Supporting clinical professionals in decision-making for patients with chronic diseases

Abstract. To deal with the large amount of data produced by telemonitoring of patients with chronic diseases, a decision support system (DSS) was developed. The DSS uses sensor data and the data from a patient’s electronic health record as the input. It assesses the risk to the patient’s health using three approaches. The first approach exploits the existing medical knowledge, the second approach uses supervised machine learning, and the third approach simply detects anomalies in the values of the monitored parameters. The risk assessment can show the contribution of the individual monitored parameters to the risk, and can be tailored by the doctor to each individual patient. The assessed risk and the raw input data can be used to trigger alerts. Finally, following the principles of evidence-based medicine, the DSS facilitates the consultation of medical literature when needed.