A systematic approach to optimize electronic health record medication alerts in a health system.

Purpose The effectiveness of a systematic, streamlined approach to optimize drug–drug interaction alerts in an electronic health record for a health system was studied. Methods An 81-week quasi-experimental study was conducted to evaluate interventions made to medication-related clinical decision-su...

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Publicado en:American Journal of Health-System Pharmacy Vol. 76; no. 8; pp. 530 - 537
Autores principales: Bhakta, Sunny B, Colavecchia, A Carmine, Haines, Linda, Varkey, Divya, Garey, Kevin W
Formato: algorithm research tables/charts Journal Article
Publicado: Oxford University Press / USA 4/15/2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 4/15/2019
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      pub: Oxford University Press / USA
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        10.1093/ajhp/zxz012
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        atl: A systematic approach to optimize electronic health record medication alerts in a health system.
      aug:
        au:
          Bhakta, Sunny B
          Colavecchia, A Carmine
          Haines, Linda
          Varkey, Divya
          Garey, Kevin W
        affil: Department of Pharmacy Services, Houston Methodist Hospital, Houston, TX University of Houston College of Pharmacy, Houston, TX
      sug:
        subj:
          Medication Errors Prevention and Control
          Electronic Health Records
          Drug Interactions
          Medication Systems
          Electronic Order Entry
          Decision Support Systems, Clinical
          Human
          Quasi-Experimental Studies
          Multidisciplinary Care Team
          Pharmacist Attitudes
          Interrupted Time Series Analysis
          Regression
          Inpatients
          Attitude of Health Personnel
      ab: Purpose The effectiveness of a systematic, streamlined approach to optimize drug–drug interaction alerts in an electronic health record for a health system was studied. Methods An 81-week quasi-experimental study was conducted to evaluate interventions made to medication-related clinical decision-support (CDS) alerts. Medication-related CDS alerts were systematically reduced using a multi disciplinary healthcare committee. The primary endpoint was weekly overall, modification, and acknowledgement rates of medication alerts after drug–drug interaction reclassification. Secondary endpoints included sub analysis of types of medication alerts (drug–drug interaction and duplicate therapy alerts) and alert use by providers (pharmacist and prescribers). Data was analyzed using interrupted time series regression analysis. Results After implementation of the new alert system, total number of weekly inpatient alerts decreased from 68,900 (66,300–70,900) and 50,300 (48,600–53,600) in the postintervention period (p < 0.001). The perentage of alerts acknowledged weekly increased from 11.8% (IQR, 11.4–12.1%) in the preintervention period to 13.7% (IQR, 13.3–14.0%) in the postintervention period (p < 0.001). The percentage of alerts that were modified also increased from 5.0% (IQR, 4.9–5.3%) in the preintervention period to 7.3% (IQR, 7.0–7.6%) in the postintervention period (p < 0.001). Both increases were primarily seen with pharmacists versus other healthcare professionals (p < 0.001). Conclusion A committee-led systematic approach to optimizing drug–drug interactions facilitated a significant decrease in the overall number of alerts and an increase in both medication alert acknowledgement and modification rates.
      pubtype: Academic Journal
      doctype:
        algorithm
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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