Integrating AISquared & MINDtick: a personalised digital community health care model

Opportunity 

Healthcare services increasingly rely on multiple digital systems that collect valuable information but operate independently. This limits the ability to combine electronic health record data with patient-generated health information and reduces opportunities to personalise decisions and monitor health trajectories and outcomes.  

The project explored how to enable a personalised digital community health care model where case managers could better manage caseloads and prioritise patients for discharge by incorporating additional insights on patients’ health and behaviours outside the clinic. 

Project Objectives  

The project team aimed to integrate the AISquared and MINDtick platforms to enable a personalised digital community health care model. Securely linking the day-to-day objective measures and insights from patient-generated health data with electronic health record data could be a powerful combination for developing algorithms to improve decision support and identify early intervention opportunities. The project sought to create infrastructure that would generate more meaningful decision-support information for clinicians while establishing a reusable framework for future digital health applications.