Beyond “proof of concept” – machine learning and related tools applied to transactional data extracts from clinical and business information systems – in service of Quality Assurance/Quality Improvement.

The program of eight interlocking applied research projects employs various machine learning (ML) methodologies with large volumes of Island Health cross-continuum patient-service encounter data inside the Island Health firewall. The objective is to generate ready-for-use products that will promote better outcomes via more effectively optimized interoperation of IH programs. As well, the work targets objectives of health system sustainability by identifying, counting and costing out processes that are difficult to reconcile with established clinical care guidelines. Complementing more usual diagnostically-based approaches, the project seeks to classify persons in terms of cross-continuum patterns of service utilization (PSUs), relate PSUs to outcomes, and employ PSUs as foundational units for tools that can be employed to build out evidentiary foundations for Quality Assurance/Quality Improvement targeting and approaches. Information products are expressed in an intuitive manner, to provide direct support for translation of generic service system strategies into tactically focused Quality Assurance/Quality Improvement initiatives.

Faculty Supervisor:

Alex Thomo;Lloyd Elliott;Venkatesh Srinivasan

Student:

Partner:

Vancouver Island Health Authority (Victoria, BC)

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology

University:

Simon Fraser University; University of Victoria

Program: