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

Decision Support for Health Professionals (1482) Clinical Information and Decision Making (1824)

Published on in Vol 8, No 1 (2020): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16912, first published .
Accuracy and Effects of Clinical Decision Support Systems Integrated With BMJ Best Practice–Aided Diagnosis: Interrupted Time Series Study

Accuracy and Effects of Clinical Decision Support Systems Integrated With BMJ Best Practice–Aided Diagnosis: Interrupted Time Series Study

Accuracy and Effects of Clinical Decision Support Systems Integrated With BMJ Best Practice–Aided Diagnosis: Interrupted Time Series Study

Authors of this article:

Liyuan Tao1 Author Orcid Image ;   Chen Zhang2 Author Orcid Image ;   Lin Zeng1 Author Orcid Image ;   Shengrong Zhu2 Author Orcid Image ;   Nan Li1 Author Orcid Image ;   Wei Li2 Author Orcid Image ;   Hua Zhang1 Author Orcid Image ;   Yiming Zhao1 Author Orcid Image ;   Siyan Zhan1, 3 Author Orcid Image ;   Hong Ji2 Author Orcid Image
Article Authors Cited by (27) Tweetations (18) Metrics

Journals

  1. Siaki L, LIN V, Marshall R, Highley R. Feasibility of a Clinical Decision Support Tool to Manage Resistant Hypertension: Team-HTN, a Single-arm Pilot Study. Military Medicine 2021;186(1-2):e225 View
  2. Poly T, Islam M, Muhtar M, Yang H, Nguyen P, Li Y. Machine Learning Approach to Reduce Alert Fatigue Using a Disease Medication–Related Clinical Decision Support System: Model Development and Validation. JMIR Medical Informatics 2020;8(11):e19489 View
  3. Beldhuis I, Marapin R, Jiang Y, Simões de Souza N, Georgiou A, Kaufmann T, Castela Forte J, van der Horst I. Cognitive biases, environmental, patient and personal factors associated with critical care decision making: A scoping review. Journal of Critical Care 2021;64:144 View
  4. Saukkonen P, Elovainio M, Virtanen L, Kaihlanen A, Nadav J, Lääveri T, Vänskä J, Viitanen J, Reponen J, Heponiemi T. The Interplay of Work, Digital Health Usage, and the Perceived Effects of Digitalization on Physicians’ Work: Network Analysis Approach. Journal of Medical Internet Research 2022;24(8):e38714 View
  5. Graber M. Reaching 95%: decision support tools are the surest way to improve diagnosis now. BMJ Quality & Safety 2022;31(6):415 View
  6. Wang M, Sun Z, Jia M, Wang Y, Wang H, Zhu X, Chen L, Ji H. Intelligent virtual case learning system based on real medical records and natural language processing. BMC Medical Informatics and Decision Making 2022;22(1) View
  7. Lin C, Chien T, Chen Y, Lee Y, Su S. An app to classify a 5-year survival in patients with breast cancer using the convolutional neural networks (CNN) in Microsoft Excel. Medicine 2022;101(4):e28697 View
  8. Wang X, Xi H, Geng X, Li Y, Zhao M, Li F, Li Z, Ji H, Tian H. Artificial Intelligence-Based Prediction of Lower Extremity Deep Vein Thrombosis Risk After Knee/Hip Arthroplasty. Clinical and Applied Thrombosis/Hemostasis 2023;29 View
  9. Zhang D, Xiao L, Duan J, Chang X, Walsh K, Sandars J, Brown J, Dang X, Shen W, Du J, Cao Y. Understanding online self-directed learning using point of care information systems (POCIS): A plot study using a capability approach perspective. Medical Teacher 2022;44(12):1413 View
  10. Wang M, Lee C, Wei Z, Ji H, Yang Y, Yang C. Clinical assistant decision-making model of tuberculosis based on electronic health records. BioData Mining 2023;16(1) View
  11. Wang M, Yang B, Liu Y, Yang Y, Ji H, Yang C. Emerging infectious disease surveillance using a hierarchical diagnosis model and the Knox algorithm. Scientific Reports 2023;13(1) View
  12. Wang M, Jia M, Wei Z, Wang W, Shang Y, Ji H. Construction and effectiveness evaluation of a knowledge-based infectious disease monitoring and decision support system. Scientific Reports 2023;13(1) View
  13. van Velzen M, de Graaf-Waar H, Ubert T, van der Willigen R, Muilwijk L, Schmitt M, Scheper M, van Meeteren N. 21st century (clinical) decision support in nursing and allied healthcare. Developing a learning health system: a reasoned design of a theoretical framework. BMC Medical Informatics and Decision Making 2023;23(1) View
  14. Armando L, Miglio G, de Cosmo P, Cena C. Clinical decision support systems to improve drug prescription and therapy optimisation in clinical practice: a scoping review. BMJ Health & Care Informatics 2023;30(1):e100683 View
  15. K N, M․ B M. Fuzzy rule based classifier model for evidence based clinical decision support systems. Intelligent Systems with Applications 2024;22:200393 View
  16. Huang Z, Lim H, Ow J, Sun S, Chow A. Doctors’ perception on the ethical use of AI-enabled clinical decision support systems for antibiotic prescribing recommendations in Singapore. Frontiers in Public Health 2024;12 View
  17. Hatem N. Advancing Pharmacy Practice: The Role of Intelligence-Driven Pharmacy Practice and the Emergence of Pharmacointelligence. Integrated Pharmacy Research and Practice 2024;Volume 13:139 View
  18. Kim B, Ryan K, Kim J. Assessing the impact of information on patient attitudes toward artificial intelligence-based clinical decision support (AI/CDS): a pilot web-based SMART vignette study. Journal of Medical Ethics 2025;51(8):541 View
  19. Zhu S, Yang R, Pan Z, Tian X, Ji H. MISDP: multi-task fusion visit interval for sequential diagnosis prediction. BMC Bioinformatics 2024;25(1) View
  20. Azadi A, García-Peñalvo F. A Synergistic Bridge Between Human–Computer Interaction and Data Management Within CDSS. Data 2025;10(5):60 View
  21. Marceau M, Dulgarian S, Cambre J, Garabedian P, Amato M, Seger D, Volk L, Jackson G, Bates D, Rozenblum R, Syrowatka A. Clinician Attitudes and Perceptions of Point-of-Care Information Resources and Their Integration Into Electronic Health Records: Qualitative Interview Study. JMIR Medical Informatics 2025;13:e60191 View
  22. Schwalowsky O. Use of clinical decision tools across urgent and primary care: recognising barriers and challenges. International Journal for Advancing Practice 2025:1 View
  23. Wang W, Yang B, Wu H, Che H, Tong Y, Zhang B, Liu H, Chen Y. Auxiliary Diagnosis of Pulmonary Nodules’ Benignancy and Malignancy Based on Machine Learning: A Retrospective Study. Journal of Multidisciplinary Healthcare 2025;Volume 18:3735 View
  24. Mustafa U, Sauli E, Kreppel K, Boenecke J, Brinkel J. Evaluation of the acceptability of ESIDA app, a smartphone-based clinical decision support application to improve infectious disease outbreak detection in Tanzania: clinician perspectives. BMC Public Health 2025;25(1) View

Books/Policy Documents

  1. Popolo V, Nyanchama K, Marchesano M. Proceedings of LLEAHMM 2024. View

Conference Proceedings

  1. Nagar S, Patidar M, Sheikh R, Singh S, Kashiv A, Jain A, Namdeo S, Paranjpe P, Mandloi D. 2024 International Conference on Advances in Computing Research on Science Engineering and Technology (ACROSET). Review and Explore the Transformative Impact of Artificial Intelligence (AI) in Smart Healthcare Systems View
  2. Onyeachu P, Bounsall K, Inches J, Hammett K, Hunneman R, Stapleton N, Meinert E, Carroll C. 2025 IEEE International Conference on Digital Health (ICDH). SMaRT-PD CDSS: A Service Improvement Initiative for Self-Management and Clinical Decision Support in Parkinson’s Disease - Development and Initial Validation. View