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      OntoPharma: ontology based clinical decision support system to reduce medication prescribing errors

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          Abstract

          Background

          Clinical decision support systems (CDSS) have been shown to reduce medication errors. However, they are underused because of different challenges. One approach to improve CDSS is to use ontologies instead of relational databases. The primary aim was to design and develop OntoPharma, an ontology based CDSS to reduce medication prescribing errors. Secondary aim was to implement OntoPharma in a hospital setting.

          Methods

          A four-step process was proposed. (1) Defining the ontology domain. The ontology scope was the medication domain. An advisory board selected four use cases: maximum dosage alert, drug-drug interaction checker, renal failure adjustment, and drug allergy checker. (2) Implementing the ontology in a formal representation. The implementation was conducted by Medical Informatics specialists and Clinical Pharmacists using Protégé-OWL. (3) Developing an ontology-driven alert module. Computerised Physician Order Entry (CPOE) integration was performed through a REST API. SPARQL was used to query ontologies. (4) Implementing OntoPharma in a hospital setting. Alerts generated between July 2020/ November 2021 were analysed.

          Results

          The three ontologies developed included 34,938 classes, 16,672 individuals and 82 properties. The domains addressed by ontologies were identification data of medicinal products, appropriateness drug data, and local concepts from CPOE. When a medication prescribing error is identified an alert is shown. OntoPharma generated 823 alerts in 1046 patients. 401 (48.7%) of them were accepted.

          Conclusions

          OntoPharma is an ontology based CDSS implemented in clinical practice which generates alerts when a prescribing medication error is identified. To gain user acceptance OntoPharma has been designed and developed by a multidisciplinary team. Compared to CDSS based on relational databases, OntoPharma represents medication knowledge in a more intuitive, extensible and maintainable manner.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12911-022-01979-3.

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          Most cited references41

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          An overview of clinical decision support systems: benefits, risks, and strategies for success

          Computerized clinical decision support systems, or CDSS, represent a paradigm shift in healthcare today. CDSS are used to augment clinicians in their complex decision-making processes. Since their first use in the 1980s, CDSS have seen a rapid evolution. They are now commonly administered through electronic medical records and other computerized clinical workflows, which has been facilitated by increasing global adoption of electronic medical records with advanced capabilities. Despite these advances, there remain unknowns regarding the effect CDSS have on the providers who use them, patient outcomes, and costs. There have been numerous published examples in the past decade(s) of CDSS success stories, but notable setbacks have also shown us that CDSS are not without risks. In this paper, we provide a state-of-the-art overview on the use of clinical decision support systems in medicine, including the different types, current use cases with proven efficacy, common pitfalls, and potential harms. We conclude with evidence-based recommendations for minimizing risk in CDSS design, implementation, evaluation, and maintenance.
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            A translation approach to portable ontology specifications

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              Overriding of drug safety alerts in computerized physician order entry.

              Many computerized physician order entry (CPOE) systems have integrated drug safety alerts. The authors reviewed the literature on physician response to drug safety alerts and interpreted the results using Reason's framework of accident causation. In total, 17 papers met the inclusion criteria. Drug safety alerts are overridden by clinicians in 49% to 96% of cases. Alert overriding may often be justified and adverse drug events due to overridden alerts are not always preventable. A distinction between appropriate and useful alerts should be made. The alerting system may contain error-producing conditions like low specificity, low sensitivity, unclear information content, unnecessary workflow disruptions, and unsafe and inefficient handling. These may result in active failures of the physician, like ignoring alerts, misinterpretation, and incorrect handling. Efforts to improve patient safety by increasing correct handling of drug safety alerts should focus on the error-producing conditions in software and organization. Studies on cognitive processes playing a role in overriding drug safety alerts are lacking.
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                Author and article information

                Contributors
                elcalvo@clinic.cat
                concepcion_camacho@clinic.cat
                ffeu@clinic.cat
                xpastor@clinic.cat
                ccodinajane@gmail.com
                rlozano@clinic.cat
                Journal
                BMC Med Inform Decis Mak
                BMC Med Inform Decis Mak
                BMC Medical Informatics and Decision Making
                BioMed Central (London )
                1472-6947
                10 September 2022
                10 September 2022
                2022
                : 22
                : 238
                Affiliations
                [1 ]GRID grid.410458.c, ISNI 0000 0000 9635 9413, Pharmacy Service, Division of Medicines, , Hospital Clínic of Barcelona, ; 170 Villarroel Street, 08036 Barcelona, Spain
                [2 ]GRID grid.410458.c, ISNI 0000 0000 9635 9413, Division of Medicines, , Hospital Clínic of Barcelona, ; 170 Villarroel Street, 08036 Barcelona, Spain
                [3 ]GRID grid.410458.c, ISNI 0000 0000 9635 9413, Management Team, , Hospital Clínic of Barcelona, ; 170 Villarroel Street, 08036 Barcelona, Spain
                [4 ]GRID grid.410458.c, ISNI 0000 0000 9635 9413, Unit of Medical Informatics, , Hospital Clínic of Barcelona, ; 170 Villarroel Street, 08036 Barcelona, Spain
                Article
                1979
                10.1186/s12911-022-01979-3
                9463735
                36088328
                2592b739-54d9-4d39-8357-d619a74a2ee5
                © The Author(s) 2022

                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/. The Creative Commons Public Domain Dedication waiver ( http://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.

                History
                : 10 May 2022
                : 25 August 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Bioinformatics & Computational biology
                “biological ontologies” [mesh],“decision support systems clinical” [mesh],“medication errors” [mesh],“drug prescriptions” [mesh]

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