: A Comprehensive View of Frequent Emergency Department Users Based on Data from a Regional HIE.
abstract: 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).
  
  
  
  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.
  
  
  
  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.
  
  
  
  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.
authors.affiliation: 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.
authors.forename: Steven Howard
authors.initials: SH
authors.lastname: Saef
authors.affiliation: 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.
authors.forename: Christine Marie
authors.initials: CM
authors.lastname: Carr
authors.affiliation: 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.
authors.forename: Jeffrey S
authors.initials: JS
authors.lastname: Bush
authors.affiliation: 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.
authors.forename: Marc T
authors.initials: MT
authors.lastname: Bartman
authors.affiliation: 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.
authors.forename: Adam B
authors.initials: AB
authors.lastname: Sendor
authors.affiliation: 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.
authors.forename: Wenle
authors.initials: W
authors.lastname: Zhao
authors.affiliation: 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.
authors.forename: Zemin
authors.initials: Z
authors.lastname: Su
authors.affiliation: 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.
authors.forename: Jingwen
authors.initials: J
authors.lastname: Zhang
authors.affiliation: 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.
authors.forename: Justin
authors.initials: J
authors.lastname: Marsden
authors.affiliation: 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.
authors.forename: J Christophe
authors.initials: JC
authors.lastname: Arnaud
authors.affiliation: 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.
authors.forename: Cathy L
authors.initials: CL
authors.lastname: Melvin
authors.affiliation: 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.
authors.forename: Leslie
authors.initials: L
authors.lastname: Lenert
authors.affiliation: 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.
authors.forename: William P
authors.initials: WP
authors.lastname: Moran
authors.affiliation: 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.
authors.forename: Patrick D
authors.initials: PD
authors.lastname: Mauldin
authors.affiliation: 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.
authors.forename: Jihad S
authors.initials: JS
authors.lastname: Obeid
mesh_terms: D000328:Adult; D000367:Age Factors; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005006:Ethnicity; D005260:Female; D066275:Health Information Exchange / Q000592:standards / Q000706:statistics & numerical data; D006801:Humans; D038801:International Classification of Diseases; D008297:Male; D000069342:Medical Overuse / Q000517:prevention & control*; D008498:Medical Record Linkage / Q000379:methods*; D001523:Mental Disorders / Q000453:epidemiology; D010355:Patient Identification Systems / Q000379:methods; D011247:Pregnancy; D011248:Pregnancy Complications / Q000453:epidemiology; D013022:South Carolina / Q000453:epidemiology