Clinical AI Is No Longer A Matter of Innovation For Providers. It’s A Matter Of Survival.

By Jay Deady, CEO, Jvion
Twitter: @JvionHealth

For the last decade, clinical artificial intelligence (AI) has been seen by many as a promising new technology. However, adoption really only picked up across provider organizations that view themselves at the cutting edge of care. Most providers are more apprehensive, waiting until the technology matures before they invest.

In a pandemic, innovation is no longer an option.

Telehealth is the perfect example. After a decade of sluggish adoption and a doctrine of wait-and-see, providers were forced to shift almost all their care to telehealth overnight. HHS reported that the ratio of Medicare primary care visits conducted via telehealth grew from .1% in February to an astounding 43.5% in April. For private insurance, telehealth claims increased by 8,336% nationally in April compared to the year before.

This rapid innovation allowed providers to stay open and continue seeing patients through the worst of the pandemic. Now, experts agree telehealth is here to stay. Frost & Sullivan predicts seven-fold growth in telehealth by 2025, with demand growing by 64.3% in 2020 alone.

But the need to innovate goes much deeper than the need to maintain continuity of care. For the industry to prosper, AI needs to follow the same growth trajectory as telehealth.

The American Hospital Association (AHA) predicts hospitals will lose a total of $323 billion in revenue this year due to the pandemic. As a result, 40% of providers are at risk of closing. Health systems will need to innovate to survive — or risk joining the more than 42 hospitals that have already closed this year.

As the industry shifts to value-based revenue models, providers’ financial survival will hinge on whether they can efficiently use their resources to improve patient outcomes and reduce avoidable utilization. This is where clinical AI can drive cost savings.

Clinical AI excels at analyzing clinical and socioeconomic data to identify patients whose risk of deterioration would not otherwise be recognized by clinicians. With this insight, care teams can intervene earlier in the patient’s risk trajectory to prevent avoidable hospital admissions, readmissions, and other healthcare utilization, ultimately improving patient outcomes and lowering the costs of care.

An important difference between clinical AI and traditional predictive analytics tools is that clinical AI can integrate data beyond the patient record, particularly data on social determinants of health (SDOH). SDOH factors, such as income, transportation access, and whether the patient lives alone, are often invisible to providers, but play a critical role in patient vulnerability.

With clinical AI, providers can account for hidden SDOH factors to reveal patients with invisible risk. They can then personalize care plans to each patients’ unique clinical, socioeconomic, environmental, and behavioral circumstances.

This ability to identify vulnerable patients and proactively manage their care is increasingly important in light of the pandemic. 48% of Americans reported delaying medical care due to COVID-19, and many with chronic conditions or undiagnosed illnesses are likely to deteriorate. With clinical AI, providers are more equipped to proactively intervene with vulnerable patients and prevent patient deterioration, avoidable utilization and the associated costs.

Providers will also need to be proactive in preventing uncompensated care. Millions of Americans who recently lost their jobs also lost their health insurance. This is another area where clinical AI can support. By analyzing SDOH data, clinical AI can identify patients in a provider’s population who may struggle to pay for their care. Providers can then help these patients enroll in Medicaid or other financial assistance programs before they need care.

The financial pressures on providers didn’t start with the pandemic, and they won’t end with the pandemic either. Inefficiency, uncompensated care and avoidable utilization will continue to impact providers’ ability to stay afloat. In addressing these persistent challenges, clinical AI will be a vital tool for financial survival, now and into the future.

Countless communities are depending on their local hospitals to survive the pandemic. Providers cannot afford not to innovate.