title: Potential value of health information exchange for people with epilepsy: crossover patterns and missing clinical data.
abstract: BACKGROUND
  For people with epilepsy, the potential value of health information exchange (HIE) is unknown.
  
  
  METHODS
  We reviewed two years of clinical encounters for 8055 people with epilepsy from seven Manhattan hospitals. We created network graphs illustrating crossover among these hospitals for multiple encounter types, and calculated a novel metric of care fragmentation: "encounters at risk for missing clinical data."
  
  
  RESULTS
  Given two hospitals, a median of 109 [range 46 - 588] patients with epilepsy had visited both. Due to this crossover, recent, relevant clinical data may be missing at the time of care frequently (44.8% of ED encounters, 34.5% inpatient, 24.9% outpatient, and 23.2% radiology). Though a smaller percentage of outpatient encounters were at risk for missing data than ED encounters, the absolute number of outpatient encounters at risk was three times higher (14,579 vs. 5041).
  
  
  CONCLUSIONS
  People with epilepsy may benefit from HIE. Future HIE initiatives should prioritize outpatient access.
authors.affiliation: Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, NY ; Department of Public Health, Weill Cornell Medical College, New York, NY ; Department of Pediatrics, Weill Cornell Medical College, New York, NY ; New York Presbyterian Hospital, New York, NY.
authors.forename: Zachary M
authors.initials: ZM
authors.lastname: Grinspan
authors.affiliation: Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, NY ; Department of Public Health, Weill Cornell Medical College, New York, NY ; Department of Pediatrics, Weill Cornell Medical College, New York, NY ; New York Presbyterian Hospital, New York, NY ; Health Information Technology Evaluation Collaborative, New York, NY.
authors.forename: Erika L
authors.initials: EL
authors.lastname: Abramson
authors.affiliation: Department of Public Health, Weill Cornell Medical College, New York, NY ; Department of Statistical Science, Cornell University, Ithaca, NY.
authors.forename: Samprit
authors.initials: S
authors.lastname: Banerjee
authors.affiliation: Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, NY ; Department of Public Health, Weill Cornell Medical College, New York, NY ; New York Presbyterian Hospital, New York, NY ; Health Information Technology Evaluation Collaborative, New York, NY ; Department of Medicine, Weill Cornell Medical College, New York, NY.
authors.forename: Lisa M
authors.initials: LM
authors.lastname: Kern
authors.affiliation: Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, NY ; Department of Public Health, Weill Cornell Medical College, New York, NY ; Department of Pediatrics, Weill Cornell Medical College, New York, NY ; New York Presbyterian Hospital, New York, NY ; Health Information Technology Evaluation Collaborative, New York, NY ; Department of Medicine, Weill Cornell Medical College, New York, NY.
authors.forename: Rainu
authors.initials: R
authors.lastname: Kaushal
authors.affiliation: Department of Emergency Medicine, Mount Sinai Medical Center, New York, NY.
authors.forename: Jason S
authors.initials: JS
authors.lastname: Shapiro
mesh_terms: D003266:Continuity of Patient Care / Q000458:organization & administration*; D057286:Electronic Health Records; D004827:Epilepsy; D063025:Health Information Management; D006751:Hospital Information Systems / Q000458:organization & administration*; D006801:Humans; D033181:Information Dissemination; D008498:Medical Record Linkage; D016347:Medical Records Systems, Computerized / Q000458:organization & administration*; D009519:New York City