O. Urbina, P. Martín, Martinez, A. L. D. Torre, C. Blanco, Y. Llorens
{"title":"4CPS-370药师使用临床决策支持工具检测药物相关问题前后的干预措施","authors":"O. Urbina, P. Martín, Martinez, A. L. D. Torre, C. Blanco, Y. Llorens","doi":"10.1136/EJHPHARM-2021-EAHPCONF.202","DOIUrl":null,"url":null,"abstract":"Background and importance Drug related problems (DRP) and medication adverse events occur in hospitalised patients. Computer provider order entry (CPOE) systems with clinical decision support systems (CDSS) are a key process for the pharmacist’s routine prescription validation to improve medication prescribing and patient safety. Aim and objectives To evaluate the type and number of pharmacist interventions (PI) before and after the use of a CDSS tool added to the CPOE system. Material and methods A retrospective observational study was carried out in a 300 bed hospital between January 2019 and May 2020. Data collected were: DRG type, PI and detection method. First period (January–August 2019): pharmacist validation using CPOE and electronic health records (EHR) was performed. The CDSS was introduced in August 2019. The CDSS includes drug information related to dose adjustment according to renal function, monitoring of analytic parameters susceptible to being altered by the drug, and drug–drug/drug–food interactions that are continuously updated by pharmacists. When EHR and CPOE containing demographic, anthropometric and clinical data of the patient as well as pharmacological treatment are integrated with the CDSS, alerts are generated (potential DRP) in real time that are evaluated by pharmacists. When the alerts are considered relevant, pharmacists write a PI in the patient’s chart. Second period (August 2019 –May 2020): CDSS alerts were available for prescription validation. Results First period: 1574 PI. Second period: 1687 PI (1451 using the first period method and 236 using the CDSS alerts). PI as a result of the CDSS were about 14% of total PI, and their type and number comparing both periods are presented in table 1. Conclusion and relevance The number of PI made in the two periods was similar but the CDSS tool allowed pharmacists to detect certain types of DRP that use of the CPOE alone did not allow. Moreover, the use of this tool optimised the pharmacist’s medical prescription review time and facilitated the PI registration task. To increase the usefulness of the CDSS it is necessary to increase the number of relevant alerts introduced in this application. References and/or acknowledgements None. Conflict of interest No conflict of interest","PeriodicalId":11998,"journal":{"name":"European Journal of Hospital Pharmacy","volume":"61 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"4CPS-370 Pharmacists’ interventions before and after the use of a clinical decision support tool to detect drug related problems\",\"authors\":\"O. Urbina, P. Martín, Martinez, A. L. D. Torre, C. Blanco, Y. Llorens\",\"doi\":\"10.1136/EJHPHARM-2021-EAHPCONF.202\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background and importance Drug related problems (DRP) and medication adverse events occur in hospitalised patients. Computer provider order entry (CPOE) systems with clinical decision support systems (CDSS) are a key process for the pharmacist’s routine prescription validation to improve medication prescribing and patient safety. Aim and objectives To evaluate the type and number of pharmacist interventions (PI) before and after the use of a CDSS tool added to the CPOE system. Material and methods A retrospective observational study was carried out in a 300 bed hospital between January 2019 and May 2020. Data collected were: DRG type, PI and detection method. First period (January–August 2019): pharmacist validation using CPOE and electronic health records (EHR) was performed. The CDSS was introduced in August 2019. The CDSS includes drug information related to dose adjustment according to renal function, monitoring of analytic parameters susceptible to being altered by the drug, and drug–drug/drug–food interactions that are continuously updated by pharmacists. When EHR and CPOE containing demographic, anthropometric and clinical data of the patient as well as pharmacological treatment are integrated with the CDSS, alerts are generated (potential DRP) in real time that are evaluated by pharmacists. When the alerts are considered relevant, pharmacists write a PI in the patient’s chart. Second period (August 2019 –May 2020): CDSS alerts were available for prescription validation. Results First period: 1574 PI. Second period: 1687 PI (1451 using the first period method and 236 using the CDSS alerts). PI as a result of the CDSS were about 14% of total PI, and their type and number comparing both periods are presented in table 1. Conclusion and relevance The number of PI made in the two periods was similar but the CDSS tool allowed pharmacists to detect certain types of DRP that use of the CPOE alone did not allow. Moreover, the use of this tool optimised the pharmacist’s medical prescription review time and facilitated the PI registration task. To increase the usefulness of the CDSS it is necessary to increase the number of relevant alerts introduced in this application. References and/or acknowledgements None. Conflict of interest No conflict of interest\",\"PeriodicalId\":11998,\"journal\":{\"name\":\"European Journal of Hospital Pharmacy\",\"volume\":\"61 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Hospital Pharmacy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1136/EJHPHARM-2021-EAHPCONF.202\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Hospital Pharmacy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1136/EJHPHARM-2021-EAHPCONF.202","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
4CPS-370 Pharmacists’ interventions before and after the use of a clinical decision support tool to detect drug related problems
Background and importance Drug related problems (DRP) and medication adverse events occur in hospitalised patients. Computer provider order entry (CPOE) systems with clinical decision support systems (CDSS) are a key process for the pharmacist’s routine prescription validation to improve medication prescribing and patient safety. Aim and objectives To evaluate the type and number of pharmacist interventions (PI) before and after the use of a CDSS tool added to the CPOE system. Material and methods A retrospective observational study was carried out in a 300 bed hospital between January 2019 and May 2020. Data collected were: DRG type, PI and detection method. First period (January–August 2019): pharmacist validation using CPOE and electronic health records (EHR) was performed. The CDSS was introduced in August 2019. The CDSS includes drug information related to dose adjustment according to renal function, monitoring of analytic parameters susceptible to being altered by the drug, and drug–drug/drug–food interactions that are continuously updated by pharmacists. When EHR and CPOE containing demographic, anthropometric and clinical data of the patient as well as pharmacological treatment are integrated with the CDSS, alerts are generated (potential DRP) in real time that are evaluated by pharmacists. When the alerts are considered relevant, pharmacists write a PI in the patient’s chart. Second period (August 2019 –May 2020): CDSS alerts were available for prescription validation. Results First period: 1574 PI. Second period: 1687 PI (1451 using the first period method and 236 using the CDSS alerts). PI as a result of the CDSS were about 14% of total PI, and their type and number comparing both periods are presented in table 1. Conclusion and relevance The number of PI made in the two periods was similar but the CDSS tool allowed pharmacists to detect certain types of DRP that use of the CPOE alone did not allow. Moreover, the use of this tool optimised the pharmacist’s medical prescription review time and facilitated the PI registration task. To increase the usefulness of the CDSS it is necessary to increase the number of relevant alerts introduced in this application. References and/or acknowledgements None. Conflict of interest No conflict of interest