Qual Saf Health Care 19:e15 doi:10.1136/qshc.2009.033175
  • Original research

Patient-specific electronic decision support reduces prescription of excessive doses

  1. W E Haefeli1,2
  1. 1Department of Internal Medicine VI, Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Heidelberg, Germany
  2. 2Cooperation Unit Clinical Pharmacy, University of Heidelberg, Heidelberg, Germany
  3. 3Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany
  1. Correspondence to Professor Walter E Haefeli, Department of Internal Medicine VI, Clinical Pharmacology and Pharmacoepidemiology, University of Heidelberg, Im Neuenheimer Feld 410, Heidelberg 69120, Germany; walter.emil.haefeli{at}
  1. Contributors HMS, SPWS, IWS, TBe and WEH designed the study protocol. HMS, MGP, CS, SPWS, JK, IWS, TBe and WEH were involved in developing the knowledgebase and the CDS system. HMS and SPWS conducted the study, HMS, SPWS, TBr, IWS and WEH carried out analysis and interpretation of the data. TBe, JK and WEH raised funding and supervised the whole study. HMS prepared the first draft of the manuscript. All authors critically revised the manuscript. HMS and WEH had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

  • Accepted 31 August 2009
  • Published Online First 27 April 2010


Objectives Prescription of excessive doses is the most common prescription error, provoking dose-dependent adverse drug reactions. Clinical decision support systems (CDSS) can prevent prescription errors especially when mainly clinically relevant warnings are issued. We have built and evaluated a CDSS providing upper dose limits personalised to individual patient characteristics thus guaranteeing for specific warnings.

Methods For 170 compounds, detailed information on upper dose limits (according to the drug label) was compiled. A comprehensive software-algorithm extracted relevant patient information from the electronic chart (eg, age, renal function, comedication). The CDSS was integrated into the local prescribing platform for outpatients and patients at discharge, providing immediate dosage feedback. Its impact was evaluated in a 90-day intervention study (phase 1: baseline; phase 2: intervention). Outcome measures were frequency of excessive doses before and after intervention considering potential induction of new medication errors. Moreover, predictors for alert adherence were analysed.

Results In phase 1, 552 of 12 197 (4.5%) prescriptions exceeded upper dose limits. In phase 2, initially 559 warnings were triggered (4.8%, p=0.37). Physicians were responsive to one in four warnings mostly adjusting dosages. Thus, the final prescription rate of excessive doses was reduced to 3.6%, with 20% less excessive doses compared with baseline (p<0.001). No new manifest prescription errors were induced. Physicians' alert adherence correlated with patients' age, prescribed drug class, and reason for the alert.

Conclusion During the 90-day study, implementation of a highly specific algorithm-based CDSS substantially improved prescribing quality with a high acceptance rate compared with previous studies.


  • Funding The work was supported in part by the Chamber of Pharmacists, Baden-Wuerttemberg, Germany. The funding source was not involved in study design, collection, analysis, interpretation of data or in writing the report and submitting it for publication.

  • Competing interests None.

  • Ethics approval This study was conducted with the approval of the Ethics Committee of the Medical Faculty of the University of Heidelberg.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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