title: Making electronic prescribing alerts more effective: scenario-based experimental study in junior doctors.
abstract: OBJECTIVE
  Expert authorities recommend clinical decision support systems to reduce prescribing error rates, yet large numbers of insignificant on-screen alerts presented in modal dialog boxes persistently interrupt clinicians, limiting the effectiveness of these systems. This study compared the impact of modal and non-modal electronic (e-) prescribing alerts on prescribing error rates, to help inform the design of clinical decision support systems.
  
  
  METHODS
  A randomized study of 24 junior doctors each performing 30 simulated prescribing tasks in random order with a prototype e-prescribing system. Using a within-participant design, doctors were randomized to be shown one of three types of e-prescribing alert (modal, non-modal, no alert) during each prescribing task.
  
  
  METHODS
  The main outcome measure was prescribing error rate. Structured interviews were performed to elicit participants' preferences for the prescribing alerts and their views on clinical decision support systems.
  
  
  RESULTS
  Participants exposed to modal alerts were 11.6 times less likely to make a prescribing error than those not shown an alert (OR 11.56, 95% CI 6.00 to 22.26). Those shown a non-modal alert were 3.2 times less likely to make a prescribing error (OR 3.18, 95% CI 1.91 to 5.30) than those not shown an alert. The error rate with non-modal alerts was 3.6 times higher than with modal alerts (95% CI 1.88 to 7.04).
  
  
  CONCLUSIONS
  Both kinds of e-prescribing alerts significantly reduced prescribing error rates, but modal alerts were over three times more effective than non-modal alerts. This study provides new evidence about the relative effects of modal and non-modal alerts on prescribing outcomes.
authors.affiliation: Department of Health Informatics Directorate, Leeds, West Yorkshire, UK. gregory.scott99@imperial.ac.uk
authors.forename: Gregory P T
authors.initials: GP
authors.lastname: Scott
authors.forename: Priya
authors.initials: P
authors.lastname: Shah
authors.forename: Jeremy C
authors.initials: JC
authors.lastname: Wyatt
authors.forename: Boikanyo
authors.initials: B
authors.lastname: Makubate
authors.forename: Frank W
authors.initials: FW
authors.lastname: Cross
mesh_terms: D020000:Decision Support Systems, Clinical; D055695:Electronic Prescribing; D006801:Humans; D050316:Medical Order Entry Systems; D008505:Medical Staff, Hospital; D008508:Medication Errors / Q000517:prevention & control* / Q000706:statistics & numerical data; D017010:Reminder Systems