title: People with epilepsy who use multiple hospitals; prevalence and associated factors assessed via a health information exchange.
abstract: OBJECTIVE
  Hospital crossover occurs when people seek care at multiple hospitals, creating information gaps for physicians at the time of care. Health information exchange (HIE) is technology that fills these gaps, by allowing otherwise unaffiliated physicians to share electronic medical information. However, the potential value of HIE is understudied, particularly for chronic neurologic conditions like epilepsy. We describe the prevalence and associated factors of hospital crossover among people with epilepsy, in order to understand the epidemiology of who may benefit from HIE.
  
  
  METHODS
  We used a cross-sectional study design to examine the bivariate and multivariable association of demographics, comorbidity, and health service utilization variables with hospital crossover, among people with epilepsy. We identified 8,074 people with epilepsy from the International Classification of Diseases, Ninth Revision (ICD-9) codes, obtained from an HIE that linked seven hospitals in Manhattan, New York. We defined hospital crossover as care from more than one hospital in any setting (inpatient, outpatient, emergency, or radiology) over 2 years.
  
  
  RESULTS
  Of 8,074 people with epilepsy, 1,770 (22%) engaged in hospital crossover over 2 years. Crossover was associated with younger age (children compared with adults, adjusted odds ratio [OR] 1.4, 95% confidence interval [CI] 1.2-1.7), living near the hospitals (Manhattan vs. other boroughs of New York City, adjusted OR 1.6, 95% CI 1.4-1.8), more visits in the emergency, radiology, inpatient, and outpatient settings (p < 0.001 for each), and more head computerized tomography (CT) scans (p < 0.01). The diagnosis of "encephalopathy" was consistently associated with crossover in bivariate and multivariable analyses (adjusted OR 2.66, 95% CI 2.14-3.29), whereas the relationship between other comorbidities and crossover was less clear.
  
  
  CONCLUSIONS
  Hospital crossover is common among people with epilepsy, particularly among children, frequent users of medical services, and people living near the study hospitals. HIE should focus on these populations. Further research should investigate why hospital crossover occurs, how it affects care, and how HIE can most effectively mitigate the resultant fragmentation of medical records.
authors.affiliation: Department of Pediatrics, Weill Cornell Medical College, New York, New York, U.S.A.|Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, New York, U.S.A.|New York Presbyterian Hospital, New York, New York, U.S.A.
authors.forename: Zachary M
authors.initials: ZM
authors.lastname: Grinspan
authors.affiliation: Department of Pediatrics, Weill Cornell Medical College, New York, New York, U.S.A.|Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, New York, U.S.A.|New York Presbyterian Hospital, New York, New York, U.S.A.|Department of Public Health, Weill Cornell Medical College, New York, New York, U.S.A.|Health Information Technology Evaluation Collaborative, New York, New York, U.S.A.
authors.forename: Erika L
authors.initials: EL
authors.lastname: Abramson
authors.affiliation: Department of Public Health, Weill Cornell Medical College, New York, New York, U.S.A.|Department of Statistical Science, Cornell University, Ithaca, New York, U.S.A.
authors.forename: Samprit
authors.initials: S
authors.lastname: Banerjee
authors.affiliation: Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, New York, U.S.A.|New York Presbyterian Hospital, New York, New York, U.S.A.|Department of Public Health, Weill Cornell Medical College, New York, New York, U.S.A.|Health Information Technology Evaluation Collaborative, New York, New York, U.S.A.|Department of Medicine, Weill Cornell Medical College, New York, New York, U.S.A.
authors.forename: Lisa M
authors.initials: LM
authors.lastname: Kern
authors.affiliation: Department of Pediatrics, Weill Cornell Medical College, New York, New York, U.S.A.|Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, New York, U.S.A.|New York Presbyterian Hospital, New York, New York, U.S.A.|Department of Public Health, Weill Cornell Medical College, New York, New York, U.S.A.|Health Information Technology Evaluation Collaborative, New York, New York, U.S.A.|Department of Medicine, Weill Cornell Medical College, New York, New York, U.S.A.
authors.forename: Rainu
authors.initials: R
authors.lastname: Kaushal
authors.affiliation: Department of Emergency Medicine, Mount Sinai School of Medicine, New York, New York, U.S.A.
authors.forename: Jason S
authors.initials: JS
authors.lastname: Shapiro
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D015897:Comorbidity; D003266:Continuity of Patient Care / Q000458:organization & administration / Q000706:statistics & numerical data*; D003430:Cross-Sectional Studies; D057286:Electronic Health Records / Q000458:organization & administration / Q000706:statistics & numerical data*; D004827:Epilepsy / Q000453:epidemiology* / Q000628:therapy; D005260:Female; D063025:Health Information Management / Q000458:organization & administration / Q000706:statistics & numerical data*; D006751:Hospital Information Systems / Q000458:organization & administration / Q000706:statistics & numerical data*; D006786:Hospitals, Urban / Q000458:organization & administration / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D008297:Male; D008498:Medical Record Linkage; D008875:Middle Aged; D009519:New York City; D012017:Referral and Consultation / Q000706:statistics & numerical data; D014600:Utilization Review / Q000706:statistics & numerical data; D055815:Young Adult
keywords: Epidemiology; Epilepsy; Health information exchange; Health information technology; Health services research