Clinical decision support (CDS) provides timely information, usually at the point of care, to help inform decisions about a patient's treatment. CDS tools and systems help clinical teams by taking over some routine tasks, warning of potential problems, or providing suggestions for the clinical team and patient to consider [1].
A clinical decision support system (CDSS) is a software application that analyses data to help healthcare providers make decisions and improve patient care.
Image Credit: Visensia® from Oxford Biosignals Ltd. is one of the earliest examples of an FDA-approved clinical decision support system that employs machine learning to predict which patients are at risk of deterioration, hours before most healthcare professionals can.
Objectives for a Clinical Decision Support System
A CDSS focuses on using knowledge management to generate clinical advice based on multiple sources of patient-related data. It offers information to clinicians and primary care providers to improve the quality of the care their patients receive. CDSS tools can, for example, offer reminders for preventive care, give alerts about potentially dangerous drug interactions and alert clinicians to possible redundant testing their patient has been scheduled to undergo. As such, using a CDSS can lower costs and increase efficiency [2].
As CDSSs become increasingly sophisticated in terms of the information they can generate, questions naturally arise about whether they are in fact diagnostics and when and how medical device regulations should be applied to them.
Examples of Clinical Decision Support Systems
Clinical Decision Support Systems and the Role of Artifical Intelligence
Alert Fatigue
Regulation of Clinical Decision Support Systems
How to Evaluate Clinical Decision Support Systems
Where to find out more
Romilly Life Sciences can offer several decades experience leading the validation, regulatory approval and implementation of clinical decision support systems as well as now-routinely deployed machine learning solutions for decision support in other safety-critical industries such as aviation.
To find out how you can reach patients faster, backed by compelling evidence, contact us.
References
[4] https://healthitanalytics.com/features/understanding-the-basics-of-clinical-decision-support-systems
[5] Berner, Eta S., ed. Clinical Decision Support Systems. New York, NY: Springer, 2007.
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