CohortIQ

About

CohortIQ ingests health and open government datasets, uses machine learning to identify chronic patients likely to have unnecessary hospital admissions, and routes them to community interventions while automating hospital analytics.

Mission

CohortIQ ingests health data and open government datasets and runs them through machine-learning systems to identify patients who represent ""unnecessary admissions."" The company is initially targeting people with chronic illnesses such as renal failure and diabetes who can be better treated in community settings. Its product aims to keep frequent hospital users out of hospital and direct them into intervention programs, freeing up beds. Prior to the DataStart win the concept was an idea from co-founder Ian Tebbutt and two others; the team used hospital episode data from data.gov.au to develop the system. CohortIQ won AU$200,000 in seed funding via the public–private DataStart initiative, and says the money will be used to further develop automation and scalability. The founders describe the problem as global — noting 235,000 unnecessary admissions per year — and aim to make hospital analytics simpler and more automated so the solution can scale.

Quick Facts