28.5 million people are uninsured in the US. Can Radiology AI play a role in reducing the costs of MRI scans?

Outpatient MRI in the US – The Case of Insured vs. Uninsured

U.S. census data shows that in 2017, 8.8 percent of people did not have health insurance at any point during the year. This may seem like a small percent, but it equates to 28.5 million individuals without access to coverage for necessary medical tests and procedures.

Source: U.S. Census Bureau, 2017

Health insurance coverage in the US healthcare system directly affects the treatment of individuals requiring outpatient MRI. The experience of insurance “haves” and “have nots” differ greatly in terms of:  

  • where they can go to receive treatment;
  • what they can do once they are diagnosed; and
  • the patient’s ability to negotiate affordable services.

Treatment Costs for Insured vs. Uninsured Patients

Emergency room physicians are required by law (1986 EMTAL Act)  to order and provide medical screenings they deem urgent, regardless of patient insurance status. However, many patients with serious but not life-threatening conditions fall through the cracks. If a patient’s MRI script is categorized as “routine” rather than “urgent,” there is a high probability that the patient will never follow through with it due to the high cost and other factors.   

Individuals requiring routine outpatient MRI are given a referral script without a specific timeline, and there generally is no follow-up from the referring physician once the patient is released from care in the hospital. A healthcare consumer must then negotiate many obstacles, including:

  • whether or not they have health insurance
  • whether or not the health insurance company will cover the MRI
  • whether the health insurance company will require another service, such as x-rays, prior to approval
  • finding an approved provider and determining whether the provider is in or out of network
  • a lack of understanding if the MRI provider/equipment is of good quality
  • a lack of information about the procedure’s risks or benefits how much the copay or full cost is

The cost of an MRI also depends on the geographic location of the patient. For example, an MRI in Mississippi can cost $97.00; in comparison it can be as much as a staggering $2000 in Florida (Business Insider, 2008). There is a stark difference between the costs faced by those with and without healthcare coverage.

An MRI from a provider in-network can cost $100 or lessThe costs for an MRI performed in the hospital can be as much as $2300.
An insured individual may have some choice of options and might be able to shop around for a lower price, but out of network costs could spiral to as much as $2000.The patient does not have negotiation power to choose the location and cheaper options.

How Can AI Play a Role in Improving Outcomes for Patients?

 It is evident that the insurance “have nots” can find themselves in a precarious healthcare situation often resulting in astronomical bills for those who can least afford to pay them. Moreover, the chance of such individuals getting treatment outside of a hospital setting is greatly reduced compared to their insured counterparts.

What if there was a machine-learning algorithm that could quickly interpret clinical MRI images with the ability to provide specific, quantifiable information? What if the AI solution could also produce a radiology report for the referring physician and improve clinical outcomes for the patient, both in emergent and outpatient situations?

Perhaps Radiology AI can alleviate some of the costs and time constraints associated with receiving an MRI scan, whether in the hospital or out.

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