title: Differences in spirometry interpretation algorithms: influence on decision making among primary-care physicians.
abstract: BACKGROUND
  Spirometry is recommended for the diagnosis of asthma and chronic obstructive pulmonary disease (COPD) in international guidelines and may be useful for distinguishing asthma from COPD. Numerous spirometry interpretation algorithms (SIAs) are described in the literature, but no studies highlight how different SIAs may influence the interpretation of the same spirometric data.
  
  
  OBJECTIVE
  We examined how two different SIAs may influence decision making among primary-care physicians.
  
  
  METHODS
  Data for this initiative were gathered from 113 primary-care physicians attending accredited workshops in Canada between 2011 and 2013. Physicians were asked to interpret nine spirograms presented twice in random sequence using two different SIAs and touch pad technology for anonymous data recording.
  
  
  RESULTS
  We observed differences in the interpretation of spirograms using two different SIAs. When the pre-bronchodilator FEV1/FVC (forced expiratory volume in one second/forced vital capacity) ratio was >0.70, algorithm 1 led to a 'normal' interpretation (78% of physicians), whereas algorithm 2 prompted a bronchodilator challenge revealing changes in FEV1 that were consistent with asthma, an interpretation selected by 94% of physicians. When the FEV1/FVC ratio was <0.70 after bronchodilator challenge but FEV1 increased >12% and 200 ml, 76% suspected asthma and 10% suspected COPD using algorithm 1, whereas 74% suspected asthma versus COPD using algorithm 2 across five separate cases. The absence of a post-bronchodilator FEV1/FVC decision node in algorithm 1 did not permit consideration of possible COPD.
  
  
  CONCLUSIONS
  This study suggests that differences in SIAs may influence decision making and lead clinicians to interpret the same spirometry data differently.
authors.affiliation: Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
authors.forename: Xiao-Ou
authors.initials: XO
authors.lastname: He
authors.affiliation: 1] Faculty of Medicine, University of Toronto, Toronto, ON, Canada [2] Department of Family and Community Medicine at the University of Toronto, Toronto, ON, Canada.
authors.forename: Anthony
authors.initials: A
authors.lastname: D'Urzo
authors.affiliation: Department of Family and Community Medicine at the University of Toronto, Toronto, ON, Canada.
authors.forename: Pieter
authors.initials: P
authors.lastname: Jugovic
authors.affiliation: Department of Family and Community Medicine at the University of Toronto, Toronto, ON, Canada.
authors.forename: Reuven
authors.initials: R
authors.lastname: Jhirad
authors.affiliation: Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
authors.forename: Prateek
authors.initials: P
authors.lastname: Sehgal
authors.affiliation: Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
authors.forename: Evan
authors.initials: E
authors.lastname: Lilly
mesh_terms: D000465:Algorithms; D001249:Asthma / Q000175:diagnosis* / Q000503:physiopathology; D003657:Decision Making; D003937:Diagnosis, Differential; D005541:Forced Expiratory Volume; D006801:Humans; D058007:Physicians, Primary Care; D029424:Pulmonary Disease, Chronic Obstructive / Q000175:diagnosis* / Q000503:physiopathology; D013147:Spirometry; D014797:Vital Capacity