Isabel

Isabel is a Web-based clinical decision support system cutting edge technology from Autonomy an industry leader in Meaning Based Computing (MBC) coupled with proprietary Isabel algorithms to 'understand' vast amounts of medical knowledge. This enables the system to instantly provide the busy clinician with a safe checklist of likely diagnoses for a set of signs and symptoms entered in free text. The clinicians who 'Isabel' their patients at an early stage are able to offer a higher quality of care and reduce clinical risk by ensuring that important possible diagnoses have not been missed. Using the same proprietary technology which powers the diagnosis reminder system, Isabel also mobilizes knowledge to help the clinician find relevant and diagnosis specific answers to clinical questions more easily and quickly at the point of care.

As well as helping clinicians provide the highest quality standard of care, Isabel has set new standards for the clinical testing of decision support systems in healthcare having undergone a robust, peer-reviewed validation process over 7 years to demonstrate its accuracy, effectiveness and value. To date, 13 articles including independent clinical studies, multi-centre collaborative studies, and our own studies as developers have appeared in prestigious peer-reviewed journals.

Isabel uniquely adds intelligence to the electronic medical record (EMR) by processing extracted relevant clinical information automatically thereby providing the clinician with diagnosis support instantly with no additional data entry. To date, Isabel interfaces with NextGen, PatientKeeper and A4 Health Systems, along with a number of hospital-based EMR vendors including Cerner.