title: Referral patterns after a seizure admission in an English region: an opportunity for effective intervention? An observational study of routine hospital data.
abstract: OBJECTIVE
  To identify emergency seizure admissions to hospital and their subsequent access to specialist outpatient services.
  
  
  METHODS
  Algorithmic analysis of anonymised routine hospital data over 7 years using specialist follow-up by 3 months as the target outcome.
  
  
  METHODS
  All adults resident in Merseyside and Cheshire, England.
  
  
  RESULTS
  Whether, and when, access to the specialist advice that might prevent further admissions was offered.
  
  
  RESULTS
  1.4% of all emergency medical admissions are as a result of seizure. In the following 12 months 35% were readmitted and experienced a mean of 2.3 emergency department visits. Only 27% (48% of those already known to specialists and 13% of those not known) were offered appointments. Subsequent attendance at a specialist clinic is more likely if already known to a clinic, if aged <35 years, if female, or required a longer spell in hospital. Extrapolation from other work suggests 100,000 bed days per annum could be saved.
  
  
  CONCLUSIONS
  Most seizure admissions are not being referred for the help that could prevent future admissions. The majority of those that are referred are not seen within an appropriate time frame. Our service structures are not providing an optimum service for people with epilepsy.
authors.affiliation: Department of Data Management, Northwest CSU, Liverpool, UK Department of Bio-informatics, University of Liverpool, Liverpool, UK.
authors.forename: Ruth
authors.initials: R
authors.lastname: Grainger
authors.affiliation: Department of Bio-informatics, University of Liverpool, Liverpool, UK.
authors.forename: Michael
authors.initials: M
authors.lastname: Pearson
authors.affiliation: Department of Bio-informatics, University of Liverpool, Liverpool, UK.
authors.forename: Peter
authors.initials: P
authors.lastname: Dixon
authors.affiliation: Department of Bio-informatics, University of Liverpool, Liverpool, UK.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Devonport
authors.affiliation: Liverpool CCG, Liverpool, UK.
authors.forename: Michelle
authors.initials: M
authors.lastname: Timoney
authors.affiliation: Department of Gastroenterology, University of Liverpool, Liverpool, UK Aintree University, Hospital NHS Trust, Digestive Diseases Centre, Liverpool, UK.
authors.forename: Keith
authors.initials: K
authors.lastname: Bodger
authors.affiliation: Department of Medical Statistics, University of Liverpool, Liverpool, UK.
authors.forename: Jamie
authors.initials: J
authors.lastname: Kirkham
authors.affiliation: Department of Bio-informatics, University of Liverpool, Liverpool, UK.
authors.forename: Anthony
authors.initials: A
authors.lastname: Marson
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000553:Ambulatory Care / Q000706:statistics & numerical data; D015331:Cohort Studies; D003695:Delivery of Health Care / Q000592:standards; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D004739:England; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008134:Long-Term Care / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D012017:Referral and Consultation / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012640:Seizures / Q000628:therapy*; D055815:Young Adult
keywords: Statistics and research methods