title: Typed versus voice recognition for data entry in electronic health records: emergency physician time use and interruptions.
abstract: BACKGROUND
  Use of electronic health record (EHR) systems can place a considerable data entry burden upon the emergency department (ED) physician. Voice recognition data entry has been proposed as one mechanism to mitigate some of this burden; however, no reports are available specifically comparing emergency physician (EP) time use or number of interruptions between typed and voice recognition data entry-based EHRs. We designed this study to compare physician time use and interruptions between an EHR system using typed data entry versus an EHR with voice recognition.
  
  
  METHODS
  We collected prospective observational data at 2 academic teaching hospital EDs, one using an EHR with typed data entry and the other with voice recognition capabilities. Independent raters observed EP activities during regular shifts. Tasks each physician performed were noted and logged in 30 second intervals. We compared time allocated to charting, direct patient care, and change in tasks leading to interruptions between sites.
  
  
  RESULTS
  We logged 4,140 minutes of observation for this study. We detected no statistically significant differences in the time spent by EPs charting (29.4% typed; 27.5% voice) or the time allocated to direct patient care (30.7%; 30.8%). Significantly more interruptions per hour were seen with typed data entry versus voice recognition data entry (5.33 vs. 3.47; p=0.0165).
  
  
  CONCLUSIONS
  The use of a voice recognition data entry system versus typed data entry did not appear to alter the amount of time physicians spend charting or performing direct patient care in an ED setting. However, we did observe a lower number of workflow interruptions with the voice recognition data entry EHR. Additional research is needed to further evaluate the data entry burden in the ED and examine alternative mechanisms for chart entry as EHR systems continue to evolve.
authors.affiliation: Southern Illinois University School of Medicine, Department of Surgery, Division of Emergency Medicine, Springfield, Illinois.
authors.forename: Jonathan E
authors.initials: JE
authors.lastname: Dela Cruz
authors.affiliation: Southern Illinois University School of Medicine, Department of Surgery, Division of Emergency Medicine, Springfield, Illinois.
authors.forename: John C
authors.initials: JC
authors.lastname: Shabosky
authors.affiliation: Southern Illinois University School of Medicine, Department of Surgery, Division of Emergency Medicine, Springfield, Illinois.
authors.forename: Matthew
authors.initials: M
authors.lastname: Albrecht
authors.affiliation: Southern Illinois University School of Medicine, Department of Surgery, Division of Emergency Medicine, Springfield, Illinois.
authors.forename: Ted R
authors.initials: TR
authors.lastname: Clark
authors.affiliation: Southern Illinois University School of Medicine, Department of Surgery and Center for Clinical Research, Springfield, Illinois.
authors.forename: Joseph C
authors.initials: JC
authors.lastname: Milbrandt
authors.affiliation: Southern Illinois University School of Medicine, Department of Surgery, Division of Emergency Medicine, Springfield, Illinois.
authors.forename: Steven J
authors.initials: SJ
authors.lastname: Markwell
authors.affiliation: Southern Illinois University School of Medicine, Department of Surgery, Division of Emergency Medicine, Springfield, Illinois.
authors.forename: Jason A
authors.initials: JA
authors.lastname: Kegg
mesh_terms: D057286:Electronic Health Records; D004636:Emergency Service, Hospital / Q000458:organization & administration*; D005568:Forms and Records Control / Q000379:methods*; D006801:Humans; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D011446:Prospective Studies; D049250:Speech Recognition Software; D013997:Time Factors; D014584:User-Computer Interface