Patient-specific electronic decision support reduces prescription of excessive doses

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.

[1]  J. McCulloch,et al.  CHAPTER 7 – Implications for Prevention , 1972 .

[2]  L. Dettli.  The Kidney in Pre-Clinical and Clinical Pharmacokinetics , 1984 .

[3]  H Pohl,et al.  Medication prescribing errors in a teaching hospital. , 1990, JAMA.

[4]  L. Lenert,et al.  Practical computer-assisted dosing for aminoglycoside antibiotics , 1992, Antimicrobial Agents and Chemotherapy.

[5]  P. Casner,et al.  A randomized controlled trial of computerized pharmacokinetic theophylline dosing versus empiric physician dosing , 1993, Clinical pharmacology and therapeutics.

[6]  N. Laird,et al.  Incidence of Adverse Drug Events and Potential Adverse Drug Events: Implications for Prevention , 1995 .

[7]  N. Laird,et al.  Incidence of adverse drug events and potential adverse drug events , 1995 .

[8]  S D Small,et al.  Incidence of adverse drug events and potential adverse drug events. Implications for prevention. ADE Prevention Study Group. , 1995, JAMA.

[9]  H Pohl,et al.  Medication-prescribing errors in a teaching hospital. A 9-year experience. , 1997, Archives of internal medicine.

[10]  V. Rodighiero.  Effects of Liver Disease on Pharmacokinetics , 1999, Clinical pharmacokinetics.

[11]  M Peters,et al.  Implementation of rules based computerised bedside prescribing and administration: intervention study , 2000, BMJ : British Medical Journal.

[12]  D. Bates,et al.  Guided medication dosing for inpatients with renal insufficiency. , 2001, JAMA.

[13]  Timothy S Lesar,et al.  Tenfold Medication Dose Prescribing Errors , 2002, The Annals of pharmacotherapy.

[14]  D. Bates,et al.  Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. , 2003, Archives of internal medicine.

[15]  J. Vuyk.  Pharmacodynamics in the elderly. , 2003, Best practice & research. Clinical anaesthesiology.

[16]  Robyn Tamblyn,et al.  Reasons for Physician Non-Adherence to Electronic Drug Alerts , 2004, MedInfo.

[17]  Almut G Winterstein,et al.  Nature and causes of clinically significant medication errors in a tertiary care hospital. , 2004, American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists.

[18]  W. Haefeli,et al.  Dose individualisation in patients with renal insufficiency: does drug labelling support optimal management? , 2004, European Journal of Clinical Pharmacology.

[19]  A. Localio,et al.  Role of computerized physician order entry systems in facilitating medication errors. , 2005, JAMA.

[20]  E. Balas,et al.  Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success , 2005, BMJ : British Medical Journal.

[21]  R. C. Kirk,et al.  Computer Calculated Dose in Paediatric Prescribing , 2005, Drug safety.

[22]  D. Bates,et al.  Guided prescription of psychotropic medications for geriatric inpatients. , 2005, Archives of internal medicine.

[23]  M. Marciello,et al.  Efficacy of Computer-Aided Dosing of Warfarin Among Patients in a Rehabilitation Hospital , 2005, American journal of physical medicine & rehabilitation.

[24]  R. Shah.  Mechanistic basis of adverse drugreactions: the perils of inappropriate dose schedules , 2005, Expert opinion on drug safety.

[25]  A. Localio,et al.  Role of computerized physician order entry systems in facilitating medication errors. , 2005 .

[26]  Marc Berg,et al.  Overriding of drug safety alerts in computerized physician order entry. , 2006, Journal of the American Medical Informatics Association : JAMIA.

[27]  A. Seeringer,et al.  Clinical implications of pharmacogenetics of cytochrome P450 drug metabolizing enzymes. , 2007, Biochimica et biophysica acta.

[28]  T. Bertsche,et al.  Detection and prevention of prescriptions with excessive doses in electronic prescribing systems , 2007, European Journal of Clinical Pharmacology.

[29]  Myrna Y Munar,et al.  Drug dosing adjustments in patients with chronic kidney disease. , 2007, American family physician.

[30]  A. Egberts,et al.  Frequency of and Risk Factors for Preventable Medication-Related Hospital Admissions in the Netherlands , 2009 .

[31]  G. Maartens,et al.  Outcomes of nevirapine- and efavirenz-based antiretroviral therapy when coadministered with rifampicin-based antitubercular therapy. , 2008, JAMA.

[32]  Jens Kaltschmidt,et al.  Successful strategy to improve the specificity of electronic statin–drug interaction alerts , 2009, European Journal of Clinical Pharmacology.