title: Impact of automated alerts on follow-up of post-discharge microbiology results: a cluster randomized controlled trial.
abstract: BACKGROUND
  Failure to follow up microbiology results pending at the time of hospital discharge can delay diagnosis and treatment of important infections, harm patients, and increase the risk of litigation. Current systems to track pending tests are often inadequate.
  
  
  OBJECTIVE
  To design, implement, and evaluate an automated system to improve follow-up of microbiology results that return after hospitalized patients are discharged.
  
  
  METHODS
  Cluster randomized controlled trial.
  
  
  METHODS
  Inpatient and outpatient physicians caring for adult patients hospitalized at a large academic hospital from February 2009 to June 2010 with positive and untreated or undertreated blood, urine, sputum, or cerebral spinal fluid cultures returning post-discharge.
  
  
  METHODS
  An automated e-mail-based system alerting inpatient and outpatient physicians to positive post-discharge culture results not adequately treated with an antibiotic at the time of discharge.
  
  
  METHODS
  Our primary outcome was documented follow-up of results within 3 days. Secondary outcomes included physician awareness and assessment of result urgency, impact on clinical assessments and plans, and preferred alerting scenarios.
  
  
  RESULTS
  We evaluated the follow-up of 157 post-discharge microbiology results from patients of 121 physicians. We found documented follow-up in 27/97 (28%) results in the intervention group and 8/60 (13%) in the control group [aOR 3.2, (95% CI 1.3-8.4); p=0.01]. Of all inpatient physician respondents, 32/82 (39%) were previously aware of the results, 45/77 (58%) felt the results changed their assessments and plans, 43/77 (56%) felt the results required urgent action, and 67/70 (96%) preferred alerts for current or broader scenarios.
  
  
  CONCLUSIONS
  Our alerting system improved the proportion of important post-discharge microbiology results with documented follow-up, though the proportion remained low. The alerts were well received and may be expanded in the future.
authors.affiliation: Division of Biomedical Informatics, University of California San Diego, 9500 Gilman Dr., no. 0505, La Jolla, San Diego, CA 92093-0505, USA, relkareh@ucsd.edu
authors.forename: Robert
authors.initials: R
authors.lastname: El-Kareh
authors.forename: Christopher
authors.initials: C
authors.lastname: Roy
authors.forename: Deborah H
authors.initials: DH
authors.lastname: Williams
authors.forename: Eric G
authors.initials: EG
authors.lastname: Poon
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001331:Automation / Q000592:standards; D016000:Cluster Analysis; D003266:Continuity of Patient Care / Q000592:standards / Q000639:trends*; D003955:Diagnostic Tests, Routine / Q000592:standards / Q000639:trends*; D034742:Electronic Mail / Q000592:standards / Q000639:trends*; D005500:Follow-Up Studies; D006801:Humans; D050316:Medical Order Entry Systems / Q000592:standards / Q000639:trends*; D008875:Middle Aged; D010351:Patient Discharge / Q000592:standards / Q000639:trends*; D011446:Prospective Studies