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

Clinical Information and Decision Making (1407) Digital Health Reviews (1289) Decision Support for Health Professionals (1185) Electronic Health Records (1053) Tools, Programs and Algorithms (266) Intensive Care Unit (ICU) (112)
Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28209, first published .
Predicting Patient Deterioration: A Review of Tools in the Digital Hospital Setting

Predicting Patient Deterioration: A Review of Tools in the Digital Hospital Setting

Predicting Patient Deterioration: A Review of Tools in the Digital Hospital Setting

Authors of this article:

Kay D Mann1 Author Orcid Image ;   Norm M Good1 Author Orcid Image ;   Farhad Fatehi2, 3 Author Orcid Image ;   Sankalp Khanna1 Author Orcid Image ;   Victoria Campbell4, 5, 6 Author Orcid Image ;   Roger Conway4 Author Orcid Image ;   Clair Sullivan2, 7 Author Orcid Image ;   Andrew Staib5, 8, 9 Author Orcid Image ;   Christopher Joyce8, 9 Author Orcid Image ;   David Cook8, 9, 10 Author Orcid Image
Article Authors Cited by (31) Tweetations (5) Metrics

Journals

  1. Shen Y, Zhang L, Wu P, Huang Y, Xin S, Zhang Q, Zhao S, Sun H, Lei G, Zhang T, Han W, Wang Z, Jiang J, Yu X. Construction and evaluation of networks among multiple postoperative complications. Computer Methods and Programs in Biomedicine 2023;232:107439 View
  2. Scquizzato T, Gamberini L, Semeraro F. How technology can save lives in cardiac arrest. Current Opinion in Critical Care 2022;28(3):250 View
  3. Brankovic A, Hassanzadeh H, Good N, Mann K, Khanna S, Abdel-Hafez A, Cook D. Explainable machine learning for real-time deterioration alert prediction to guide pre-emptive treatment. Scientific Reports 2022;12(1) View
  4. Malycha J, Bacchi S, Redfern O. Artificial intelligence and clinical deterioration. Current Opinion in Critical Care 2022;28(3):315 View
  5. Malycha J, Andersen C, Redfern O, Peake S, Subbe C, Dykes L, Phillips A, Ludbrook G, Young D, Watkinson P, Flabouris A, Jones D. Protocol describing a systematic review and mixed methods consensus process to define the deteriorated ward patient. BMJ Open 2022;12(9):e057614 View
  6. Zahradka N, Geoghan S, Watson H, Goldberg E, Wolfberg A, Wilkes M. Assessment of Remote Vital Sign Monitoring and Alarms in a Real-World Healthcare at Home Dataset. Bioengineering 2022;10(1):37 View
  7. Saab A, Abi Khalil C, Jammal M, Saikali M, Lamy J. Early Prediction of All-Cause Clinical Deterioration in General Wards Patients: Development and Validation of a Biomarker-Based Machine Learning Model Derived From Rapid Response Team Activations. Journal of Patient Safety 2022;18(6):578 View
  8. Jahandideh S, Ozavci G, Sahle B, Kouzani A, Magrabi F, Bucknall T. Evaluation of machine learning-based models for prediction of clinical deterioration: A systematic literature review. International Journal of Medical Informatics 2023;175:105084 View
  9. Pollack M, Trujillo Rivera E, Morizono H, Patel A. Clinical Instability Is a Sign of Severity of Illness: A Cohort Study. Pediatric Critical Care Medicine 2023;24(9):e425 View
  10. Al-Kofahi M, Spicer A, Schaefer R, Uhl A, Churpek M, Govindan S. National Early Warning Score Deployment in a Veterans Affairs Facility: A Quality Improvement Initiative and Analysis. American Journal of Medical Quality 2023;38(3):147 View
  11. Monfredi O, Andris R, Lake D, Moorman J. A novel predictive analytics score reflecting accumulating disease burden—an investigation of the cumulative CoMET score. Physiological Measurement 2023;44(5):055005 View
  12. ARSLAN A. Sağlıkta Kalite Kapsamında Dijital Bir Hastanede Müşteri Memnuniyeti Araştırması. Alanya Akademik Bakış 2023;7(3):1123 View
  13. Beard J, Sethi A, Jiao W, Hyatt H, Yapici H, Erslon M, Overdyk F. Cost savings through continuous vital sign monitoring in the medical-surgical unit. Journal of Medical Economics 2023;26(1):760 View
  14. van Rossum M, Bekhuis R, Wang Y, Hegeman J, Folbert E, Vollenbroek-Hutten M, Kalkman C, Kouwenhoven E, Hermens H. Early Warning Scores to Support Continuous Wireless Vital Sign Monitoring for Complication Prediction in Patients on Surgical Wards: Retrospective Observational Study. JMIR Perioperative Medicine 2023;6:e44483 View
  15. Wan Y, Wright M, McFarland M, Dishman D, Nies M, Rush A, Madaras-Kelly K, Jeppesen A, Del Fiol G. Information displays for automated surveillance algorithms of in-hospital patient deterioration: a scoping review. Journal of the American Medical Informatics Association 2023;31(1):256 View
  16. Sharabi A, Abutbul E, Grossbard E, Martsiano Y, Berman A, Kassif-Lerner R, Hakim H, Liber P, Zoubi A, Barkai G, Segal G. Six-Lead Electrocardiography Enables Identification of Rhythm and Conduction Anomalies of Patients in the Telemedicine-Based, Hospital-at-Home Setting: A Prospective Validation Study. Sensors 2023;23(20):8464 View
  17. Cimr D, Busovsky D, Fujita H, Studnicka F, Cimler R, Hayashi T. Classification of health deterioration by geometric invariants. Computer Methods and Programs in Biomedicine 2023;239:107623 View
  18. van der Vegt A, Campbell V, Mitchell I, Malycha J, Simpson J, Flenady T, Flabouris A, Lane P, Mehta N, Kalke V, Decoyna J, Es’haghi N, Liu C, Scott I. Systematic review and longitudinal analysis of implementing Artificial Intelligence to predict clinical deterioration in adult hospitals: what is known and what remains uncertain. Journal of the American Medical Informatics Association 2024;31(2):509 View
  19. Holder A, Khanna A, Scott M, Rossetti S, Rinehart J, Linn D, Weichert J, Dellinger R. A Delphi Process to Identify Relevant Outcomes That May Be Associated With a Predictive Analytic Tool to Detect Hemodynamic Deterioration in the Intensive Care Unit. Cureus 2023 View
  20. Batterbury A, Douglas C, Coyer F. Patient outcomes following medical emergency team review on general wards: Development of predictive models. Journal of Clinical Nursing 2024;33(9):3565 View
  21. Balagopalan A, Baldini I, Celi L, Gichoya J, McCoy L, Naumann T, Shalit U, van der Schaar M, Wagstaff K, Badawi O. Machine learning for healthcare that matters: Reorienting from technical novelty to equitable impact. PLOS Digital Health 2024;3(4):e0000474 View
  22. Lin C, Liu W, Tsai D, Lou Y, Chang C, Lee C, Fang W, Wang C, Chen Y, Lin W, Cheng C, Lee C, Wang C, Tsai C, Lin S, Lin C. AI-enabled electrocardiography alert intervention and all-cause mortality: a pragmatic randomized clinical trial. Nature Medicine 2024;30(5):1461 View
  23. Rahman J, Brankovic A, Tracy M, Khanna S. Exploring Computational Techniques in Preprocessing Neonatal Physiological Signals for Detecting Adverse Outcomes: Scoping Review. Interactive Journal of Medical Research 2024;13:e46946 View
  24. Li S, Tan T, Li J, Li H, Zhou L, Bai K, Xiao L, Xu X, Tan L, Jekarl D. Validating the performance of organ dysfunction scores in children with infection: A cohort study. PLOS ONE 2024;19(7):e0306172 View
  25. Ogieuhi I, Aderinto N, Olatunji G, Kokori E, Babalola A, Ayodeji K, Oluwatomiwa A, Bisola M, Ishola I, Rebecca O, Ojapah I. Towards equitable renal care: Strategies for enhancing kidney transplantation in Africa. Journal of Medicine, Surgery, and Public Health 2024;3:100131 View
  26. Leenen J, Mondria C. Variation in nurses’ compliance with an Early Warning Score protocol: A retrospective cohort study. Heliyon 2024;10(16):e36147 View
  27. Ghoshal A, Prince R, Downar J, Lapenskie J, Subramaniam S, Wegier P, Le L, Hannon B. Exploring the Utility of the Modified Hospitalized‐Patient One‐Year Mortality Risk Score to Trigger Referrals to Palliative Care for Inpatients With Cancer. Cancer Medicine 2024;13(19) View

Books/Policy Documents

  1. Mishra D. Intersections of Law and Computational Intelligence in Health Governance. View