Artificial Intelligence (AI) in healthcare is an umbrella term used to describe the application of machine learning algorithms and other cognitive technologies in medical settings. In the simplest sense, AI refers to when computers and other machines mimic human cognition, and are capable of learning, thinking, and making decisions or taking actions.
More and more, research suggests that patient treatment results rely on social determinants of health (SDoH), including economic stability, education, access to transportation, and access to quality health care. According to the Centers for Disease Control and Prevention (CDC), SDoH “are conditions in the places where people live, learn, work and play that affect a wide range of health and quality-of-life risks and outcomes.” The impact of social determinants are becoming more relevant as more payers look toward value-based care models, which prioritize the quality and outcomes of health care rather than the amount of health care patients receive.
Despite the relevance of SDoH to patient outcomes, physicians lack the training and tools to analyze SDoH, which means that these important factors are often left out of clinical health care decisions. That’s where Cardinal Health comes in.
Part of the Cardinal Health’s NavistaTM TS platform, Jvion CORETM uses AI and machine learning technology to analyze patients’ clinical and socioeconomic data to improve patient outcomes.
To assist providers with incorporating SDoH into treatment decision making, Cardinal Health partnered with Jvion, a clinical AI developer, to deliver an AI and machine learning tool within Cardinal Health’s NavistaTM TS point of care platform. The result is a decision support analysis that could identify high-risk SDoH profiles that might negatively impact patient treatment outcomes and increase the risks of emergency department visits and hospitalizations. (NavistaTM TS is a fully integrated resource for value-based care decisions. It helps oncology practices balance clinical and financial decision-making in one place through connected tools and data-driven insights.)
In order to address whole patient health, the tool works by integrating providers’ electronic health records systems (EHRs) and merging patients’ clinical data with external data from public and private sources (such as the U.S. Census Bureau, the Department of Housing and Urban Development, the Environmental Protection Agency, the Department of Agriculture, medical records, labs, etc.) to predict the risk of health deterioration in patients, and make connections providers might not have the time to analyze.
“Using AI-driven insights alerts the oncologist to patient risks outside of traditional clinical profiles, thereby decreasing negative outcomes that increase cost and diminish quality of life,” said Bruce Feinberg, DO, vice president and chief medical officer at Cardinal Health Specialty Solutions.
Within Cardinal Health’s technology solution for value-based care, NavistaTM TS, the JVION CoreTM technology is used by providers to identity patients at greater risk of mental health crises, emergency department visits and hospitalizations. Cardinal Health’s research team has closely tracked pilot programs to examine how effective the predictive AI technology is; the research team has recently presented results at numerous conferences, sharing these results that oncology practices are now seeing:
Cardinal Health is not only committed to bringing advanced technologies to physicians to assist them in point of care decision support, but also to providing the research needed to optimize these solutions to improve patient outcomes and the patient experience.