{"title":"在电子处方系统中重新设计临床决策过敏和药物相互作用警报对患者安全的影响-一项定量描述性研究","authors":"V. Khalil, A. Hua","doi":"10.29337/ijdh.40","DOIUrl":null,"url":null,"abstract":"Background: Electronic medication management systems (EMS) generate medication alerts such as Drug-Drug interaction (DDI) and allergy at the drug order entry point for clinicians to improve patients’ safety. EMS that provide non-clinically significant alerts contribute to alert fatigue and pose a risk for patients’ harm. The primary aim is to assess the impact of redesign of allergy and DDI alerts on alerts’ trigger and overrides rates. The secondary aim is to assess the impact of the redesign of the alerts on reported patients’ harm. Methodology: A retrospective cross sectional 2 stage study was conducted. Stage 1 involved analysis of inpatients’ electronic drug orders in the hospital’s EMS that triggered an allergy, or a DDI alert from October to December 2019 in a 650 bed Australian hospital. A report on the 50 commonly overridden allergy and DDI alerts was reviewed by a multidisciplinary team to assess the clinical significance of the alerts using a risk matrix tool, frequency of overrides as well as published literature on adverse effects. Subsequently, non-clinically significant allergies and DDI alerts were deactivated in EMS system in March 2020. Stage 2 of the study involved the same analysis conducted in stage 1 (March to May 2021). The number of alerts overrides, alert trigger rates and number of related reported incidents involving patients’ harm were analysed. Results: A total of 288,267 and 288,133 prescriptions orders were reviewed in the 2 stages respectively. A total of 12 DDI and 37 allergy alerts were deactivated in stage 2. Redesign of the alerts reduced the trigger rate of allergy alerts (4.96% to 3.77%, P < 0.0001) and DDI alerts (5.30% to 4.73%, P < 0.0001). A statistically significant reduction in the number of incidents with reported patients’ harm related to overrides of alerts was observed in the post intervention phase. The allergy alert trigger rate was reduced from 4.96% to 3.77%, P = 0.0172. Conclusion: The study demonstrated that using an evidence-based approach and a risk assessment matrix to deactivate non-clinically significant alerts","PeriodicalId":372681,"journal":{"name":"International Journal of Digital Health","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Impact of Redesign of a Clinical Decision Allergy and Drug Interactions Alerts in an Electronic Prescribing System on Patient Safety – A Quantitative Descriptive Study\",\"authors\":\"V. Khalil, A. Hua\",\"doi\":\"10.29337/ijdh.40\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Electronic medication management systems (EMS) generate medication alerts such as Drug-Drug interaction (DDI) and allergy at the drug order entry point for clinicians to improve patients’ safety. EMS that provide non-clinically significant alerts contribute to alert fatigue and pose a risk for patients’ harm. The primary aim is to assess the impact of redesign of allergy and DDI alerts on alerts’ trigger and overrides rates. The secondary aim is to assess the impact of the redesign of the alerts on reported patients’ harm. Methodology: A retrospective cross sectional 2 stage study was conducted. Stage 1 involved analysis of inpatients’ electronic drug orders in the hospital’s EMS that triggered an allergy, or a DDI alert from October to December 2019 in a 650 bed Australian hospital. A report on the 50 commonly overridden allergy and DDI alerts was reviewed by a multidisciplinary team to assess the clinical significance of the alerts using a risk matrix tool, frequency of overrides as well as published literature on adverse effects. Subsequently, non-clinically significant allergies and DDI alerts were deactivated in EMS system in March 2020. Stage 2 of the study involved the same analysis conducted in stage 1 (March to May 2021). The number of alerts overrides, alert trigger rates and number of related reported incidents involving patients’ harm were analysed. Results: A total of 288,267 and 288,133 prescriptions orders were reviewed in the 2 stages respectively. A total of 12 DDI and 37 allergy alerts were deactivated in stage 2. Redesign of the alerts reduced the trigger rate of allergy alerts (4.96% to 3.77%, P < 0.0001) and DDI alerts (5.30% to 4.73%, P < 0.0001). A statistically significant reduction in the number of incidents with reported patients’ harm related to overrides of alerts was observed in the post intervention phase. The allergy alert trigger rate was reduced from 4.96% to 3.77%, P = 0.0172. Conclusion: The study demonstrated that using an evidence-based approach and a risk assessment matrix to deactivate non-clinically significant alerts\",\"PeriodicalId\":372681,\"journal\":{\"name\":\"International Journal of Digital Health\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Digital Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29337/ijdh.40\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Digital Health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29337/ijdh.40","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Impact of Redesign of a Clinical Decision Allergy and Drug Interactions Alerts in an Electronic Prescribing System on Patient Safety – A Quantitative Descriptive Study
Background: Electronic medication management systems (EMS) generate medication alerts such as Drug-Drug interaction (DDI) and allergy at the drug order entry point for clinicians to improve patients’ safety. EMS that provide non-clinically significant alerts contribute to alert fatigue and pose a risk for patients’ harm. The primary aim is to assess the impact of redesign of allergy and DDI alerts on alerts’ trigger and overrides rates. The secondary aim is to assess the impact of the redesign of the alerts on reported patients’ harm. Methodology: A retrospective cross sectional 2 stage study was conducted. Stage 1 involved analysis of inpatients’ electronic drug orders in the hospital’s EMS that triggered an allergy, or a DDI alert from October to December 2019 in a 650 bed Australian hospital. A report on the 50 commonly overridden allergy and DDI alerts was reviewed by a multidisciplinary team to assess the clinical significance of the alerts using a risk matrix tool, frequency of overrides as well as published literature on adverse effects. Subsequently, non-clinically significant allergies and DDI alerts were deactivated in EMS system in March 2020. Stage 2 of the study involved the same analysis conducted in stage 1 (March to May 2021). The number of alerts overrides, alert trigger rates and number of related reported incidents involving patients’ harm were analysed. Results: A total of 288,267 and 288,133 prescriptions orders were reviewed in the 2 stages respectively. A total of 12 DDI and 37 allergy alerts were deactivated in stage 2. Redesign of the alerts reduced the trigger rate of allergy alerts (4.96% to 3.77%, P < 0.0001) and DDI alerts (5.30% to 4.73%, P < 0.0001). A statistically significant reduction in the number of incidents with reported patients’ harm related to overrides of alerts was observed in the post intervention phase. The allergy alert trigger rate was reduced from 4.96% to 3.77%, P = 0.0172. Conclusion: The study demonstrated that using an evidence-based approach and a risk assessment matrix to deactivate non-clinically significant alerts