This paper is in the following e-collection/theme issue:

Decision Support for Health Professionals (1210) JMIR Theme Issue: COVID-19 Special Issue (2461) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520) Outbreak and Pandemic Preparedness and Management (1743) Infectious Diseases (non-STD/STI) (1592) Clinical Information and Decision Making (1434) Clinical Informatics (1050) eHealth Infrastructures (357) Medication Adherence (90)

Published on in Vol 9, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30743, first published .
Implementation of an Anticoagulation Practice Guideline for COVID-19 via a Clinical Decision Support System in a Large Academic Health System and Its Evaluation: Observational Study

Implementation of an Anticoagulation Practice Guideline for COVID-19 via a Clinical Decision Support System in a Large Academic Health System and Its Evaluation: Observational Study

Implementation of an Anticoagulation Practice Guideline for COVID-19 via a Clinical Decision Support System in a Large Academic Health System and Its Evaluation: Observational Study

Authors of this article:

Surbhi Shah1 Author Orcid Image ;   Sean Switzer1 Author Orcid Image ;   Nathan D Shippee1 Author Orcid Image ;   Pamela Wogensen2 Author Orcid Image ;   Kathryn Kosednar2 Author Orcid Image ;   Emma Jones3 Author Orcid Image ;   Deborah L Pestka4 Author Orcid Image ;   Sameer Badlani2 Author Orcid Image ;   Mary Butler5 Author Orcid Image ;   Brittin Wagner5 Author Orcid Image ;   Katie White5 Author Orcid Image ;   Joshua Rhein6 Author Orcid Image ;   Bradley Benson6 Author Orcid Image ;   Mark Reding6 Author Orcid Image ;   Michael Usher6 Author Orcid Image ;   Genevieve B Melton3 Author Orcid Image ;   Christopher James Tignanelli3 Author Orcid Image
Article Authors Cited by (6) Tweetations (3) Metrics

Journals

  1. Cross D, Pestka D, White K, Shah S. Business Not As Usual. Mayo Clinic Proceedings: Innovations, Quality & Outcomes 2021;5(6):1008 View
  2. Rosario B, Zhang A, Patel M, Rajmane A, Xie N, Weeraratne D, Alterovitz G. Characterizing Thrombotic Complication Risk Factors Associated With COVID-19 via Heterogeneous Patient Data: Retrospective Observational Study. Journal of Medical Internet Research 2022;24(10):e35860 View
  3. Mlakar I, Smrke U, Flis V, Bergauer A, Kobilica N, Kampič T, Horvat S, Vidovič D, Musil B, Plohl N. A randomized controlled trial for evaluating the impact of integrating a computerized clinical decision support system and a socially assistive humanoid robot into grand rounds during pre/post-operative care. DIGITAL HEALTH 2022;8:205520762211290 View
  4. Vazquez S, Yates N, Beavers C, Triller D, McFarland M. Differences in quality of anticoagulation care delivery according to ethnoracial group in the United States: A scoping review. Journal of Thrombosis and Thrombolysis 2024;57(6):1076 View
  5. Tignanelli C, Shah S, Vock D, Siegel L, Serrano C, Haut E, Switzer S, Martin C, Rizvi R, Peta V, Jenkins P, Lemke N, Thyvalikakath T, Osheroff J, Torres D, Vawdrey D, Callcut R, Butler M, Melton G. A pragmatic, stepped-wedge, hybrid type II trial of interoperable clinical decision support to improve venous thromboembolism prophylaxis for patients with traumatic brain injury. Implementation Science 2024;19(1) View
  6. Wohlgemut J, Pisirir E, Stoner R, Perkins Z, Marsh W, Tai N, Kyrimi E. A scoping review, novel taxonomy and catalogue of implementation frameworks for clinical decision support systems. BMC Medical Informatics and Decision Making 2024;24(1) View