Waste in healthcare is estimated to be about a fourth of all the money spent on healthcare each year. One of the key areas of waste is in unneeded testing or routine tests that are rarely used. The number of tests can add up for an individual patient and result in significant costs that do not contribute to the quality of care or positive patient outcomes.
AI based solutions within the Refactor Health platform can be used to help clinicians make better decisions by narrowing the types of tests that are likely to be useful for a patient. AI models can be created using volumes of patient information from healthcare systems together with data from pharmaceutical companies to predict likely test results a given patients. This model is then deployed into an AI-driven application that can provide indications of which tests are likely to produce definitive or valuable results based on the patient’s medical history and current symptoms.