AI technologies can play a valuable role in building advanced systems that monitor; interpret and react to key events during the management of a customers life cycle. We have built a system that is an example of such an AI technology -- we refer to it as Intelligent Collaborative Care Management (ICCM). ICCM guides a team of providers and customers through critical stages in a customers life cycle.
This system has been applied to the collaborative care of patients with chronic disease. Managing patient care is difficult; because health care providers and patients must collaboratively achieve goals in a customised care plan. Achieving these goals is strongly correlated with better health outcomes of patients. Regrettably; these outcomes are seldom attained because of uncertainty; incompleteness and bounded resources in this domain (e.g.; change of health conditions; change of objectives of providers; unreliable patients and change of governance policies).
ICCM specifies intelligent agents that assist health care providers and patients in (a) adhering to a care plan and (b) varying the care plan itself; if required.
This adherence and variation support component in ICCM defines a monitoring-recognitionintervention cycle: monitoring provider and customer behaviour; recognising off-track behaviour; and intervening to (a) move processes back on-track or (b) make changes to the care plan itself.
This presentation is concluded by outlining challenging future directions in this line of research.