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

Adoption and Change Management of eHealth Systems (670) User Needs and Competencies (270)

Published on in Vol 7, No 2 (2019): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13064, first published .
Clinical Requirements of Future Patient Monitoring in the Intensive Care Unit: Qualitative Study

Clinical Requirements of Future Patient Monitoring in the Intensive Care Unit: Qualitative Study

Clinical Requirements of Future Patient Monitoring in the Intensive Care Unit: Qualitative Study

Authors of this article:

Akira-Sebastian Poncette1, 2 Author Orcid Image ;   Claudia Spies1 Author Orcid Image ;   Lina Mosch1 Author Orcid Image ;   Monique Schieler1 Author Orcid Image ;   Steffen Weber-Carstens1 Author Orcid Image ;   Henning Krampe1 Author Orcid Image ;   Felix Balzer1, 2 Author Orcid Image
Article Authors Cited by (58) Tweetations (11) Metrics

Journals

  1. Poncette A, Glauert D, Mosch L, Braune K, Balzer F, Back D. Undergraduate Medical Competencies in Digital Health and Curricular Module Development: Mixed Methods Study. Journal of Medical Internet Research 2020;22(10):e22161 View
  2. Jankovic I, Chen J. Clinical Decision Support and Implications for the Clinician Burnout Crisis. Yearbook of Medical Informatics 2020;29(01):145 View
  3. Shah P. Wireless monitoring in the ICU on the horizon. Nature Medicine 2020;26(3):316 View
  4. Poncette A, Mosch L, Spies C, Schmieding M, Schiefenhövel F, Krampe H, Balzer F. Improvements in Patient Monitoring in the Intensive Care Unit: Survey Study. Journal of Medical Internet Research 2020;22(6):e19091 View
  5. Al-Qatatsheh A, Morsi Y, Zavabeti A, Zolfagharian A, Salim N, Z. Kouzani A, Mosadegh B, Gharaie S. Blood Pressure Sensors: Materials, Fabrication Methods, Performance Evaluations and Future Perspectives. Sensors 2020;20(16):4484 View
  6. Dursun Ergezen F, Kol E. Nurses’ responses to monitor alarms in an intensive care unit: An observational study. Intensive and Critical Care Nursing 2020;59:102845 View
  7. Weenk M, Bredie S, Koeneman M, Hesselink G, van Goor H, van de Belt T. Continuous Monitoring of Vital Signs in the General Ward Using Wearable Devices: Randomized Controlled Trial. Journal of Medical Internet Research 2020;22(6):e15471 View
  8. Thakur A, Soklaridis S, Crawford A, Mulsant B, Sockalingam S. Using Rapid Design Thinking to Overcome COVID-19 Challenges in Medical Education. Academic Medicine 2021;96(1):56 View
  9. Lewandowska K, Weisbrot M, Cieloszyk A, Mędrzycka-Dąbrowska W, Krupa S, Ozga D. Impact of Alarm Fatigue on the Work of Nurses in an Intensive Care Environment—A Systematic Review. International Journal of Environmental Research and Public Health 2020;17(22):8409 View
  10. Schwartz J, Moy A, Rossetti S, Elhadad N, Cato K. Clinician involvement in research on machine learning–based predictive clinical decision support for the hospital setting: A scoping review. Journal of the American Medical Informatics Association 2021;28(3):653 View
  11. Sakib N, Ahamed S, Khan R, Griffin P, Haque M. Unpacking Prevalence and Dichotomy in Quick Sequential Organ Failure Assessment and Systemic Inflammatory Response Syndrome Parameters: Observational Data–Driven Approach Backed by Sepsis Pathophysiology. JMIR Medical Informatics 2020;8(12):e18352 View
  12. Buchanan C, Howitt M, Wilson R, Booth R, Risling T, Bamford M. Predicted Influences of Artificial Intelligence on the Domains of Nursing: Scoping Review. JMIR Nursing 2020;3(1):e23939 View
  13. Xu S, Rwei A, Vwalika B, Chisembele M, Stringer J, Ginsburg A, Rogers J. Wireless skin sensors for physiological monitoring of infants in low-income and middle-income countries. The Lancet Digital Health 2021;3(4):e266 View
  14. Poncette A, Wunderlich M, Spies C, Heeren P, Vorderwülbecke G, Salgado E, Kastrup M, Feufel M, Balzer F. Patient Monitoring Alarms in an Intensive Care Unit: Observational Study With Do-It-Yourself Instructions. Journal of Medical Internet Research 2021;23(5):e26494 View
  15. Sakib N, Tian S, Haque M, Khan R, Ahamed S. SepINav (Sepsis ICU Navigator): A data-driven software tool for sepsis monitoring and intervention using Bayesian Online Change Point Detection. SoftwareX 2021;14:100689 View
  16. Ray I, Agarwal V, Agarwal T, Pande A. Medical Student’s Perspective Regarding Undergraduate Surgical Education with Special Reference to Pandemic. Indian Journal of Surgery 2022;84(S1):104 View
  17. 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
  18. Farias-Gaytan S, Aguaded I, Ramirez-Montoya M. Transformation and digital literacy: Systematic literature mapping. Education and Information Technologies 2022;27(2):1417 View
  19. Kim M, Oh J, Kim J, Park J. Development and Validation of Simplified Delirium Prediction Model in Intensive Care Unit. Frontiers in Psychiatry 2022;13 View
  20. Gülsoy Z, Karabey T. Quality Of Life and Coping With Stress in Relatives of Patients in Intensive Care Units During COVID-19. American Journal of Critical Care 2023;32(3):205 View
  21. 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
  22. Chromik J, Klopfenstein S, Pfitzner B, Sinno Z, Arnrich B, Balzer F, Poncette A. Computational approaches to alleviate alarm fatigue in intensive care medicine: A systematic literature review. Frontiers in Digital Health 2022;4 View
  23. 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
  24. Grunow J, Nydahl P, Schaller S. Mobilisation auf Intensivstationen: Intensivpflegezimmer und Medizintechnik können helfen. AINS - Anästhesiologie · Intensivmedizin · Notfallmedizin · Schmerztherapie 2022;57(01):41 View
  25. 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
  26. Shih Y, Lee T, Mills M. Critical Care Nurses' Perceptions of Clinical Alarm Management on Nursing Practice. CIN: Computers, Informatics, Nursing 2022;40(6):389 View
  27. 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
  28. López‐Espuela F, Rodríguez‐Martin B, Lavado García J, Toribio‐Felipe R, Amarilla‐Donoso F, Rodríguez Almagro J, Ribeiro A, Fernandes V, Moran‐García J. Experiences and mediating factors in nurses' responses to electronic device alarms: A phenomenological study. Journal of Nursing Management 2022;30(5):1303 View
  29. Bacchin D, Pernice G, Pierobon L, Zanella E, Sardena M, Malvestio M, Gamberini L. Co-Design in Electrical Medical Beds with Caregivers. International Journal of Environmental Research and Public Health 2022;19(23):16353 View
  30. Obeidat B, Younis M, Al-Shlool E, Alzouby A. A Study of Workspace Design Characteristics Exemplified by Nurses’ Satisfaction Within Three Intensive Care Units in a University Hospital. HERD: Health Environments Research & Design Journal 2022;15(2):63 View
  31. Wetli D, Bergauer L, Nöthiger C, Roche T, Spahn D, Tscholl D, Said S. Improving Visual-Patient-Avatar Design Prior to Its Clinical Release: A Mixed Qualitative and Quantitative Study. Diagnostics 2022;12(2):555 View
  32. Movahedi A, Sadooghiasl A, Ahmadi F, Vaismoradi M. A grounded theory study of alarm fatigue among nurses in intensive care units. Australian Critical Care 2023;36(6):980 View
  33. Krampe H, Denke C, Gülden J, Mauersberger V, Ehlen L, Schönthaler E, Wunderlich M, Lütz A, Balzer F, Weiss B, Spies C. Perceived Severity of Stressors in the Intensive Care Unit: A Systematic Review and Semi-Quantitative Analysis of the Literature on the Perspectives of Patients, Health Care Providers and Relatives. Journal of Clinical Medicine 2021;10(17):3928 View
  34. Gallagher K, Hayns-Worthington R, Marlow N, Meek J, Chant K. Parental experiences of live video streaming technology in neonatal care in England: a qualitative study. BMC Pediatrics 2023;23(1) View
  35. Woo J, Kim E, Kim S. The current status of breakthrough devices designation in the United States and innovative medical devices designation in Korea for digital health software. Expert Review of Medical Devices 2022;19(3):213 View
  36. . ‘What Makes It Nice Is Also What Makes It Difficult’. Anthropology in Action 2021;28(3):35 View
  37. Tsopra R, Peiffer-Smadja N, Charlier C, Campeotto F, Lemogne C, Ruszniewski P, Vivien B, Burgun A. Putting undergraduate medical students in AI-CDSS designers’ shoes: An innovative teaching method to develop digital health critical thinking. International Journal of Medical Informatics 2023;171:104980 View
  38. Martin L, Peine A, Gronholz M, Marx G, Bickenbach J. Künstliche Intelligenz: Herausforderungen und Nutzen in der Intensivmedizin. AINS - Anästhesiologie · Intensivmedizin · Notfallmedizin · Schmerztherapie 2022;57(03):199 View
  39. 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
  40. Livia J, Márquez Miramontes B, Campos Pérez R, Leiner de la Cabada M. Comparación de estrategias multimodales para mejorar el reconocimiento de los hitos del desarrollo infantil entre los proveedores de servicios de guardería durante una conferencia virtual o presencial. Investigación en Enfermería: Imagen y Desarrollo 2023;25 View
  41. Gupta N, Simmen P, Trachsel D, Haeberlin A, Jost K, Niederhauser T. Respiratory rate estimation from multi-channel signals using auto-regulated adaptive extended Kalman filter. Biomedical Signal Processing and Control 2023;84:104977 View
  42. 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
  43. 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
  44. Kim J, Ryan K, Kasun M, Hogg J, Dunn L, Roberts L. Physicians’ and Machine Learning Researchers’ Perspectives on Ethical Issues in the Early Development of Clinical Machine Learning Tools: Qualitative Interview Study. JMIR AI 2023;2:e47449 View
  45. 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
  46. Peine A, Gronholz M, Seidl-Rathkopf K, Wolfram T, Hallawa A, Reitz A, Celi L, Marx G, Martin L. Standardized Comparison of Voice-Based Information and Documentation Systems to Established Systems in Intensive Care: Crossover Study. JMIR Medical Informatics 2023;11:e44773 View
  47. Lee J, Hwang Y, Park S. Rationale and Design of a Wearable Cardiopulmonary Monitoring System for Improving the Efficiency of Critical Care Monitoring. Applied Sciences 2023;13(24):13101 View
  48. 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
  49. Rony M, Kayesh I, Bala S, Akter F, Parvin M. Artificial intelligence in future nursing care: Exploring perspectives of nursing professionals - A descriptive qualitative study. Heliyon 2024;10(4):e25718 View
  50. Martin L, Peine A, Gronholz M, Marx G, Bickenbach J. Künstliche Intelligenz: Herausforderungen und Nutzen in der Intensivmedizin. intensiv 2024;32(02):76 View
  51. 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
  52. Tambour R, Malak M, Rabee H, Nazzal Z, Gharbeyah M, Abugaber D, Ghoul I. A retrospective study of the predictors of mortality among patients in intensive care units at North West-Bank hospitals in Palestine. Hospital Practice 2024:1 View
  53. 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

Books/Policy Documents

  1. Poncette A, Meske C, Mosch L, Balzer F. Human Interface and the Management of Information. Information in Intelligent Systems. View
  2. Geoffrey Chase J, Zhou C, Knopp J, Moeller K, Benyo B, Desaive T, Wong J, Malinen S, Naswall K, Shaw G, Lambermont B, Chiew Y. Cyber–Physical–Human Systems. View