title: Characteristics of general practices associated with numbers of elective admissions.
abstract: BACKGROUND
  In England both emergency (unplanned) and non-emergency (elective) hospital admissions have been increasing. Some elective admissions are potentially avoidable.
  
  
  OBJECTIVE
  to identify the characteristics of general practices and patients associated with elective admissions.
  
  
  METHODS
  A cross-sectional study, in Leicestershire, England, was conducted using admission data (2006-07 and 2007-08). Practice characteristics (list size, distance from principal hospital, quality and outcomes framework score and general practitioner (GP) patient access survey data) and patient characteristics (age, ethnicity and deprivation and gender) were used as predictors of elective hospital admissions in a negative binomial regression model.
  
  
  RESULTS
  Practices with a higher proportion of patients aged 65 years or greater and of white ethnicity had higher rates of elective hospital admissions. Practices with more male patients and with more patients reporting being able to consult a particular GP had fewer elective hospital admissions. For 2007-08 practices with a larger list size were associated with higher elective hospital admissions. Quality and outcomes framework performance did not predict admission numbers.
  
  
  CONCLUSIONS
  As for unplanned admissions, elective admissions increase as being able to consult a particular GP declines. Interventions to improve continuity should be investigated. Practices face major problems in managing the increased need for planned care as the population ages.
authors.affiliation: Department of Health Sciences,  University of Leicester, Leicester,  UK.
authors.forename: Mitum
authors.initials: M
authors.lastname: Chauhan
authors.forename: M John
authors.initials: MJ
authors.lastname: Bankart
authors.forename: Alexander
authors.initials: A
authors.lastname: Labeit
authors.forename: Richard
authors.initials: R
authors.lastname: Baker
mesh_terms: D017677:Age Distribution; D000368:Aged; D003430:Cross-Sectional Studies; D004739:England / Q000453:epidemiology; D005006:Ethnicity / Q000706:statistics & numerical data; D005260:Female; D058006:General Practice / Q000191:economics / Q000592:standards / Q000706:statistics & numerical data*; D006297:Health Services Accessibility / Q000191:economics / Q000592:standards / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D010343:Patient Admission / Q000191:economics / Q000706:statistics & numerical data* / Q000639:trends; D017060:Patient Satisfaction / Q000706:statistics & numerical data; D010818:Practice Patterns, Physicians' / Q000191:economics / Q000592:standards / Q000706:statistics & numerical data*; D012017:Referral and Consultation / Q000191:economics / Q000706:statistics & numerical data / Q000639:trends; D012044:Regression Analysis; D017678:Sex Distribution; D012959:Socioeconomic Factors; D044465:White People / Q000706:statistics & numerical data