SASICU Project Insights
Intensive care units (ICUs) are highly complex environments where multiple medical devices monitor and treat patients. While many medical devices display measured parameters, there is a lack of meaningful decision support to turn clinical data into valuable insights for clinicians. Having the right understanding in critical situations could be an important contribution to patient safety.
The Smart and Silent ICU (SASICU) research project aims to develop new capabilities to improve intensive care outcomes through standardised, open and secure interoperability between medical devices and clinical information systems.
The project group is investigating how near real-time data integration could provide clinicians with a comprehensive and up-to-date view of the patient's condition. It will analyse how intelligent decision support could help manage the clinical complexity of modern intensive care units. In addition, new alarm management capabilities will be investigated to see if they can improve outcomes by silencing medical alarms in patients' rooms, creating a 'silent ICU'.
Project Insights
8
Project participants from clinics, research and industry
3
Three years runtime from October 2023 to September 2026
8.8 Mio. €
EU funding via the Innovative Health Initiative (IHI)
8.8 Mio. €
Industry funding contribution
Technology Research Field
The project makes use of the Service-oriented Device Connectivity (SDC) standard (ISO/IEEE 11073 SDC), which facilitates the interoperability of different medical devices and IT systems in high acuity environments. SASICU will run four studies at different hospital sites across Europe to explore how system architectures based on the SDC standard can help to reduce noise pollution in ICUs and improve patient care with meaningful decision support.
Creating a Healing Environment
Silent ICU Use Case
With peaks of up to 127.9 dBA, ICUs are significantly louder than the WHO recommendation of 35 dB. [1] Alarm noise could contribute to patient delirium, which is associated with longer lengths of stay, increased readmission rates, cognitive and functional impairment as well as increased mortality. [2,3]
Together, we are investigating how a silent patient room with alarm distribution can reduce stress and improve outcomes.
Project partners
Erasmus Medical Center (Rotterdam, Netherlands)
Dräger
B. Braun
Ascom
Clinical Alarm Reduction
Smart Alarming Use Case
Up to 350 alarms can occur per patient per day while 85-95% of alarms do not require an immediate clinical intervention. [4,5,6] This overwhelming number of alarms can lead to alarm fatigue amongst caregivers and poses the risk of relevant clinical alarms being missed.
Together, we are eliminating unnecessary alarms by developing a powerful algorithm to evaluate alarms and their clinical relevance.
Project partners
Universitair Medisch Centrum Utrecht (Utrecht, Netherlands)
Dräger
Ascom
Early detection and prevention of the post intensive care syndrome (PICS)
Smart ICU Use Case
Patients suffering from a critical illness have an increased risk of long-term cognitive impairment after their stay in the ICU. [7]
Together, we strive to predict and detect PICS at an early stage with a validated algorithm and prediction tool.
Project partners
Medical University of Vienna (Vienna, Austria)
Dräger
Heart-lung Interaction Analytics
Smart ICU Use Case
Complexity is one of the leading causes for critical incidents in acute care. Over 80% of all critical incidents are related to loss of situation awareness due to missing perception or comprehension. [8]
Together, we are enabling prediction of specific clinical conditions, such as septic and cardiogenic shock, ARDS and readiness for weaning.
Project partners
Hospital Clínic de Barcelona (Barcelona, Spain)
Universitat Politecnica de Catalunya (Barcelona, Spain)
Dräger
BetterCare
References
[1] Darbyshire J. L. et al. (2019). Mapping sources of noise in an intensive care unit. Anaesthesia 2019, 74, pp. 1018-1025.
[2] Darbyshire J. L. & Young J. D. (2013). An investigation of sound levels on intensive care units with reference to the WHO guidelines. Critical Care 17:R187.
[3] Hughes, C. G. et al. (2020). American Society for Enhanced Recovery and Perioperative Quality Initiative Joint Consensus Statement on Postoperative Delirium Prevention. Anesth Analg. 130(6), pp. 1572-1590.
[4] Jones, K. (2014). Alarm fatigue a top patient safety hazard. Canadian Medical Association Journal, 186(3), p.178.
[5] Koomen E et al. (2021). Reducing medical device alarms by an order of magnitude: A human factors approach. Anaestesia and Intensive Care 49(1), pp. 52-61.
[6] Nix M et al. (2015). Combating Alarm Fatigue. American Journal of Nursing, 115(2), p.16.
[7] Pandharipande, P. P. et al. (2013). Long-term cognitive impairment after critical illness. The New England journal of medicine, 369(14), 1306–1316.
[8] Schulz, C. M. et al. (2016). Situation awareness errors in anesthesia and critical care in 200 cases of a critical incident reporting system. BMC anesthesiology, 16, 4.