AI may help medical providers adapt to reduce and increase care as needed. (Source:

Patient Numbers Climb while Hospital Compensation Dwindles

Given we are living in such a medical disaster across the globe, it might be hard to imagine that the medical field is having money problems. That is to say, doctors are making less money in a year where their services are probably more in demand than ever.

Revenue from elective procedures still lags behind pre-pandemic levels, and the American Hospital Association (AHA) predicts hospitals will lose a total of $323 billion this year. These losses put 40% of providers at risk of closure.

Those numbers are from an article found at And though they are not good news, the article points out that the use of AI may provide some relief for both patients and medical workers as well. And the idea is to use AI to research a thousand points of data on a patient and compare it to millions of other points of data. And that has costs as well.

Unfortunately, the problem of uncompensated care will only get worse as the pandemic progresses and its economic toll worsens. In the first half of 2020, 43% of Americans were uninsured, had gaps in their insurance, or were unable to afford their out-of-pocket costs and deductibles. By the end of the year, 10 million Americans could lose their health insurance due to pandemic-related job losses, adding to hospitals’ uncompensated care woes.

Other costs of uncompensated care affect patients who are unable to afford their care. They are more likely to skip important preventive care visits or stop taking life-saving medications, worsening their outcomes. Under value-based care models, providers will face financial penalties for these worsening outcomes — when they can least afford it.

“Amidst the financial headwinds of 2020, most hospitals can’t afford to sit idly by and hope their patients independently enroll in Medicaid, an affordable ACA plan or a financial assistance program. To prevent uncompensated care, providers need to proactively find patients who may need care they can’t afford, and help them find a way to pay for their care before they need it.”

AI: The Antidote for Uncompensated Care

Prescriptive clinical AI is a powerful tool that can help providers prevent uncompensated care by identifying patients likely to need significant care, seek that care from their specific facility, and lack the means to cover the costs. The clinical and financial insights help providers address the needs of their patient population more holistically and proactively. It presents an opportunity to reach out and counsel patients on their options for affordable care, whether that be Medicaid enrollment, a low-cost plan from an ACA exchange, or a financial assistance program — all before the provider is put in the position of sending a bill that will go unpaid.

Prescriptive analytics go beyond traditional predictive analytics, adding value by identifying the people on the cusp of being high-risk, not just those with known risks, and then prioritizing actions to mitigate the risk. Clinical AI does this by analyzing thousands of data points per patient and comparing them with a database of millions of other patients, AI can predict patient risk that would otherwise be invisible to providers. The more data is processed by the AI, the more accurately it can predict which patients are likely to deteriorate or require hospitalization.

Medicaid can be a powerful tool for stopping uncompensated care. In states where Medicaid expanded, uncompensated care decreased. If used to its fullest extent, Medicaid can help vulnerable patients afford care while preventing providers from losing the revenue they need to stay afloat. However, nothing is perfect, and not all patients eligible for Medicaid are aware of it.

Although many data analytics tools are based only on clinical data from electronic health records, socioeconomic data should not be overlooked, as it can be a powerful predictor of patient risk. In fact, a study published this year in the American Journal for Managed Care found that AI trained on socioeconomic determinants of health (SDOH) data alone can accurately predict inpatient and emergency department utilization.

If you or someone you know is on Medicaid or Medicare, then you might find the information in this article very useful. It can be found in the link below.