title: Experience with decision support system and comfort with topic predict clinicians' responses to alerts and reminders.
abstract: OBJECTIVE
  Clinicians at our institution typically respond to about half of the prompts they are given by the clinic's computer decision support system (CDSS). We sought to examine factors associated with clinician response to CDSS prompts as part of a larger, ongoing quality improvement effort to optimize CDSS use.
  
  
  METHODS
  We examined patient, prompt, and clinician characteristics associated with clinician response to decision support prompts from the Child Health Improvement through Computer Automation (CHICA) system. We asked pediatricians who were nonusers of CHICA to rate decision support topics as "easy" or "not easy" to discuss with patients and their guardians. We analyzed these ratings and data, from July 1, 2009 to January 29, 2013, utilizing a hierarchical regression model, to determine whether factors such as comfort with the prompt topic and the length of the user's experience with CHICA contribute to user response rates.
  
  
  RESULTS
  We examined 414 653 prompts from 22 260 patients. The length of time a clinician had been using CHICA was associated with an increase in their prompt response rate. Clinicians were more likely to respond to topics rated as "easy" to discuss. The position of the prompt on the page, clinician gender, and the patient's age, race/ethnicity, and preferred language were also predictive of prompt response rate.
  
  
  CONCLUSIONS
  This study highlights several factors associated with clinician prompt response rates that could be generalized to other health information technology applications, including the clinician's length of exposure to the CDSS, the prompt's position on the page, and the clinician's comfort with the prompt topic. Incorporating continuous quality improvement efforts when designing and implementing health information technology may ensure that its use is optimized.
authors.affiliation: Indiana University School of Medicine, Department of Pediatrics, Section of Children's Health Services Research, Indianapolis, Indiana, USA Indiana University School of Medicine, Department of Pediatrics, Section of Pediatric and Adolescent Comparative Effectiveness Research, Indianapolis, Indiana, USA nsbauer@iu.edu.
authors.forename: Nerissa S
authors.initials: NS
authors.lastname: Bauer
authors.affiliation: Indiana University School of Medicine, Department of Pediatrics, Section of Pediatric and Adolescent Comparative Effectiveness Research, Indianapolis, Indiana, USA Regenstrief Institute for Healthcare, Indianapolis, Indiana, USA.
authors.forename: Aaron E
authors.initials: AE
authors.lastname: Carroll
authors.affiliation: Indiana University School of Medicine, Department of Biostatistics, Indianapolis, Indiana, USA.
authors.forename: Chandan
authors.initials: C
authors.lastname: Saha
authors.affiliation: Indiana University School of Medicine, Department of Pediatrics, Section of Children's Health Services Research, Indianapolis, Indiana, USA Indiana University School of Medicine, Department of Pediatrics, Section of Pediatric and Adolescent Comparative Effectiveness Research, Indianapolis, Indiana, USA.
authors.forename: Stephen M
authors.initials: SM
authors.lastname: Downs
mesh_terms: D000293:Adolescent; D001291:Attitude of Health Personnel; D001292:Attitude to Computers; D002648:Child; D002675:Child, Preschool; D056902:Clinical Alarms; D020000:Decision Support Systems, Clinical; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D016015:Logistic Models; D008297:Male; D015999:Multivariate Analysis; D010372:Pediatrics; D017010:Reminder Systems; D055815:Young Adult
keywords: clinical guidelines; computer-based decision support; pediatrics; primary care