New information model for clinical challenges

The importance of information systems for health and pharma industries is rapidly growing.
The traditional IT health solution has been designed based on data gathered in RDBMS systems with strictly and rigidly defined data models, applications and functionalities. Nowadays, it must meet the requirements of rapidly changing medical demands, pharmaceutical research, and an increasing number of new drugs, trial programs or more advanced treatments.
All this information and rules build a knowledge data base which, at the end of the day, improves treatment by giving medical doctors access to new research results and medical books, simplifying knowledge exchange and, most importantly, providing access to treatment history of each patient.

But how can this knowledge be used to support medical treatment?


The answer is the Clinical Decision Support System (CDSS), a major topic of artificial intelligence in medicine, whose main goal is to link health observations with health knowledge to assist health choices by clinicians and doctors for the improved quality and effectiveness of health care. It collects patient data, provides data analysis, diagnosis and recommendations for case-specific items and is integrated into the clinical workflow.

Read more about the CDSS case study for ESMO guidelines and technology behind the semantic model driven solution.