AI-powered tools support the transition to value-based care (VBC) by surfacing insights from multiple data sources – including claims, pharmacy, social determinants of health, and EHR data – to inform timely interventions and close care gaps.
AI algorithms can translate what used to be a vast array of disparate data points into predictive models that highlight patients at higher risk of missing critical care, such as preventive screenings, or are at higher-than-average risk of being diagnosed with a new or worsening chronic condition.
Predictive models can also help patients slow the progression of chronic disease, avoid disease onset entirely, or mitigate the chances of a serious event, such as a stroke or heart attack.
When in-depth insights on patient risk factors are available to care teams and clinicians, it facilitates care coordination for more targeted interventions, diagnoses, and treatments.
AI tools can also improve primary and preventive care by minimizing administrative burdens, maximizing physician resources to ensure patients receive high-quality care while freeing care teams from time-consuming manual tasks.
As the use of AI tools grows in health care practices, so does the need to maintain the highest data security standards, ensuring patient privacy and HIPAA compliance.
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