The American College of Cardiology (ACC) has selected HealthReveal’s personalised clinical AI solution for its TRANSFORM studies.
The study data will be utilised for recommending life-saving patient care interventions to augment physicians’ adherence to guideline-directed medical therapy (GDMT), predict impending adverse cardiovascular events and enhance patient outcomes.
This collaboration will cover three TRANSFORM programmes. The first study, TRANSFORM HFrEF, will offer GDMT for individuals who have heart failure with reduced ejection fraction (HFrEF).
This study will enrol around 3,072 patients at various health systems. Each subject will be part of the study for six months.
It will span three years from first patient to first comprehensive reporting and the last patient visit is anticipated in the middle of next year.
In TRANSFORM HFrEF, the potential of Reveals will be assessed to improve GDMT adherence, optimise patient care and lower future adverse events.
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By GlobalDataThe second trial, TRANSFORM CVRiD, plans to drive meaningful improvements in cardiovascular outcomes in Type 2 diabetes patients. This 12-month study is anticipated to commence in September this year while a third study will be announced soon.
ACC president Dipti Itchhaporia said: “Guidelines clearly outline the most appropriate treatments for HFrEF patients, but we know that these patients are often under-treated and adherence to guidelines is suboptimal.
“Through this study and collaborations that optimise technology-enabled approaches, we’re addressing this problem and transforming the care these vulnerable patients receive.”
As per a 2018 study, below 25% of HFrEF patients received GDMT recommended pharmacotherapies, while less than 1% were given a correct prescription at medically appropriate doses.
HealthReveal founder and CEO Lonny Reisman said: “The TRANSFORM model will fundamentally change the way medical guidelines for cardiovascular diseases are developed and implemented.
“It is an innovative approach to deploying current guidelines into clinical practice and measuring their real-world impact.”