title: Emergency Department Attendance after Telephone Triage: A Population-Based Data Linkage Study.
abstract: To investigate compliance with telephone helpline advice to attend an emergency department (ED) and the acuity of patients who presented to ED following a call.
  
  
  
  In New South Wales (NSW), Australia, 2009-2012, all (1.04 million) calls to a telephone triage service, ED presentations, hospital admissions and death registrations, linked using probabilistic data linkage.
  
  
  
  Population-based, observational cohort study measuring ED presentations within 24 hours of a call in patients (1) with dispositions to attend ED (compliance) and (2) low-urgency dispositions (self-referral), triage categories on ED presentation.
  
  
  
  A total of 66.5 percent of patients were compliant with dispositions to attend an ED. A total of 6.2 percent of patients with low-urgency dispositions self-referred to the ED within 24 hours. After age adjustment, healthdirect compliant patients were significantly less likely (7.8 percent) to receive the least urgent ED triage category compared to the general NSW ED population (16.9 percent).
  
  
  
  This large population-based data linkage study provides precise estimates of ED attendance following calls to a telephone triage service and details the predictors of ED attendance. Patients who attend an ED compliant with a healthdirect helpline disposition are significantly less likely than the general ED population to receive the lowest urgency triage category on arrival.
authors.affiliation: Centre for Big Data Research in Health, UNSW, Sydney, NSW, Australia.
authors.forename: Amy
authors.initials: A
authors.lastname: Gibson
authors.affiliation: Centre for Big Data Research in Health, UNSW, Sydney, NSW, Australia.
authors.forename: Deborah
authors.initials: D
authors.lastname: Randall
authors.affiliation: Centre for Big Data Research in Health, UNSW, Sydney, NSW, Australia.
authors.forename: Duong T
authors.initials: DT
authors.lastname: Tran
authors.affiliation: Healthdirect Australia, Sydney, NSW, Australia.
authors.forename: Mary
authors.initials: M
authors.lastname: Byrne
authors.affiliation: Department of Health and Human Services, University of Tasmania and Healthdirect Australia, Hobart, Tasmania, Australia.
authors.forename: Anthony
authors.initials: A
authors.lastname: Lawler
authors.affiliation: Centre for Big Data Research in Health, UNSW, Sydney, NSW, Australia.
authors.forename: Alys
authors.initials: A
authors.lastname: Havard
authors.affiliation: Healthdirect Australia, Clinical Governance, Sydney, NSW, Australia.
authors.forename: Maureen
authors.initials: M
authors.lastname: Robinson
authors.affiliation: Centre for Big Data Research in Health, UNSW, Sydney, NSW, Australia.
authors.forename: Louisa R
authors.initials: LR
authors.lastname: Jorm
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D009517:New South Wales; D010349:Patient Compliance / Q000706:statistics & numerical data*; D012017:Referral and Consultation / Q000706:statistics & numerical data*; D013689:Telephone; D013997:Time Factors; D014218:Triage / Q000379:methods* / Q000706:statistics & numerical data; D055815:Young Adult
keywords: Administrative data uses; epidemiology; hospitals; referrals, referral networks