For decades, patients and providers have operated mostly in a “sick care” system, where people engage with providers and facilities only after they experience adverse health events. That happened for many reasons, but the primary one is the incentive structure. When payments are structured as fee-for-service, there is little incentive for providers to encourage earlier intervention and preventive care because such measures reduce patient transaction volume.
As VBC takes root, HDOs and providers are increasingly embracing VBC's capacity to assess patient health holistically, proactively identify potential health risks, and intervene before health issues become critical problems that require emergency or hospital care. Predictive analytics can help providers find this information faster and easier. Analytics tools designed to predict risk can identify trends, flag deviations, and anticipate potential health complications down to the individual patient level. These software tools can then create cohorts with patients for whom intervention could minimize complications or prevent diseases entirely. Providers and care teams can then develop strategies, such as regular check-ups and disease management, to address issues before they snowball into acute care events. Eliminating the need for an ER visit or a hospital admission significantly lowers costs and translates to better outcomes for most patients.
Disease prediction and mitigation AI prediction models can pinpoint undiagnosed cases and inaccurately coded records for the leading causes of death in America – diabetes and heart disease. This predictive capability provides another tool for providers to engage with patients flagged as high-risk.
For example, AI algorithms can comb through historical data to look for indications that a person has or will develop a chronic condition like diabetes or coronary artery disease. The model assigns a risk score from 0 to 100, flagging those surpassing a score of 50 as "likely" to develop the condition within the next 12 months. It can also flag patients who may already have a chronic condition, but it is not properly coded in their health record, which could negatively impact their future care.
Physicians can use the information alongside other data they have about a patient – such as family history and lifestyle behaviors – to recommend additional care or lifestyle changes that can mitigate the risk of disease, increase surveillance, or take other action to improve health.
