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VANCOUVER — A new study from the Fraser Institute says artificial intelligence could significantly improve productivity in health care, but only if health systems are redesigned to integrate the technology across entire care models rather than in isolated applications.
The report, released Thursday, argues artificial intelligence already plays a role in areas such as medical research, diagnosis, administration and clinical documentation, but current uses tend to be limited to specific tasks and produce only incremental gains.
Author Avi Goldfarb, a professor at the University of Toronto’s Rotman School of Management, says larger improvements would come from system wide changes that place AI at the centre of how health care is organized and delivered.
The study points to existing tools such as AI assisted clinical note taking, which can save physicians time by automatically recording and documenting patient interactions. It suggests broader integration could allow AI to update records, coordinate follow up appointments, manage prescriptions and flag test results as part of a single workflow.
In research settings, the report says machine learning is already used to analyze data and review scientific literature. It highlights the potential for so called self driving laboratories, where artificial intelligence designs and adjusts experiments in real time to accelerate drug discovery and treatment development.
The study concludes that while artificial intelligence offers major potential for health care systems, realizing those gains will depend on whether decision makers pursue system level redesign while maintaining patient care as the primary focus.
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