Clinical decision support system and the benefits of healthcare software development

When it comes to human life, every second counts. Rubius has developed an AI-based system that helps doctors instantly diagnose blood clotting disorders at the patient's bedside.

Clinical software, and Clinical Decision Support Systems (CDSS) in particular,  provides evidence-based information and guidance to healthcare professionals, including interpretation of laboratory results. It helps clinicians identify potential abnormalities or patterns in blood test results and provide suggestions for further investigation or treatment options.

Customer

The system was ordered by Mednorth-Technics, a manufacturer of piezoelectric thromboelastographs. These instruments analyze blood clotting values in real time and provide results in the form of a chart with numerical values. To decipher them, a doctor needs a high level of qualification and a lot of time. 

To make the work of medical professionals easier, Mednorth-Technics decided to "teach" the device to issue conclusions based on thromboelastography results.

The Rubius team analyzed 1,300 thromboelastograph studies, 20 blood clotting parameters in each record and their corresponding diagnoses. Using this information, we developed a machine learning algorithm for classifying disorders and created a medical decision support system. 

How the clinical decision support system works

The system provides suggestions or recommendations based on established medical guidelines and algorithms. It analyzes blood clotting parameters recorded by the thromboelastograph, determines what kind of disorder the patient has, and provides the doctor with a clear conclusion. 

It takes a couple of seconds to get the result, and its accuracy is 98.4%.