Identification of Medication Prescription Errors and Factors of Clinical Relevance in 314 Hospitalized Patients for Improved Multidimensional Clinical Decision Support Algorithms
Potential medication errors and related adverse drug events (ADE) pose major challenges in clinical medicine. Clinical decision support systems (CDSSs) help identify preventable prescription errors leading to ADEs but are typically characterized by high sensitivity and low specificity, resulting in...
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| Format: | Article |
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MDPI AG
2023-07-01
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| Series: | Journal of Clinical Medicine |
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| Online Access: | https://www.mdpi.com/2077-0383/12/15/4920 |
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| author | Stefan Russmann Fabiana Martinelli Franziska Jakobs Manjinder Pannu David F. Niedrig Andrea Michelle Burden Martina Kleber Markus Béchir |
| author_facet | Stefan Russmann Fabiana Martinelli Franziska Jakobs Manjinder Pannu David F. Niedrig Andrea Michelle Burden Martina Kleber Markus Béchir |
| author_sort | Stefan Russmann |
| collection | DOAJ |
| description | Potential medication errors and related adverse drug events (ADE) pose major challenges in clinical medicine. Clinical decision support systems (CDSSs) help identify preventable prescription errors leading to ADEs but are typically characterized by high sensitivity and low specificity, resulting in poor acceptance and alert-overriding. With this cross-sectional study we aimed to analyze CDSS performance, and to identify factors that may increase CDSS specificity. Clinical pharmacology services evaluated current pharmacotherapy of 314 patients during hospitalization across three units of two Swiss tertiary care hospitals. We used two CDSSs (pharmaVISTA and MediQ), primarily for the evaluation of drug-drug interactions (DDI). Additionally, we evaluated potential drug-disease, drug-age, drug-food, and drug-gene interactions. Recommendations for change of therapy were forwarded without delay to treating physicians. Among 314 patients, automated analyses by both CDSSs produced an average of 15.5 alerts per patient. In contrast, additional expert evaluation resulted in only 0.8 recommendations per patient to change pharmacotherapy. For clinical pharmacology experts, co-factors such as comorbidities and laboratory results were decisive for the classification of CDSS alerts as clinically relevant in individual patients in about 70% of all decisions. Such co-factors should therefore be used for the development of multidimensional CDSS alert algorithms with improved specificity. In combination with local expert services, this poses a promising approach to improve drug safety in clinical practice. |
| first_indexed | 2024-03-11T00:24:15Z |
| format | Article |
| id | doaj.art-472fca7ccce6454f9317a1c7c3a745f9 |
| institution | Directory Open Access Journal |
| issn | 2077-0383 |
| language | English |
| last_indexed | 2024-03-11T00:24:15Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Clinical Medicine |
| spelling | doaj.art-472fca7ccce6454f9317a1c7c3a745f92023-11-18T23:06:59ZengMDPI AGJournal of Clinical Medicine2077-03832023-07-011215492010.3390/jcm12154920Identification of Medication Prescription Errors and Factors of Clinical Relevance in 314 Hospitalized Patients for Improved Multidimensional Clinical Decision Support AlgorithmsStefan Russmann0Fabiana Martinelli1Franziska Jakobs2Manjinder Pannu3David F. Niedrig4Andrea Michelle Burden5Martina Kleber6Markus Béchir7Swiss Federal Institute of Technology Zurich (ETHZ), 8093 Zurich, SwitzerlandSwiss Federal Institute of Technology Zurich (ETHZ), 8093 Zurich, SwitzerlandSwiss Federal Institute of Technology Zurich (ETHZ), 8093 Zurich, SwitzerlandFaculty of Medicine, University of Nicosia, 2408 Egkomi, CyprusDrugsafety.ch, Seestrasse 221, 8703 Küsnacht, SwitzerlandSwiss Federal Institute of Technology Zurich (ETHZ), 8093 Zurich, SwitzerlandDepartment of Internal Medicine, Clinic Hirslanden Zurich, 8032 Zurich, SwitzerlandFaculty of Medicine, University of Nicosia, 2408 Egkomi, CyprusPotential medication errors and related adverse drug events (ADE) pose major challenges in clinical medicine. Clinical decision support systems (CDSSs) help identify preventable prescription errors leading to ADEs but are typically characterized by high sensitivity and low specificity, resulting in poor acceptance and alert-overriding. With this cross-sectional study we aimed to analyze CDSS performance, and to identify factors that may increase CDSS specificity. Clinical pharmacology services evaluated current pharmacotherapy of 314 patients during hospitalization across three units of two Swiss tertiary care hospitals. We used two CDSSs (pharmaVISTA and MediQ), primarily for the evaluation of drug-drug interactions (DDI). Additionally, we evaluated potential drug-disease, drug-age, drug-food, and drug-gene interactions. Recommendations for change of therapy were forwarded without delay to treating physicians. Among 314 patients, automated analyses by both CDSSs produced an average of 15.5 alerts per patient. In contrast, additional expert evaluation resulted in only 0.8 recommendations per patient to change pharmacotherapy. For clinical pharmacology experts, co-factors such as comorbidities and laboratory results were decisive for the classification of CDSS alerts as clinically relevant in individual patients in about 70% of all decisions. Such co-factors should therefore be used for the development of multidimensional CDSS alert algorithms with improved specificity. In combination with local expert services, this poses a promising approach to improve drug safety in clinical practice.https://www.mdpi.com/2077-0383/12/15/4920medication errorsadverse drug eventsclinical decision supportclinical medicineclinical pharmacologydrug interactions |
| spellingShingle | Stefan Russmann Fabiana Martinelli Franziska Jakobs Manjinder Pannu David F. Niedrig Andrea Michelle Burden Martina Kleber Markus Béchir Identification of Medication Prescription Errors and Factors of Clinical Relevance in 314 Hospitalized Patients for Improved Multidimensional Clinical Decision Support Algorithms Journal of Clinical Medicine medication errors adverse drug events clinical decision support clinical medicine clinical pharmacology drug interactions |
| title | Identification of Medication Prescription Errors and Factors of Clinical Relevance in 314 Hospitalized Patients for Improved Multidimensional Clinical Decision Support Algorithms |
| title_full | Identification of Medication Prescription Errors and Factors of Clinical Relevance in 314 Hospitalized Patients for Improved Multidimensional Clinical Decision Support Algorithms |
| title_fullStr | Identification of Medication Prescription Errors and Factors of Clinical Relevance in 314 Hospitalized Patients for Improved Multidimensional Clinical Decision Support Algorithms |
| title_full_unstemmed | Identification of Medication Prescription Errors and Factors of Clinical Relevance in 314 Hospitalized Patients for Improved Multidimensional Clinical Decision Support Algorithms |
| title_short | Identification of Medication Prescription Errors and Factors of Clinical Relevance in 314 Hospitalized Patients for Improved Multidimensional Clinical Decision Support Algorithms |
| title_sort | identification of medication prescription errors and factors of clinical relevance in 314 hospitalized patients for improved multidimensional clinical decision support algorithms |
| topic | medication errors adverse drug events clinical decision support clinical medicine clinical pharmacology drug interactions |
| url | https://www.mdpi.com/2077-0383/12/15/4920 |
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