title: Factors influencing unspecified chest pain admission rates in England.
abstract: BACKGROUND
  Unspecified chest pain is an important and potentially avoidable cause of emergency hospital admission. We aimed to examine inter-hospital variation in admission rates with unspecified chest pain and identify population characteristics, services and technologies that might explain this variation.
  
  
  METHODS
  We used Hospital Episodes Statistics data from 152 acute trusts in England to calculate a direct standardised annual admission rate per 100,000 population for each trust. Regression analysis was used to identify factors explaining variation, first, using routinely available data relating to the hospital catchment area and service and then using responses to a survey of emergency department (ED) management.
  
  
  RESULTS
  The best predictors of admission rate using routine data were total beds per 1000 population (p=0.001), rapid access chest pain clinic (RACPC) attendances per year (p<0.001) and percentage of households in poverty (p=0.01). Including data from 105/142 (74%) survey responses, the best predictors of admission rate were total beds (p<0.001), RACPC attendances (p=0.001), mean ED waiting time (p=0.049) and percentage of households in poverty (p<0.001). All associations were positive (higher variable predicts higher rate) except ED waiting time. We found no significant associations between factors relating to acute chest pain management and admission rate.
  
  
  CONCLUSIONS
  Hospitals with higher admission rates for unspecified chest pain have greater bed provision, more RACPC attendances and serve populations with a higher percentage of households in poverty. These findings may be explained by services responding to demand in populations with greater need. We found no evidence that chest pain management influenced admission rates.
authors.affiliation: School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK.
authors.forename: Tom
authors.initials: T
authors.lastname: Bidmead
authors.affiliation: School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK.
authors.forename: Steve
authors.initials: S
authors.lastname: Goodacre
authors.affiliation: School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK.
authors.forename: Ravi
authors.initials: R
authors.lastname: Maheswaran
authors.affiliation: School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK.
authors.forename: Alicia
authors.initials: A
authors.lastname: O'Cathain
mesh_terms: D000328:Adult; D001509:Bed Occupancy; D002637:Chest Pain; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D004739:England; D005260:Female; D006742:Hospital Bed Capacity; D006801:Humans; D007902:Length of Stay; D008297:Male; D010343:Patient Admission / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors
keywords: admission avoidance; comparitive system research; emergency care systems, admission avoidance; hospitalisations