title: Pediatric emergency department discharge prescriptions requiring pharmacy clarification.
abstract: OBJECTIVE
  The aims of the study were to analyze and classify reasons why retail pharmacies need to contact the pediatric emergency department (PED) for clarification on outpatient prescriptions generated using an electronic prescribing system and to categorize the severity of errors captured.
  
  
  METHODS
  A retrospective chart review was conducted at a PED that cares for approximately 92,000 patients annually. All pharmacy callbacks documented in the electronic medical record between August 1, 2008 and July 31, 2009 were included. A datasheet was used to capture patient demographics (age, sex, race, insurance), prescriptions written, and reason for callback. Each call was then assigned a severity level, and time to respond to all calls was estimated. Frequencies were used to analyze the data.
  
  
  RESULTS
  A total of 731 errors for 695 callbacks were analyzed from 49,583 prescriptions written at discharge. The most common errors included administrative/insurance issues 342/731 (47%) and prescription writing errors 298/731 (41%). The errors were classified as insignificant (340/729 [47%]), problematic (288/729 [40%]), significant (77/729 [11%]), serious (12/729 [1.64%]), and severe (12/729 [1.64%]). Almost 96% of errant prescriptions were not able to be filled as originally written and required a change by the prescriber. These calls required approximately 127 hours to complete.
  
  
  CONCLUSIONS
  Prescription errors requiring a pharmacy callback are typically insignificant. However, 13.8% of callbacks about an error were considered significant, serious, or severe. Automated dose checking and verifying insurance coverage of prescribed medications should be considered essential components of prescription writing in a PED.
authors.affiliation: From the *Division of Pharmacy and †Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.
authors.forename: Michelle C
authors.initials: MC
authors.lastname: Caruso
authors.forename: Michael A
authors.initials: MA
authors.lastname: Gittelman
authors.forename: Michelle L
authors.initials: ML
authors.lastname: Widecan
authors.forename: Joseph W
authors.initials: JW
authors.lastname: Luria
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D011307:Drug Prescriptions / Q000706:statistics & numerical data*; D057286:Electronic Health Records; D055695:Electronic Prescribing / Q000706:statistics & numerical data*; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D006776:Hospitals, Pediatric / Q000706:statistics & numerical data*; D006784:Hospitals, Teaching / Q000706:statistics & numerical data; D006786:Hospitals, Urban / Q000706:statistics & numerical data; D006801:Humans; D057970:Inappropriate Prescribing; D007223:Infant; D019458:Insurance Coverage; D007356:Insurance, Pharmaceutical Services; D008508:Medication Errors; D009820:Ohio; D010351:Patient Discharge; D010607:Pharmacy Service, Hospital / Q000706:statistics & numerical data*; D010818:Practice Patterns, Physicians'; D011306:Prescription Fees; D012189:Retrospective Studies; D013689:Telephone; D013997:Time Factors; D014193:Trauma Centers / Q000706:statistics & numerical data*