PDF herunterladen
CC BY 4.0 · ACI open 2021; 05(02): e116-e124
DOI: 10.1055/s-0041-1736631
Case Report

Safe and Effective Digital Anticoagulation: A Continuous Iterative Improvement Approach

Jodie A. Austin
1   Faculty of Medicine, University of Queensland, Brisbane, Australia
2   Digital Application Services ieMR, eHealth Queensland, Brisbane, Australia
,
Michael A. Barras
3   The School of Pharmacy, University of Queensland, Brisbane, Australia
4   Department of Pharmacy, Princess Alexandra Hospital, Brisbane, Australia
,
Clair M. Sullivan
1   Faculty of Medicine, University of Queensland, Brisbane, Australia
5   Metro North Hospital and Health Service, Brisbane, Australia
› Institutsangaben Funding This research was supported by the Digital Health CRC through grant (STARS 0034).
› Weitere Informationen
   Lizenzen und Reprints

Abstract

Background Anticoagulant drugs are the leading cause of medication harm in hospitals and prescribing errors are common with traditional paper prescriptions. Electronic medicines management can reduce prescribing errors for many drugs; however, little is known about the impact of e-prescribing on anticoagulants. Our case study reports on the lessons learned during conversion from paper to e-prescribing and the ongoing optimization process.

Methods The iterative implementation of an anticoagulant prescribing platform in an integrated electronic medical record (ieMR) and ongoing continuous enhancements was applied across five digital hospital sites utilizing a single domain. The collaborative management of each class of anticoagulant, optimization strategies, governance structures, and lessons learned is described. An analysis of the rate of errors and adverse events pre- and post-go live is presented.

Results The transition to e-prescribing relied on a strong inter-disciplinary governance framework to promote the safe management of anticoagulants. There was no increase in overall prescribing errors, however unfamiliarity with the new system caused a transient increase in errors with unfractionated heparin (1.8/month pre-ieMR vs. 5.5/month post-ieMR). A dedicated real-time surveillance dashboard was introduced. The iterative nature of changes indicated the complexities involved with anticoagulants and the need for an interactive, optimization approach. This led to a significant decrease in anticoagulant related hospital acquired complications (12.1/month pre-ieMR vs. 7.8/month post-ieMR, p = 0.01).

Conclusion Digitizing anticoagulant prescribing led to an overall reduction in errors, but a continuous iterative optimization approach was needed to achieve this outcome. The knowledge presented can help inform optimal therapeutic anticoagulation ieMR design strategies.

Keywords

electronic medical record - clinical decision support - order entry - medication management - iterative improvement - anticoagulation

Protection of Human and Animal Subjects

Ethics approval was sought and granted to publish this case report by the organization's Human Research Ethics Committee (Ref: LNR/2020/QMS/61139) on February 18, 2020 for low/negligible-risk research involving humans.




Publikationsverlauf

Eingereicht: 18. September 2020

Angenommen: 08. September 2021

Artikel online veröffentlicht:
15. November 2021

© 2021. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Analytics HIMSS. Stage 6 & 7 Achievement. 2017. Accessed April 05, 2021 at: https://www.himssanalytics.org/stage-6-7-achievement
    PubMedGoogle Scholar
  • 2 Keasberry J, Scott IA, Sullivan C, Staib A, Ashby R. Going digital: a narrative overview of the clinical and organisational impacts of eHealth technologies in hospital practice. Aust Health Rev 2017; 41 (06) 646-664
    CrossrefPubMedGoogle Scholar
  • 3 Australian Commission on Safety and Quality in Health Care. High risk medicines. 2019. Accessed April 05, 2020 at: https://www.safetyandquality.gov.au/our-work/medication-safety/high-risk-medicines/
    PubMedGoogle Scholar
  • 4 Institute for Safe Medication Practices. High-alert medications in acute care settings. 2020. Accessed April 05, 2020 at: https://www.ismp.org/recommendations/high-alert-medications-acute-list
    PubMedGoogle Scholar
  • 5 The Joint Commission. Sentinel Event Alert: Preventing errors relating to commonly used anticoagulants. 2008. Accessed April 05, 2020 at: https://www.jointcommission.org/assets/1/18/SEA_41.pdf
    PubMedGoogle Scholar
  • 6 Sennesael AL, Larock AS, Devalet B. et al. Preventability of serious thromboembolic and bleeding events related to the use of oral anticoagulants: a prospective study. Br J Clin Pharmacol 2018; 84 (07) 1544-1556
    CrossrefPubMedGoogle Scholar
  • 7 Dager WE, Ansell J, Barnes GD. et al. “Reduce the Likelihood of Patient Harm Associated with the Use of Anticoagulant Therapy”: Commentary from the Anticoagulation Forum on the Updated Joint Commission NPSG.03.05.01 Elements of Performance. Jt Comm J Qual Patient Saf 2020; 46 (03) 173-180
    PubMedGoogle Scholar
  • 8 Budnitz DS, Lovegrove MC, Shehab N, Richards CL. Emergency hospitalizations for adverse drug events in older Americans. N Engl J Med 2011; 365 (21) 2002-2012
    CrossrefPubMedGoogle Scholar
  • 9 Dreijer AR, Diepstraten J, Bukkems VE. et al. Anticoagulant medication errors in hospitals and primary care: a cross-sectional study. Int J Qual Health Care 2019; 31 (05) 346-352
    CrossrefPubMedGoogle Scholar
  • 10 Henriksen JN, Nielsen LP, Hellebek A, Poulsen BK. Medication errors involving anticoagulants: data from the Danish patient safety database. Pharmacol Res Perspect 2017; 5 (03) e00307
    CrossrefPubMedGoogle Scholar
  • 11 Queensland Government. Digital Projects Dashboard [cited November 26, 2020]. Available at: https://www.qld.gov.au/digitalprojectsdashboard/projects?offset=1
    PubMedGoogle Scholar
  • 12 Jones SS, Heaton P, Friedberg MW, Schneider EC. Today's ‘meaningful use’ standard for medication orders by hospitals may save few lives; later stages may do more. Health Aff (Millwood) 2011; 30 (10) 2005-2012
    CrossrefPubMedGoogle Scholar
  • 13 Schiff GD, Amato MG, Eguale T. et al. Computerised physician order entry-related medication errors: analysis of reported errors and vulnerability testing of current systems. BMJ Qual Saf 2015; 24 (04) 264-271
    CrossrefPubMedGoogle Scholar
  • 14 Austin J, Barras M, Sullivan C. Interventions designed to improve the safety and quality of therapeutic anticoagulation in an inpatient electronic medical record. Int J Med Inform 2020; 135: 104066
    CrossrefPubMedGoogle Scholar
  • 15 Barnett A, Winning M, Canaris S, Cleary M, Staib A, Sullivan C. Digital transformation of hospital quality and safety: real-time data for real-time action. Aust Health Rev 2019; 43 (06) 656-661
    CrossrefPubMedGoogle Scholar
  • 16 Leach H. National inpatient medication chart implementation. J Pharm Pract Res 2006; 36 (01) 6-7
    CrossrefPubMedGoogle Scholar
  • 17 Melton BL, Zillich AJ, Saleem J, Russ AL, Tisdale JE, Overholser BR. Iterative development and evaluation of a pharmacogenomic-guided clinical decision support system for warfarin dosing. Appl Clin Inform 2016; 7 (04) 1088-1106
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 18 Dekker KR, Myers BL, Barras MA. Compliance with enoxaparin dosing and monitoring guidelines and the impact on patient length of stay: a pilot study. Ther Drug Monit 2016; 38 (01) 59-63
    CrossrefPubMedGoogle Scholar
  • 19 Pattullo CS, Barras M, Tai B, McKean M, Donovan P. New oral anticoagulants: appropriateness of prescribing in real-world setting. Intern Med J 2016; 46 (07) 812-818
    CrossrefPubMedGoogle Scholar
  • 20 Lim W, Dentali F, Eikelboom JW, Crowther MA. Meta-analysis: low-molecular-weight heparin and bleeding in patients with severe renal insufficiency. Ann Intern Med 2006; 144 (09) 673-684
    CrossrefPubMedGoogle Scholar
  • 21 Tran H, Joseph J, Young L. et al; Australasian Society of Thrombosis and Haemostasis. New oral anticoagulants: a practical guide on prescription, laboratory testing and peri-procedural/bleeding management. Intern Med J 2014; 44 (06) 525-536
    CrossrefPubMedGoogle Scholar
  • 22 Garber A, Nowacki AS, Chaitoff A. et al. Frequency, timing, and types of medication ordering errors made by residents in the electronic medical records era. South Med J 2019; 112 (01) 25-31
    CrossrefPubMedGoogle Scholar
  • 23 Ibáñez-Garcia S, Rodriguez-Gonzalez C, Escudero-Vilaplana V. et al. Development and evaluation of a clinical decision support system to improve medication safety. Appl Clin Inform 2019; 10 (03) 513-520
    Artikel in Thieme ConnectPubMedGoogle Scholar
  • 24 Waitman LR, Phillips IE, McCoy AB. et al. Adopting real-time surveillance dashboards as a component of an enterprisewide medication safety strategy. Jt Comm J Qual Patient Saf 2011; 37 (07) 326-332
    PubMedGoogle Scholar
  • 25 Su L, Liu C, Li D. et al. Toward optimal heparin dosing by comparing multiple machine learning methods: retrospective study. JMIR Med Inform 2020; 8 (06) e17648
    CrossrefPubMedGoogle Scholar
  • 26 Sennesael AL, Krug B, Sneyers B, Spinewine A. Do computerized clinical decision support systems improve the prescribing of oral anticoagulants? A systematic review. Thromb Res 2020; 187: 79-87
    CrossrefPubMedGoogle Scholar