title: Design and implementation of electronic health record integrated clinical prediction rules (iCPR): a randomized trial in diverse primary care settings.
abstract: Clinical prediction rules (CPRs) represent a method of determining individual patient risk to help providers make more accurate decisions at the point of care. Well-validated CPRs are underutilized but may decrease antibiotic overuse for acute respiratory infections. The integrated clinical prediction rules (iCPR) study builds on a previous single clinic study to integrate two CPRs into the electronic health record and assess their impact on practice. This article discusses study design and implementation of a multicenter cluster randomized control trial of the iCPR clinical decision support system, including the tool adaptation, usability testing, staff training, and implementation study to disseminate iCPR at multiple clinical sites across two health care systems.
  
  
  
  The iCPR tool is based on two well-validated CPRs, one for strep pharyngitis and one for pneumonia. The iCPR tool uses the reason for visit to trigger a risk calculator. Provider completion of the risk calculator provides a risk score, which is linked to an order set. Order sets guide evidence-based care and include progress note documentation, tests, prescription medications, and patient instructions. The iCPR tool was refined based on interviews with providers, medical assistants, and clinic managers, and two rounds of usability testing. "Near live" usability testing with simulated patients was used to ensure that iCPR fit into providers' clinical workflows. Thirty-three Family Medicine and General Internal Medicine primary care clinics were recruited at two institutions. Clinics were randomized to academic detailing about strep pharyngitis and pneumonia diagnosis and treatment (control) or academic detailing plus use of the iCPR tool (intervention). The primary outcome is the difference in antibiotic prescribing rates between the intervention and control groups with secondary outcomes of difference in rapid strep and chest x-ray ordering. Use of the components of the iCPR will also be assessed.
  
  
  
  The iCPR study uses a strong user-centered design and builds on the previous initial study, to assess whether CPRs integrated in the electronic health record can change provider behavior and improve evidence-based care in a broad range of primary care clinics.
  
  
  
  Clinicaltrials.gov ( NCT02534987 ).
authors.affiliation: Division of General Internal Medicine, University of Wisconsin School of Medicine and Public Health, 2828 Marshall Court, Suite 100, Madison, WI, 53705, USA. df2@medicine.wisc.edu.
authors.forename: David A
authors.initials: DA
authors.lastname: Feldstein
authors.affiliation: Division of Health System Innovation and Research, University of Utah School of Medicine, Williams Building, 295 Chipeta Way, Salt Lake City, UT, 84108, USA.
authors.forename: Rachel
authors.initials: R
authors.lastname: Hess
authors.affiliation: Department of Medicine, Hofstra Northwell School of Medicine, 300 Community Drive, Manhasset, NY, 11030, USA.
authors.forename: Thomas
authors.initials: T
authors.lastname: McGinn
authors.affiliation: Department of Medicine, Boston University School of Medicine, 801 Massachusetts Avenue, Crosstown 2, Boston, MA, 02118, USA.
authors.forename: Rebecca G
authors.initials: RG
authors.lastname: Mishuris
authors.affiliation: Department of Medicine, Hofstra Northwell School of Medicine, 600 Community Drive, Suite 300, Manhasset, NY, 11030, USA.
authors.forename: Lauren
authors.initials: L
authors.lastname: McCullagh
authors.affiliation: Department of Family Medicine and Community Health, University of Wisconsin School of Medicine and Public Health, 1100 Delaplaine Court, Madison, WI, 53715, USA.
authors.forename: Paul D
authors.initials: PD
authors.lastname: Smith
authors.affiliation: Westridge Health Center, University of Utah School of Medicine, 3730 West 4700 South, West Valley City, UT, 84118, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Flynn
authors.affiliation: Boston University School of Public Health, Fuller Building M-900C, Boston, MA, 02118, USA.
authors.forename: Joseph
authors.initials: J
authors.lastname: Palmisano
authors.affiliation: Department of Biostatistics, Boston University School of Public Health, Crosstown Center-CT331, Boston, MA, 02118, USA.
authors.forename: Gheorghe
authors.initials: G
authors.lastname: Doros
authors.affiliation: Department of Medicine, New York University School of Medicine, 227 East 30th St. 7th floor, New York, NY, 10016, USA.
authors.forename: Devin
authors.initials: D
authors.lastname: Mann
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000900:Anti-Bacterial Agents / Q000627:therapeutic use*; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D003661:Decision Support Techniques; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D006801:Humans; D008875:Middle Aged; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data; D011320:Primary Health Care / Q000379:methods* / Q000706:statistics & numerical data; D012141:Respiratory Tract Infections / Q000188:drug therapy*; D055815:Young Adult
chemical_list: D000900:Anti-Bacterial Agents
keywords: Clinical decision support; Electronic health record; Implementation science; Pharyngitis; Pneumonia; Randomized controlled trial; Streptococcal infections