title: Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain?
abstract: BACKGROUND
  Follow-up of abnormal outpatient laboratory test results is a major patient safety concern. Electronic medical records can potentially address this concern through automated notification. We examined whether automated notifications of abnormal laboratory results (alerts) in an integrated electronic medical record resulted in timely follow-up actions.
  
  
  METHODS
  We studied 4 alerts: hemoglobin A1c > or =15%, positive hepatitis C antibody, prostate-specific antigen > or =15 ng/mL, and thyroid-stimulating hormone > or =15 mIU/L. An alert tracking system determined whether the alert was acknowledged (ie, provider clicked on and opened the message) within 2 weeks of transmission; acknowledged alerts were considered read. Within 30 days of result transmission, record review and provider contact determined follow-up actions (eg, patient contact, treatment). Multivariable logistic regression models analyzed predictors for lack of timely follow-up.
  
  
  RESULTS
  Between May and December 2008, 78,158 tests (hemoglobin A1c, hepatitis C antibody, thyroid-stimulating hormone, and prostate-specific antigen) were performed, of which 1163 (1.48%) were transmitted as alerts; 10.2% of these (119/1163) were unacknowledged. Timely follow-up was lacking in 79 (6.8%), and was statistically not different for acknowledged and unacknowledged alerts (6.4% vs 10.1%; P =.13). Of 1163 alerts, 202 (17.4%) arose from unnecessarily ordered (redundant) tests. Alerts for a new versus known diagnosis were more likely to lack timely follow-up (odds ratio 7.35; 95% confidence interval, 4.16-12.97), whereas alerts related to redundant tests were less likely to lack timely follow-up (odds ratio 0.24; 95% confidence interval, 0.07-0.84).
  
  
  CONCLUSIONS
  Safety concerns related to timely patient follow-up remain despite automated notification of non-life-threatening abnormal laboratory results in the outpatient setting.
authors.affiliation: Michael E. DeBakey Veterans Affairs Medical Center and the Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA. hardeeps@bcm.tmc.edu
authors.forename: Hardeep
authors.initials: H
authors.lastname: Singh
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Thomas
authors.forename: Dean F
authors.initials: DF
authors.lastname: Sittig
authors.forename: Lindsey
authors.initials: L
authors.lastname: Wilson
authors.forename: Donna
authors.initials: D
authors.lastname: Espadas
authors.forename: Myrna M
authors.initials: MM
authors.lastname: Khan
authors.forename: Laura A
authors.initials: LA
authors.lastname: Petersen
mesh_terms: D003142:Communication; D003951:Diagnostic Errors / Q000706:statistics & numerical data*; D005260:Female; D005500:Follow-Up Studies; D006526:Hepatitis C / Q000175:diagnosis*; D006801:Humans; D008297:Male; D016347:Medical Records Systems, Computerized; D010818:Practice Patterns, Physicians'; D011320:Primary Health Care / Q000379:methods*; D012189:Retrospective Studies; D014481:United States