title: Detection and prevention of prescriptions with excessive doses in electronic prescribing systems.
abstract: BACKGROUND
  Dose dependent adverse drug reactions are often caused by prescribing errors ignoring upper dose limits. Thus, computerised physician order entry incorporating maximum recommended therapeutic doses (MRTDs) might reduce prescriptions of excessive doses. We evaluated the suitability of MRTD information as published in the Summary of Product Characteristics (SPC) (MRTD(SPC)) or by the US Food and Drug Administration (MRTD(FDA)) and the value of Defined Daily Doses (DDD, World Health Organisation) as knowledge bases for an alerting system.
  
  
  METHODS
  In a large set of critical-dose drugs (N = 140) we compared MRTD(FDA) and DDD values with the corresponding German MRTD(SPC). We then retrospectively assessed a set of 633 electronically prescribed drugs (EPDs) issued at a university hospital and calculated prescription rates of excessive doses.
  
  
  RESULTS
  MRTD(FDA) was similar to MRTD(SPC) in 37% (N = 140), higher in 32%, and lower in 31% of drugs. On average, available DDD values (N = 129) were 1.6 times lower than MRTD(SPC), with 64% being lower, 33% similar, and 3% larger than MRTD(SPC). Prescription rates of excessive doses according to MRTD(FDA) were 2.5-fold higher (6.1%) than according to MRTD(SPC) (2.5%) (p < 0.01). However, only one in four EPDs categorised as overdosed according to MRTD(FDA) exceeded MRTD(SPC), and MRTD(FDA) values were available only for 67% of all assessed EPDs.
  
  
  CONCLUSIONS
  Our study revealed a remarkable number of prescriptions with doses exceeding approved limits. Their prevention appears feasible but the choice of an appropriate database for MRTDs is essential, and differences between available information sources are large.
authors.affiliation: Department of Internal Medicine VI, Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Im Neuenheimer Feld 410, 69120 Heidelberg, Germany.
authors.forename: H M
authors.initials: HM
authors.lastname: Seidling
authors.forename: A
authors.initials: A
authors.lastname: Al Barmawi
authors.forename: J
authors.initials: J
authors.lastname: Kaltschmidt
authors.forename: T
authors.initials: T
authors.lastname: Bertsche
authors.forename: M G
authors.initials: MG
authors.lastname: Pruszydlo
authors.forename: W E
authors.initials: WE
authors.lastname: Haefeli
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems / Q000706:statistics & numerical data*; D016208:Databases, Factual; D020000:Decision Support Systems, Clinical / Q000295:instrumentation* / Q000458:organization & administration; D011307:Drug Prescriptions; D004360:Drug Therapy, Computer-Assisted; D006801:Humans; D008499:Medical Records; D008508:Medication Errors / Q000517:prevention & control* / Q000706:statistics & numerical data