title: Comparison of methods for identifying patients at risk of medication-related harm.
abstract: BACKGROUND
  With the introduction of Computerised Physician Order Entry (CPOE) in routine hospital care, a great deal of effort has been put into refining Clinical Decision Support Systems (CDSS) to identify patients at risk of preventable medication-related harm.
  
  
  OBJECTIVE
  This study compared a CPOE with basic CDSS and 16 clinical rules with a manual pharmacist medication review to detect overdose and drug-drug interactions that actually required a change in medication.
  
  
  METHODS
  The study involved the review of 313 patients admitted over 5 months at an internal medicine ward where a change in medication as a result of dosing of therapeutic errors was detected by a manual medication review by a trained pharmacist. Subsequently, all these patients' medication orders (MOs) were entered into the authors' CPOE with basic CDSS. Medication orders with a safety alert indicating overdose and drug-drug interactions generated by the authors' CPOE with basic CDSS were compared with the same type of medication errors identified through manual review. The positive predictive value (PPV), sensitivity and specificity compared with manual review were determined. Second, a set of 16 clinical rules was applied to the patient and prescribing data. The overlap between the clinical rules and manual review was determined by comparing patients triggered by the clinical rule with patients with a corresponding error in the manual medication review.
  
  
  RESULTS
  Manual medication review identified 57 medication errors involving overdose and 143 therapeutic errors of which 46 were drug-drug interactions. The CPOE with basic CDDS generated 297 safety alerts involving overdose (PPV 0.06, sensitivity 0.32, specificity 0.92) and 365 safety alerts involving drug-drug interactions (PPV 0.12, sensitivity 0.96, specificity 0.91). The clinical rules generated 313 safety alerts identifying 39% of all the overdoses and therapeutic errors found in the manual review at which they were targeted. In 23% of the alerts generated by a clinical rule, the patients actually required a change of medication as indicated by the manual review. When CPOE with basic CDSS and the rules were combined, 66% of the overdoses and therapeutic errors were identified.
  
  
  CONCLUSIONS
  The authors' CPOE with basic CDSS and the clinical rules are useful early strategies for preventing medication-related harm. They could be a first step towards more advanced decision support. These computerised systems will be even more useful in daily practice, once they are further fine-tuned to decrease the number of alerts that need no clinical action.
authors.affiliation: Department of Hospital and Clinical Pharmacy, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands. j.v.doormaal@mzh.nl
authors.forename: Jasperien E
authors.initials: JE
authors.lastname: van Doormaal
authors.forename: Mirjam K
authors.initials: MK
authors.lastname: Rommers
authors.forename: Jos G W
authors.initials: JG
authors.lastname: Kosterink
authors.forename: Irene M
authors.initials: IM
authors.lastname: Teepe-Twiss
authors.forename: Flora M
authors.initials: FM
authors.lastname: Haaijer-Ruskamp
authors.forename: Peter G M
authors.initials: PG
authors.lastname: Mol
mesh_terms: D020000:Decision Support Systems, Clinical; D005260:Female; D006801:Humans; D008297:Male; D050316:Medical Order Entry Systems; D008508:Medication Errors / Q000517:prevention & control* / Q000639:trends; D010607:Pharmacy Service, Hospital; D011785:Quality Assurance, Health Care; D018570:Risk Assessment; D017751:Safety Management