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Dahmke H, Cabrera-Diaz F, Heizmann M, Stoop S, Schuetz P, Fiumefreddo R, Zaugg C. Development and validation of a clinical decision support system to prevent anticoagulant duplications. Int J Med Inform 2024; 187:105446. [PMID: 38669733 DOI: 10.1016/j.ijmedinf.2024.105446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 03/28/2024] [Accepted: 04/04/2024] [Indexed: 04/28/2024]
Abstract
BACKGROUND AND OBJECTIVE Unintended duplicate prescriptions of anticoagulants increase the risk of serious adverse events. Clinical Decision Support Systems (CDSSs) can help prevent such medication errors; however, sophisticated algorithms are needed to avoid alert fatigue. This article describes the steps taken in our hospital to develop a CDSS to prevent anticoagulant duplication (AD). METHODS The project was composed of three phases. In phase I, the status quo was established. In phase II, a clinical pharmacist developed an algorithm to detect ADs using daily data exports. In phase III, the algorithm was integrated into the hospital's electronic health record system. Alerts were reviewed by clinical pharmacists before being sent to the prescribing physician. We conducted a retrospective analysis of all three phases to assess the impact of the interventions on the occurrence and duration of ADs. Phase III was analyzed in more detail regarding the acceptance rate, sensitivity, and specificity of the alerts. RESULTS We identified 91 ADs in 1581 patients receiving two or more anticoagulants during phase I, 70 ADs in 1692 patients in phase II, and 57 ADs in 1575 patients in phase III. Mean durations of ADs were 1.8, 1.4, and 1.1 calendar days during phases I, II, and III, respectively. In comparison to the baseline in phase I, the relative risk reduction of AD in patients treated with at least two different anticoagulants during phase III was 42% (RR: 0.58, CI: 0.42-0.81). A total of 429 alerts were generated during phase III, many of which were self-limiting, and 186 alerts were sent to the respective prescribing physician. The acceptance rate was high at 97%. We calculated a sensitivity of 87.4% and a specificity of 87.9%. CONCLUSION The stepwise development of a CDSS for the detection of AD markedly reduced the frequency and duration of medication errors in our hospital, thereby improving patient safety.
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Affiliation(s)
- Hendrike Dahmke
- Hospital Pharmacy, Kantonsspital Aarau, 5000 Aarau, Switzerland.
| | | | - Marc Heizmann
- Division of Oncology, Haematology and Transfusion Medicine, Kantonsspital Aarau, Aarau, Switzerland
| | - Sophie Stoop
- Department of Chemistry and Applied Biosciences, Eidgenossische Technische Hochschule Zürich, Zurich, Switzerland
| | - Philipp Schuetz
- Department of Internal Medicine, Kantonsspital Aarau, 5000 Aarau, Switzerland
| | - Rico Fiumefreddo
- Department of Internal Medicine, Kantonsspital Aarau, 5000 Aarau, Switzerland
| | - Claudia Zaugg
- Hospital Pharmacy, Kantonsspital Aarau, 5000 Aarau, Switzerland
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Austin JA, Barras M, Woods LS, Sullivan C. AIDH Summit 2022 - The effect of digitisation on the safe management of anticoagulants. Appl Clin Inform 2022; 13:845-856. [PMID: 35896507 PMCID: PMC9474267 DOI: 10.1055/a-1910-4339] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
Abstract
BACKGROUND Anticoagulants are high-risk medications and are a common cause of adverse events of hospitalised inpatients. The incidence of adverse events involving anticoagulants has remained relatively unchanged over the past two decades, suggesting novel approaches are required to address this persistent issue. Electronic medication management systems (eMMS) offer strategies to help reduce medication incidents and adverse drug events, yet poor system design can introduce new error types. OBJECTIVE To evaluate the effect of the introduction of an electronic medical record (EMR) on the quality and safety of therapeutic anticoagulation management. METHODS A retrospective, observational pre/post study was conducted, analysing real-world data across five hospital sites in a single health service. Four metrics were compared one year pre- and one year post-EMR implementation. They included clinician-reported medication incidents, toxic pathology results, hospital-acquired bleeding complications (HACs) and rate of heparin-induced thrombocytopenia. Further sub-analyses of patients experiencing HACs in the post-EMR period, identified key opportunities for intervention to maximise safety and quality of anticoagulation within an eMMS. RESULTS A significant reduction in HACs was observed in the post-EMR implementation period (mean (SD) =12.1 (4.4)/month, vs. mean (SD) =7.8 (3.5)/month; p=0.01). The categorisation of potential EMR design enhancements found that new automated clinical decision support or improved pathology result integration would be suitable to mitigate future HACs in an eMMS. There was no significant difference in the mean monthly clinician-reported incident rates for anticoagulants or the rate of toxic pathology results in the pre- versus post-EMR implementation period. A 62.5% reduction in the cases of heparin-induced thrombocytopenia were observed in the post-EMR implementation period. CONCLUSION The implementation of an EMR improves clinical care outcomes for patients receiving anticoagulation. System design plays a significant role in mitigating the risks associated with anticoagulants and consideration must be given to optimising eMMS.
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Affiliation(s)
- Jodie Ann Austin
- Centre for Health Services Research, The University of Queensland Faculty of Medicine, Herston, Australia
| | - Michael Barras
- School of Pharmacy, The University of Queensland Faculty of Health and Behavioural Sciences, Woolloongabba, Australia.,Department of Pharmacy, Princess Alexandra Hospital, Woolloongabba, Australia
| | - Leanna Sarah Woods
- Centre for Health Services Research, The University of Queensland, Herston, Australia.,Digital Health Cooperative Research Centre, Sydney, Australia
| | - Clair Sullivan
- Centre for Health Services Research, The University of Queensland Faculty of Medicine, Herston, Australia.,Digital Metro North, Royal Brisbane and Women's Hospital, Herston, Australia
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Curtis HJ, MacKenna B, Walker AJ, Croker R, Mehrkar A, Morton C, Bacon S, Hickman G, Inglesby P, Bates C, Evans D, Ward T, Cockburn J, Davy S, Bhaskaran K, Schultze A, Rentsch CT, Williamson E, Hulme W, Tomlinson L, Mathur R, Drysdale H, Eggo RM, Wong AY, Forbes H, Parry J, Hester F, Harper S, Douglas I, Smeeth L, Goldacre B. OpenSAFELY: impact of national guidance on switching anticoagulant therapy during COVID-19 pandemic. Open Heart 2021; 8:e001784. [PMID: 34785588 PMCID: PMC8595296 DOI: 10.1136/openhrt-2021-001784] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 10/08/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Early in the COVID-19 pandemic, the National Health Service (NHS) recommended that appropriate patients anticoagulated with warfarin should be switched to direct-acting oral anticoagulants (DOACs), requiring less frequent blood testing. Subsequently, a national safety alert was issued regarding patients being inappropriately coprescribed two anticoagulants following a medication change and associated monitoring. OBJECTIVE To describe which people were switched from warfarin to DOACs; identify potentially unsafe coprescribing of anticoagulants; and assess whether abnormal clotting results have become more frequent during the pandemic. METHODS With the approval of NHS England, we conducted a cohort study using routine clinical data from 24 million NHS patients in England. RESULTS 20 000 of 164 000 warfarin patients (12.2%) switched to DOACs between March and May 2020, most commonly to edoxaban and apixaban. Factors associated with switching included: older age, recent renal function test, higher number of recent INR tests recorded, atrial fibrillation diagnosis and care home residency. There was a sharp rise in coprescribing of warfarin and DOACs from typically 50-100 per month to 246 in April 2020, 0.06% of all people receiving a DOAC or warfarin. International normalised ratio (INR) testing fell by 14% to 506.8 patients tested per 1000 warfarin patients each month. We observed a very small increase in elevated INRs (n=470) during April compared with January (n=420). CONCLUSIONS Increased switching of anticoagulants from warfarin to DOACs was observed at the outset of the COVID-19 pandemic in England following national guidance. There was a small but substantial number of people coprescribed warfarin and DOACs during this period. Despite a national safety alert on the issue, a widespread rise in elevated INR test results was not found. Primary care has responded rapidly to changes in patient care during the COVID-19 pandemic.
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Affiliation(s)
- Helen J Curtis
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Brian MacKenna
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Alex J Walker
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Richard Croker
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Amir Mehrkar
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Caroline Morton
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Seb Bacon
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - George Hickman
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Peter Inglesby
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | | | - David Evans
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Tom Ward
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | | | - Simon Davy
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Krishnan Bhaskaran
- Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Anna Schultze
- Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Christopher T Rentsch
- Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Elizabeth Williamson
- Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK
| | - William Hulme
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Laurie Tomlinson
- Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Rohini Mathur
- Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Henry Drysdale
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Rosalind M Eggo
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Angel Yun Wong
- Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Harriet Forbes
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | | | | | - Ian Douglas
- Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Liam Smeeth
- Department of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Ben Goldacre
- The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
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