title: Understanding physician adherence with a pneumonia practice guideline: effects of patient, system, and physician factors.
abstract: BACKGROUND
  Adherence with clinical practice guidelines is highly variable. Reasons for their inconsistent performance have not been well studied.
  
  
  OBJECTIVE
  To determine the patient, system, and physician factors that may explain why physicians may not follow guidelines.
  
  
  METHODS
  We used chart review and physician surveys to measure adherence with an actively implemented guideline to reduce hospitalizations for patients coming to the emergency department with community-acquired pneumonia. Logistic regression analyses were used to identify factors associated with guideline nonadherence.
  
  
  RESULTS
  Overall nonadherence with the guideline was 43.6%, with 71 of 163 low-risk patients with pneumonia being hospitalized despite the recommendation for outpatient therapy. In univariate analyses, nonadherence to the guideline was more likely for patients who were aged 65 years or older, were male, were employed, and had multilobar disease or other comorbid conditions (P<.05). Active involvement of a primary care physician in the admission decision also increased nonadherence (odds ratio, 4.9; 95% confidence interval, 2.2-11.0). Physicians with more pneumonia experience were more likely not to follow the guideline (P<.001). In multivariate models, the odds of nonadherence were 2 to 3 times greater when patients were 65 years or older, were male, or had multilobar disease, or the primary care physician was involved in the triage decision (P<.05). Physicians' reasons for admission were the presence of active comorbidities (55%), the primary care physician's wish for hospitalization (41%), the presence of worse pneumonia than the guideline indicated (36%), patient preference (17%), and inadequate home support (16%).
  
  
  CONCLUSIONS
  Nonadherence to a pneumonia guideline was associated with a variety of patient, system, and physician factors. Guideline implementation strategies should take into account the heterogeneous forces that can influence physician decision making.
authors.affiliation: Department of Health Policy, Mount Sinai Medical Center, New York, NY 10029, USA. ethan.halm@mountsinai.org
authors.forename: E A
authors.initials: EA
authors.lastname: Halm
authors.forename: S J
authors.initials: SJ
authors.lastname: Atlas
authors.forename: L H
authors.initials: LH
authors.lastname: Borowsky
authors.forename: T I
authors.initials: TI
authors.lastname: Benzer
authors.forename: J P
authors.initials: JP
authors.lastname: Metlay
authors.forename: Y C
authors.initials: YC
authors.lastname: Chang
authors.forename: D E
authors.initials: DE
authors.lastname: Singer
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D017714:Community-Acquired Infections / Q000628:therapy; D004636:Emergency Service, Hospital / Q000592:standards*; D005260:Female; D019983:Guideline Adherence / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D008297:Male; D008499:Medical Records; D009518:New York; D010343:Patient Admission / Q000706:statistics & numerical data*; D011014:Pneumonia / Q000628:therapy*; D010818:Practice Patterns, Physicians' / Q000592:standards / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D012306:Risk; D012307:Risk Factors; D011795:Surveys and Questionnaires