Improving medication-related clinical decision support. (15th February 2018)

• Record Type: Journal Article
• Authors: Tolley, Clare L.; Slight, Sarah P.; Husband, Andrew K.; Watson, Neil; Bates, David W.
• Is Part Of: American journal of health-system pharmacy. Volume 75:Number 4(2019)
• Page Start: 239
• Page End: 246
• Publication Date: 2018-02-15
• Subjects: decision-making -- decision support systems -- clinical -- electronic prescribing -- medical order entry systems -- medication errors -- patient safety; Hospital pharmacies -- United States -- Periodicals; 615.1
• DOI: 10.2146/ajhp160830
• Languages: English
• ISSNs: 1079-2082

Abstract

Abstract : Purpose: Current uses of medication-related clinical decision support (CDS) and recommendations for improving these systems are reviewed. Summary: Using a systematic approach, articles published from 2007 through 2014 were identified in MEDLINE and EMBASE using MeSH terms and keywords relating to the 5 basic medication-related CDS functionalities. A total of 156 full-text articles and 28 conference abstracts were reviewed across each of the 5 areas: drug–drug interaction (DDI) checks ( n = 78), drug allergy checks ( n = 20), drug dose support ( n = 55), drug duplication checks ( n = 11), and drug formulary support ( n = 20). The success of medication-related CDS depends on users finding the alerts valuable and acting on the information received. Improving alert specificity and sensitivity is important for all domains. Tiering is important for improving the acceptance of DDI alerts. The ability to perform appropriate cross-sensitivity checks is key to producing appropriate drug allergy checks. Drug dosage alerts should be individualized and deliver practical recommendations. How the system is configured to identify certain drug duplications is important to prevent possible patient toxicity. Accurate knowledge databases are needed to produce relevant drug formulary alerts and encourage formulary adherence. Medication-related CDS is still relatively immature in some organizations and has substantial room for improvement. For example, decision support should consider more patient-specific factors, human factors principles should always be considered, and alert specificity must be improved in order to reduce alert fatigue. Conclusion: Standardization, integration of patient-specific parameters, and consideration of human factors design principles are central to realizing the potential benefits of medication-related CDS.