title: Upgrading clinical decision support with published evidence: what can make the biggest difference?
abstract: BACKGROUND
  To enhance clinical decision support, presented messages are increasingly supplemented with information from the medical literature. The goal of this study was to identify types of evidence that can lead to the biggest difference.
  
  
  METHODS
  Seven versions of a questionnaire were mailed to randomly selected active family practice physicians and internists across the United States. They were asked about the perceived values of evidence from randomized controlled trials, locally developed recommendations, no evidence, cost-effectiveness studies, expert opinion, epidemiologic studies, and clinical studies. Analysis of variance and pairwise comparisons were used for statistical testing.
  
  
  RESULTS
  Seventy-six (52%) physicians responded. On a Likert scale from one to six, randomized controlled clinical trial was the highest rated evidence (mean 5.07, SD +/- 1.14). Such evidence was significantly superior to locally developed recommendations and no evidence at all (P < .05). The interaction was also strong between the types of evidence and clinical areas (P = .0001).
  
  
  CONCLUSIONS
  While most health care organizations present data without interpretation or simply try to enforce locally developed recommendations, such approaches appear to be inferior to techniques of reporting data with pertinent controlled evidence from the literature. Investigating physicians' perceptions is likely to benefit the design of computer generated messages.
authors.affiliation: Health Management and Informatics, School of Medicine, University of Missouri, Columbia, USA.
authors.forename: E A
authors.initials: EA
authors.lastname: Balas
authors.forename: K C
authors.initials: KC
authors.lastname: Su
authors.forename: J F
authors.initials: JF
authors.lastname: Solem
authors.forename: Z R
authors.initials: ZR
authors.lastname: Li
authors.forename: G
authors.initials: G
authors.lastname: Brown
mesh_terms: D000328:Adult; D000368:Aged; D000704:Analysis of Variance; D001291:Attitude of Health Personnel; D003625:Data Collection; D003661:Decision Support Techniques; D019317:Evidence-Based Medicine; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010820:Physicians / Q000523:psychology; D011320:Primary Health Care; D016032:Randomized Controlled Trials as Topic; D014481:United States