The Ascom CDSS solution is a rules-based engine that gives clinicians up-to-date data they need in order to make early interventions or other actions. Once a patient’s vitals exceed pre-set values, the CDSS alerts relevant clinicians of possible patient deterioration. Clinicians can then forward the alert to colleagues and initiate and manage emergency responses. The CDSS also supports various rule-based scoring: Early Warning Scores, Aldrete scoring, etc.
The Ascom clinical decision support system (CDSS) is a rules-based engine. It continuously receives data from multiple devices and departments. And when pre-defined criteria are met, it transmits alerts—together with near-real time clinical data—to clinicians’ handsets and/or dashboards.
Vendor-neutral, interoperable with existing and planned medical devices and communication system
Clinicians get the context-rich, near-real time data they need to make the better care decisions.
Fast, targeted, informed responses by the right people at the right time can have a significant positive impact on patient satisfaction and recovery.
Filtered alerting and messaging helps improve productivity and staff morale. Calmer environments can enhance staff satisfaction.
Adapts to meet changing needs. Scalable from an on-site system for a single department/ward, up to mult-site, multi-organization solutions.
From initial planning with Ascom clinical consultants to installation and solution lifecycle support and training.
Crucially, the technology development work was done by clinicians. It meant we had genuine engagement with nurses and other stakeholders as we carefully planned the hospital from the start – taking in the views of estates, IT, domestic staff, porters, admin, allied health and medical staff.
Why Singapore's Sengkang Hospitals chose Ascom Telligence, and moved beyond traditional nurse care to achieve a true patient response system.
The new Tyks Lighthouse Hospital in Turku, Finland, will receive its first patients at the start of 2022. Focus on patients is one of the principal values of the hospital and its translation into practice is ensured through functional planning and multiprofessional collaboration.
Agile solutions in a healthcare crisis: learn how Ascom worked with a hospital to devise a patient-monitoring system for EWS calculation.
Journal of healthcare protection management: publication of the International Association for Hospital Security 26(1):81-99 DOI:10.1097/NNA.0b013e3181ae97db
Joint Commission Center for Transforming Healthcare Releases Targeted Solutions Tool for Hand-Off Communications. Joint Commission Perspectives. August 2012, Volume 32, Issue 8.
Factors associated with delayed rapid response team activation.Reardon, Peter M; Fernando, Shannon M; Murphy, Kyle; Rosenberg, Erin; Kyeremanteng, Kwadwo. Journal of critical care, 2018-08, Vol.46, p.73-78
Standards of Obstetric-Gynaecologic Services. 7th ed. Washington, DC: ACOG; 1989. American College of Obstetricians and Gynaecologist; p. 39.
Colliver, Victoria; Kaul, Greta; Allday, Erin. Medical equipment generates millions of alerts, 'alarm fatigue.' SFGate,12 November 2014.
Hospital Inpatient Falls across Clinical Departments. Mikos, Marcin; Banas, Tomasz; Czerw, Aleksandra; Banas, Bartłomiej; Strzępek, Łukasz; Curyło, Mateusz. International journal of environmental research and public health, 2021-08-02, Vol.18 (15), p.8167
Noise in hospital rooms and sleep disturbance in hospitalized medical patients. Park, Marn Joon; Yoo, Jee Hee; Cho, Byung Wook; Kim, Ki Tae; Jeong, Woo-Chul; Ha, Mina. Environmental health and toxicology. Eht, 2014, Vol.29 (29), p.6.1-6.6
Ryherd EE, Waye KP, Ljungkvist L. Characterizing noise and perceived work environment in a neurological intensive care unit. J Acoust Soc Am. 2008;123(2):747-756.
A Pragmatic, Stepped-Wedge, Cluster-controlled Clinical Trial of Real-Time Pneumonia Clinical Decision Support, Nathan C. Dean, Caroline G. Vines, Jason R. Carr, Jenna G. Rubin, Brandon J. Webb, Jason R. Jacobs, Allison M. Butler, Jaehoon Lee, Al R. Jephson, Nathan Jenson , Missy Walker, Samuel M. Brown, Jeremy A. Irvin, Matthew P. Lungren, Todd L. Allen. American Journal of Respiratory and Critical Care Medicine, https://doi.org/10.1164/rccm.202109-2092OC
An overview of clinical decision support systems: benefits, risks, and strategies for success. Reed T. Sutton, David Pincock, Daniel C. Baumgart, Daniel C. Sadowski, Richard N. Fedorak and Karen I. Kroeker. npj Digital Medicine (2020) 3:17; https://doi.org/10.1038/s41746-020-0221-y