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

Telehealth and Telemonitoring (1556) Adoption and Change Management of eHealth Systems (670) Intensive Care Unit (ICU) (101) Nursing in a Hospital Setting (95)
Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19091, first published .
Improvements in Patient Monitoring in the Intensive Care Unit: Survey Study

Improvements in Patient Monitoring in the Intensive Care Unit: Survey Study

Improvements in Patient Monitoring in the Intensive Care Unit: Survey Study

Authors of this article:

Akira-Sebastian Poncette1, 2 Author Orcid Image ;   Lina Mosch1 Author Orcid Image ;   Claudia Spies1 Author Orcid Image ;   Malte Schmieding1, 2 Author Orcid Image ;   Fridtjof Schiefenhövel1, 2 Author Orcid Image ;   Henning Krampe1 Author Orcid Image ;   Felix Balzer1, 2 Author Orcid Image
Article Authors Cited by (60) Tweetations (7) Metrics

Journals

  1. Ezhilan M, Suresh I, Nesakumar N. SARS-CoV, MERS-CoV and SARS-CoV-2: A Diagnostic Challenge. Measurement 2021;168:108335 View
  2. Hinske L. Über die Zukunft des maschinellen Lernens in der Anästhesiologie. Der Anaesthesist 2020;69(8):533 View
  3. Hernandez L, Kim R, Tokcan N, Derksen H, Biesterveld B, Croteau A, Williams A, Mathis M, Najarian K, Gryak J. Multimodal tensor-based method for integrative and continuous patient monitoring during postoperative cardiac care. Artificial Intelligence in Medicine 2021;113:102032 View
  4. Nothman S, Kaffman M, Nave R, Flugelman M. Survey of faculty development in four Israeli medical schools: clinical faculty development is inadequate and clinical teaching is undervalued in Israeli faculties of medicine. Israel Journal of Health Policy Research 2021;10(1) View
  5. Tanaka H, Yokose M, Takaki S, Mihara T, Saigusa Y, Goto T. Evaluation of respiratory rate monitoring using a microwave Doppler sensor mounted on the ceiling of an intensive care unit: a prospective observational study. Journal of Clinical Monitoring and Computing 2022;36(1):71 View
  6. Romare C, Anderberg P, Sanmartin Berglund J, Skär L. Burden of care related to monitoring patient vital signs during intensive care; a descriptive retrospective database study. Intensive and Critical Care Nursing 2022;71:103213 View
  7. Liu P, Lu L, Zhang J, Huo T, Liu S, Ye Z. Application of Artificial Intelligence in Medicine: An Overview. Current Medical Science 2021;41(6):1105 View
  8. KELEŞ H. TIPTA YAPAY ZEKA UYGULAMALARI. Kırıkkale Üniversitesi Tıp Fakültesi Dergisi 2022;24(3):604 View
  9. Rodrigues V, Righi R, da Costa C, Antunes R. Smart Hospitals and IoT Sensors: Why Is QoS Essential Here?. Journal of Sensor and Actuator Networks 2022;11(3):33 View
  10. Tulk Jesso S, Kelliher A, Sanghavi H, Martin T, Henrickson Parker S. Inclusion of Clinicians in the Development and Evaluation of Clinical Artificial Intelligence Tools: A Systematic Literature Review. Frontiers in Psychology 2022;13 View
  11. Santos E, Luna A, Szpalher A. Tecnologias realizadas pela enfermagem em portadores de COVID-19: revisão integrativa. Revista Recien - Revista Científica de Enfermagem 2022;12(37):222 View
  12. Dahmer M, Jennings A, Parker M, Sanchez-Pinto L, Thompson A, Traube C, Zimmerman J. Pediatric Critical Care in the Twenty-first Century and Beyond. Critical Care Clinics 2023;39(2):407 View
  13. Hwang G, Tang K, Tu Y. How artificial intelligence (AI) supports nursing education: profiling the roles, applications, and trends of AI in nursing education research (1993–2020). Interactive Learning Environments 2024;32(1):373 View
  14. Mosch L, Poncette A, Spies C, Weber-Carstens S, Schieler M, Krampe H, Balzer F. Creation of an Evidence-Based Implementation Framework for Digital Health Technology in the Intensive Care Unit: Qualitative Study. JMIR Formative Research 2022;6(4):e22866 View
  15. Isfort M, McVerry B, Shutter L, Kim M, Lacomis D. Perceived utility of electrodiagnostic testing in critical illness myopathy and polyneuropathy: A survey of intensive care unit providers. Muscle & Nerve 2022;66(1):90 View
  16. Carelli L, Terzoni S, Destrebecq A, Formenti P, Soumahoro F, Esposito A, Ferrara P. Alarm fatigue in nurses working in intensive care units: A multicenter study. Work 2022;72(2):651 View
  17. Eini-Porat B, Amir O, Eytan D, Shalit U. Tell me something interesting: Clinical utility of machine learning prediction models in the ICU. Journal of Biomedical Informatics 2022;132:104107 View
  18. Poncette A, Mosch L, Stablo L, Spies C, Schieler M, Weber-Carstens S, Feufel M, Balzer F. A Remote Patient-Monitoring System for Intensive Care Medicine: Mixed Methods Human-Centered Design and Usability Evaluation. JMIR Human Factors 2022;9(1):e30655 View
  19. Seibert K, Domhoff D, Bruch D, Schulte-Althoff M, Fürstenau D, Biessmann F, Wolf-Ostermann K. Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review. Journal of Medical Internet Research 2021;23(11):e26522 View
  20. Senechal E, Jeanne E, Tao L, Kearney R, Shalish W, Sant’Anna G. Wireless monitoring devices in hospitalized children: a scoping review. European Journal of Pediatrics 2023;182(5):1991 View
  21. Sinno Z, Shay D, Kruppa J, Klopfenstein S, Giesa N, Flint A, Herren P, Scheibe F, Spies C, Hinrichs C, Winter A, Balzer F, Poncette A. The influence of patient characteristics on the alarm rate in intensive care units: a retrospective cohort study. Scientific Reports 2022;12(1) View
  22. Shim J, Lee E, Oh E, Cho E, Park J, Lee J, Ahn J. Predicting the risk of inappropriate depth of endotracheal intubation in pediatric patients using machine learning approaches. Scientific Reports 2023;13(1) View
  23. Bergauer L, Braun J, Roche T, Meybohm P, Hottenrott S, Zacharowski K, Raimann F, Rivas E, López-Baamonde M, Ganter M, Nöthiger C, Spahn D, Tscholl D, Akbas S. Avatar-based patient monitoring improves information transfer, diagnostic confidence and reduces perceived workload in intensive care units: computer-based, multicentre comparison study. Scientific Reports 2023;13(1) View
  24. Seibert K, Domhoff D, Fürstenau D, Biessmann F, Schulte-Althoff M, Wolf-Ostermann K. Exploring needs and challenges for AI in nursing care – results of an explorative sequential mixed methods study. BMC Digital Health 2023;1(1) View
  25. Manaithiya A, Alam O, Mittal S, Naim M, Imran M, Alshrari A, Sheikh A, Khan I. An Updated and Focused Review on Heterocyclic Inhibitors for SARSCoV and SARS-CoV-2 3CLpro. Mini-Reviews in Medicinal Chemistry 2023;23(5):576 View
  26. Tataei A, Rahimi B, Afshar H, Alinejad V, Jafarizadeh H, Parizad N. The effects of electronic nursing handover on patient safety in the general (non-COVID-19) and COVID-19 intensive care units: a quasi-experimental study. BMC Health Services Research 2023;23(1) View
  27. Tanaka H, Yokose M, Takaki S, Mihara T, Saigusa Y, Goto T. Measurement accuracy of a microwave doppler sensor beneath the mattress as a continuous respiratory rate monitor: a method comparison study. Journal of Clinical Monitoring and Computing 2024;38(1):77 View
  28. GÜL G, SEREN İNTEPELER Ş. Ensuring Specificity as a Strategy for Increasing Alarm Safety. Journal of Basic and Clinical Health Sciences 2023;7(3):139 View
  29. Gheysen F, Rex S. Artificial intelligence in anesthesiology. Acta Anaesthesiologica Belgica 2023;74(3):185 View
  30. Lambert S, Madi M, Sopka S, Lenes A, Stange H, Buszello C, Stephan A. An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals. npj Digital Medicine 2023;6(1) View
  31. Donta P, Murturi I, Casamayor Pujol V, Sedlak B, Dustdar S. Exploring the Potential of Distributed Computing Continuum Systems. Computers 2023;12(10):198 View
  32. Martinez-Ortigosa A, Martinez-Granados A, Gil-Hernández E, Rodriguez-Arrastia M, Ropero-Padilla C, Roman P, Leal-Costa C. Applications of Artificial Intelligence in Nursing Care: A Systematic Review. Journal of Nursing Management 2023;2023:1 View
  33. Kim S, Seo H, Choi S, Joo S. Tele-monitoring system for intensive care ventilators in isolation rooms. Scientific Reports 2023;13(1) View
  34. Dehghan M, Mokhtarabadi S, Rashidi E, Rahiminejad E, Asadi N. Correlation between professional quality of life and alarm fatigue symptoms among intensive care unit nurses. Health Science Reports 2023;6(10) View
  35. Senechal E, Radeschi D, Tao L, Lv S, Jeanne E, Kearney R, Shalish W, Sant Anna G. The use of wireless sensors in the neonatal intensive care unit: a study protocol. PeerJ 2023;11:e15578 View
  36. Balzer F, Agha-Mir-Salim L, Ziemert N, Schmieding M, Mosch L, Prendke M, Wunderlich M, Memmert B, Spies C, Poncette A. Staff perspectives on the influence of patient characteristics on alarm management in the intensive care unit: a cross-sectional survey study. BMC Health Services Research 2023;23(1) View
  37. Yang S, Galvagno S, Badjatia N, Stein D, Teeter W, Scalea T, Shackelford S, Fang R, Miller C, Hu P. A Novel Continuous Real-Time Vital Signs Viewer for Intensive Care Units: Design and Evaluation Study. JMIR Human Factors 2024;11:e46030 View
  38. Li B, Yue L, Nie H, Cao Z, Chai X, Peng B, Zhang T, Huang W. The effect of intelligent management interventions in intensive care units to reduce false alarms: An integrative review. International Journal of Nursing Sciences 2024;11(1):133 View
  39. Okada Y, Ning Y, Ong M. Explainable artificial intelligence in emergency medicine: an overview. Clinical and Experimental Emergency Medicine 2023;10(4):354 View
  40. Evans R, Bryant L, Russell G, Absolom K. Trust and acceptability of data-driven clinical recommendations in everyday practice: A scoping review. International Journal of Medical Informatics 2024;183:105342 View
  41. Chromik J, Flint A, Arnrich B. ARTEMIS: An alarm threshold and policy mining system for the intensive care unit. International Journal of Medical Informatics 2024;184:105349 View
  42. Morgan S. Nurse productivity: using evidence to enhance nurses’ use of time. Nursing Standard 2024;39(5):30 View
  43. Rayan A, Al-Ghabeesh S, Fawaz M, Behar A, Toumi A. Experiences, barriers and expectations regarding current patient monitoring systems among ICU nurses in a University Hospital in Lebanon: a qualitative study. Frontiers in Digital Health 2024;6 View
  44. Lee J, Rachim V, Hwang Y, Park S. Modular-Hybrid Wearable Cardiopulmonary Monitoring Sensor for Unobstructive Critical Care: With a Demonstration in Practice. IEEE Sensors Journal 2024;24(6):8763 View
  45. Knop M, Mueller M, Kaiser S, Rester C. The impact of digital technology use on nurses' professional identity and relations of power: a literature review. Journal of Advanced Nursing 2024 View
  46. Mosch L, Sümer M, Flint A, Feufel M, Balzer F, Mörike F, Poncette A. Alarm Management in Intensive Care: Qualitative Triangulation Study. JMIR Human Factors 2024;11:e55571 View
  47. Aljamaan F, Malki K, Alhasan K, Jamal A, Altamimi I, Khayat A, Alhaboob A, Abdulmajeed N, Alshahrani F, Saad K, Al-Eyadhy A, Al-Tawfiq J, Temsah M. ChatGPT-3.5 System Usability Scale early assessment among Healthcare Workers: Horizons of adoption in medical practice. Heliyon 2024;10(7):e28962 View
  48. Chen H, Yang F, Duan Y, Yang L, Li J. A novel higher performance nomogram based on explainable machine learning for predicting mortality risk in stroke patients within 30 days based on clinical features on the first day ICU admission. BMC Medical Informatics and Decision Making 2024;24(1) View
  49. Holtan I. The Importance of Reporting Recurring Medical Device Issues. Journal of Clinical Engineering 2024;49(3):105 View

Books/Policy Documents

  1. Azam I, Usman M. Emerging Technologies During the Era of COVID-19 Pandemic. View
  2. Zarnegar A. Current and Future Trends in Health and Medical Informatics. View
  3. Chromik J, Pfitzner B, Ihde N, Michaelis M, Schmidt D, Klopfenstein S, Poncette A, Balzer F, Arnrich B. Biomedical Engineering Systems and Technologies. View
  4. Singh P, Kansal M, Lahiri S, Vishnoi H, Mittal L. Enhancing Medical Imaging with Emerging Technologies. View
  5. Greenshaw A, Noble J, Kuriansky J, Sui J, Cao B, Li T, Torous J, Greiner R. Resilient Health. View