title: Predictors of on-call specialist response times in California emergency departments.
abstract: OBJECTIVE
  To assess waiting times in emergency departments (EDs) for on-call specialist response and how these might vary by facility or neighborhood characteristics. Limited availability of on-call specialists is thought to contribute to ED overcrowding.
  
  
  METHODS
  Direct observational data from a random sample of 1,798 patients visiting 30 California EDs during a six-month period provided specialist waiting times. The authors used multivariate logistic regression and survival analysis to analyze predictors of time to on-call specialists' telephone response.
  
  
  RESULTS
  Eighty-six percent of on-call specialists who were paged responded by telephone within 30 minutes. Ten percent of specialists did not respond at all. After controlling for the annual percentage of nonurgent ED patients at each facility, near closure status, and hospital ownership status, for every 10,000 dollars increase in hospital zip code income, the odds of on-call specialist response within 30 minutes increased by 123% (adjusted odds ratio = 2.23; 95% confidence interval = 1.24 to 4.02; p = 0.01).
  
  
  CONCLUSIONS
  Although the majority of on-call specialists met the federal recommendation of a 30-minute response, those in poor neighborhoods were less likely to do so. One in ten on-call specialists did not respond at all. State and federal policies should focus on making more funding available for on-call specialist panels in poor areas.
authors.affiliation: Department of Medicine and Emergency Medicine, Keck School of Medicine, University of Southern California 90033, USA. samohant@usc.edu
authors.forename: Sarita A
authors.initials: SA
authors.lastname: Mohanty
authors.forename: Donna L
authors.initials: DL
authors.lastname: Washington
authors.forename: Susan
authors.initials: S
authors.lastname: Lambe
authors.forename: Arlene
authors.initials: A
authors.lastname: Fink
authors.forename: Steven M
authors.initials: SM
authors.lastname: Asch
mesh_terms: D002140:California; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D019538:Health Care Surveys; D016304:Hospitals, Private / Q000706:statistics & numerical data; D006779:Hospitals, Public / Q000706:statistics & numerical data; D006784:Hospitals, Teaching / Q000706:statistics & numerical data; D006786:Hospitals, Urban / Q000706:statistics & numerical data; D006801:Humans; D007348:Insurance, Health / Q000706:statistics & numerical data; D016015:Logistic Models; D008511:Medicine / Q000706:statistics & numerical data*; D015233:Models, Statistical; D015999:Multivariate Analysis; D017063:Outcome Assessment, Health Care; D012959:Socioeconomic Factors; D013038:Specialization; D016019:Survival Analysis; D013689:Telephone / Q000706:statistics & numerical data; D013995:Time; D014193:Trauma Centers / Q000706:statistics & numerical data; D014850:Waiting Lists