Expert systems and home-based telehealth: Exploring a role for MCRDR in enhancing diagnostics

Home-based telehealth services hold significant potential for integrating patient biological sensor data to support health management. At the same time, the deployment of telehealth into the home highlights the need for improved ways to collate, classify and dynamically interpret data safely and effectively. In relation to individual patients questions are posed as to how to most effectively communicate this data to them to support optimal health behaviour. For clinicians working at a distance, the huge amounts of data generated on all their home-based patients pose questions on how best to intelligently filter, analyse and interpret this data to make diagnoses and respond to changes in patient conditions. The paper reviews previous research work on expert systems in healthcare, in particular reviewing the capabilities of the expert system maintenance technology, Multiple Classification Ripple Down Rules, in healthcare. The paper also describes a home-based telehealth device, called MediStation that is being deployed in Korean homes to consider how MCRDR could enhance the decision-making for this device.