title: Effect of EHR user interface changes on internal prescription discrepancies.
abstract: OBJECTIVE
  To determine whether specific design interventions (changes in the user interface (UI)) of an electronic health record (EHR) medication module are associated with an increase or decrease in the incidence of contradictions between the structured and narrative components of electronic prescriptions (internal prescription discrepancies).
  
  
  METHODS
  We performed a retrospective analysis of 960,000 randomly selected electronic prescriptions generated in a single EHR between 01/2004 and 12/2011. Internal prescription discrepancies were identified using a validated natural language processing tool with recall of 76% and precision of 84%. A multivariable autoregressive integrated moving average (ARIMA) model was used to evaluate the effect of five UI changes in the EHR medication module on incidence of internal prescription discrepancies.
  
  
  RESULTS
  Over the study period 175,725 (18.4%) prescriptions were found to have internal discrepancies. The highest rate of prescription discrepancies was observed in March 2006 (22.5%) and the lowest in March 2009 (15.0%). Addition of "as directed" option to the <Frequency> dropdown decreased prescription discrepancies by 195 / month (p = 0.0004). An non-interruptive alert that reminded providers to ensure that structured and narrative components did not contradict each other decreased prescription discrepancies by 145 / month (p = 0.03). Addition of a "Renew / Sign" button to the Medication module (a negative control) did not have an effect in prescription discrepancies.
  
  
  CONCLUSIONS
  Several UI changes in the electronic medication module were effective in reducing the incidence of internal prescription discrepancies. Further research is needed to identify interventions that can completely eliminate this type of prescription error and their effects on patient outcomes.
authors.affiliation: Harvard Clinical Research Institute , Boston, MA ; Division of Endocrinology, Brigham and Women's Hospital , Boston, MA ; Harvard Medical School , Boston, MA.
authors.forename: A
authors.initials: A
authors.lastname: Turchin
authors.affiliation: Harvard Medical School , Boston, MA ; Division of General Internal Medicine, Brigham and Women's Hospital , Boston, MA.
authors.forename: A
authors.initials: A
authors.lastname: Sawarkar
authors.affiliation: Department of Mathematics, Emmanuel College , Boston, MA.
authors.forename: Y A
authors.initials: YA
authors.lastname: Dementieva
authors.affiliation: BE-Tech, Inc. , Brooklyn, NY ; Division of General Internal Medicine, Brigham and Women's Hospital , Boston, MA.
authors.forename: E
authors.initials: E
authors.lastname: Breydo
authors.affiliation: Harvard Medical School , Boston, MA ; Information Systems, Partners HealthCare , Boston, MA.
authors.forename: H
authors.initials: H
authors.lastname: Ramelson
mesh_terms: D001900:Boston; D057225:Data Mining / Q000379:methods*; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D055695:Electronic Prescribing / Q000706:statistics & numerical data*; D008508:Medication Errors / Q000706:statistics & numerical data*; D009323:Natural Language Processing; D012984:Software; D014584:User-Computer Interface; D018875:Vocabulary, Controlled
keywords: Medication errors; electronic medical records; electronic prescribing; user interface