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Development and assessment of PharmaCheck: an electronic screening tool for the prevention of twenty major adverse drug events
BACKGROUND: Adverse drug events (ADEs) can be prevented by deploying clinical decision support systems (CDSS) that directly assist physicians, via computerized order entry systems, and clinical pharmacists performing medication reviews as part of medical rounds. However, physicians using CDSS are kn...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9154036/ https://www.ncbi.nlm.nih.gov/pubmed/35642053 http://dx.doi.org/10.1186/s12911-022-01885-8 |
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author | Skalafouris, Christian Reny, Jean-Luc Stirnemann, Jérôme Grosgurin, Olivier Eggimann, François Grauser, Damien Teixeira, Daniel Jermini, Megane Bruggmann, Christel Bonnabry, Pascal Guignard, Bertrand |
author_facet | Skalafouris, Christian Reny, Jean-Luc Stirnemann, Jérôme Grosgurin, Olivier Eggimann, François Grauser, Damien Teixeira, Daniel Jermini, Megane Bruggmann, Christel Bonnabry, Pascal Guignard, Bertrand |
author_sort | Skalafouris, Christian |
collection | PubMed |
description | BACKGROUND: Adverse drug events (ADEs) can be prevented by deploying clinical decision support systems (CDSS) that directly assist physicians, via computerized order entry systems, and clinical pharmacists performing medication reviews as part of medical rounds. However, physicians using CDSS are known to be exposed to the alert-fatigue phenomenon. Our study aimed to assess the performance of PharmaCheck—a CDSS to help clinical pharmacists detect high-risk situations with the potential to lead to ADEs—and its impact on clinical pharmacists’ activities. METHODS: Twenty clinical rules, divided into four risk classes, were set for the daily screening of high-risk situations in the electronic health records of patients admitted to our General Internal Medicine Department. Alerts to clinical pharmacists encouraged them to telephone prescribers and suggest any necessary treatment adjustments. PharmaCheck’s performance was assessed using the intervention’s positive predictive value (PPV), which characterizes the proportion of interventions for each alert triggered. PharmaCheck’s impact was assessed by considering clinical pharmacists as a filter for ruling out futile alerts and by comparing the final clinical PPV with a pharmacist (the proportion of interventions that led to a change in the medical regimen) to the final clinical PPV without a pharmacist. RESULTS: Over 132 days, 447 alerts were triggered for 383 patients, leading to 90 interventions (overall intervention PPV = 20.1%). By risk class, intervention PPVs made up 26.9% (n = 65/242) of abnormal laboratory value alerts, 3.1% (4/127) of alerts for contraindicated medications or medications to be used with caution, 28.2% (20/71) of drug–drug interaction alerts, and 14.3% (1/7) of inadequate mode of administration alerts. Clinical PPVs reached 71.0% (64/90) when pharmacists filtered alerts and 14% (64/242) if they were not doing it. CONCLUSION: PharmaCheck enabled clinical pharmacists to improve their traditional processes and broaden their coverage by focusing on 20 high-risk situations. Alert management by pharmacists seemed to be a more effective way of preventing risky situations and alert-fatigue than a model addressing alerts to physicians exclusively. Some fine-tuning could enhance PharmaCheck's performance by considering the information quality of triggers, the variability of clinical settings, and the fact that some prescription processes are already highly secured. |
format | Online Article Text |
id | pubmed-9154036 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-91540362022-06-02 Development and assessment of PharmaCheck: an electronic screening tool for the prevention of twenty major adverse drug events Skalafouris, Christian Reny, Jean-Luc Stirnemann, Jérôme Grosgurin, Olivier Eggimann, François Grauser, Damien Teixeira, Daniel Jermini, Megane Bruggmann, Christel Bonnabry, Pascal Guignard, Bertrand BMC Med Inform Decis Mak Research BACKGROUND: Adverse drug events (ADEs) can be prevented by deploying clinical decision support systems (CDSS) that directly assist physicians, via computerized order entry systems, and clinical pharmacists performing medication reviews as part of medical rounds. However, physicians using CDSS are known to be exposed to the alert-fatigue phenomenon. Our study aimed to assess the performance of PharmaCheck—a CDSS to help clinical pharmacists detect high-risk situations with the potential to lead to ADEs—and its impact on clinical pharmacists’ activities. METHODS: Twenty clinical rules, divided into four risk classes, were set for the daily screening of high-risk situations in the electronic health records of patients admitted to our General Internal Medicine Department. Alerts to clinical pharmacists encouraged them to telephone prescribers and suggest any necessary treatment adjustments. PharmaCheck’s performance was assessed using the intervention’s positive predictive value (PPV), which characterizes the proportion of interventions for each alert triggered. PharmaCheck’s impact was assessed by considering clinical pharmacists as a filter for ruling out futile alerts and by comparing the final clinical PPV with a pharmacist (the proportion of interventions that led to a change in the medical regimen) to the final clinical PPV without a pharmacist. RESULTS: Over 132 days, 447 alerts were triggered for 383 patients, leading to 90 interventions (overall intervention PPV = 20.1%). By risk class, intervention PPVs made up 26.9% (n = 65/242) of abnormal laboratory value alerts, 3.1% (4/127) of alerts for contraindicated medications or medications to be used with caution, 28.2% (20/71) of drug–drug interaction alerts, and 14.3% (1/7) of inadequate mode of administration alerts. Clinical PPVs reached 71.0% (64/90) when pharmacists filtered alerts and 14% (64/242) if they were not doing it. CONCLUSION: PharmaCheck enabled clinical pharmacists to improve their traditional processes and broaden their coverage by focusing on 20 high-risk situations. Alert management by pharmacists seemed to be a more effective way of preventing risky situations and alert-fatigue than a model addressing alerts to physicians exclusively. Some fine-tuning could enhance PharmaCheck's performance by considering the information quality of triggers, the variability of clinical settings, and the fact that some prescription processes are already highly secured. BioMed Central 2022-05-31 /pmc/articles/PMC9154036/ /pubmed/35642053 http://dx.doi.org/10.1186/s12911-022-01885-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Skalafouris, Christian Reny, Jean-Luc Stirnemann, Jérôme Grosgurin, Olivier Eggimann, François Grauser, Damien Teixeira, Daniel Jermini, Megane Bruggmann, Christel Bonnabry, Pascal Guignard, Bertrand Development and assessment of PharmaCheck: an electronic screening tool for the prevention of twenty major adverse drug events |
title | Development and assessment of PharmaCheck: an electronic screening tool for the prevention of twenty major adverse drug events |
title_full | Development and assessment of PharmaCheck: an electronic screening tool for the prevention of twenty major adverse drug events |
title_fullStr | Development and assessment of PharmaCheck: an electronic screening tool for the prevention of twenty major adverse drug events |
title_full_unstemmed | Development and assessment of PharmaCheck: an electronic screening tool for the prevention of twenty major adverse drug events |
title_short | Development and assessment of PharmaCheck: an electronic screening tool for the prevention of twenty major adverse drug events |
title_sort | development and assessment of pharmacheck: an electronic screening tool for the prevention of twenty major adverse drug events |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9154036/ https://www.ncbi.nlm.nih.gov/pubmed/35642053 http://dx.doi.org/10.1186/s12911-022-01885-8 |
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