“AI is making the impossible possible” – a striking statement that most of us come across while reading about AI. It is one of the most awaited and glorified technologies of the era.
But the billion-dollar question is, can AI actually make the impossible possible? Or is it just another overhyped statement?
While many industry experts believe that AI has immense potential and will make revolutionary changes in the healthcare industry, there are still those who think that the technology is oversold.
Even those skeptical about AI’s capabilities changed their opinion in light of the recent pandemic.
To put things in perspective, consider what would have happened if the current COVID-19 pandemic occurred a decade ago when telemedicine and AI were in their nascent stages?
If one were to guess, the COVID-19 death rate would have doubled, if not tripled. We would have waited at least for a minimum of 5 years before getting an appropriate COVID vaccine. Moreover, containing the fast-spreading lethal virus would have been an uphill battle.
Clearly, AI is here to make profound changes, particularly in the field of healthcare.
AI is not the first technology to reshape or advance healthcare. There are numerous other technologies like CAD, cloud, augmented reality, 3-D printing, nanotechnology, robotics, etc., that have improved healthcare delivery and patient care.
But why is AI alone the most glorified and most awaited?
Well, key players, not just in healthcare but from other industries as well, believe that AI can not just mimic human intelligence, but can also augment the speed and efficiency of their workforce, much more than any other technological innovation.
And this conviction has led to health systems experimenting with the potential of AI in areas like spine care. And here’s how experts believe AI can make a difference in spine reporting:
2. Top use cases of AI in spine injury cases
2.1. Detection and localization of vertebral fractures
Nearly a million vertebral fractures occur in the U.S. every year. The most common site of spine fracture is the neck or the cervical spine.
Cervical spine fractures are highly common among the elder generation and can be extremely difficult to determine on images due to conditions like osteoporosis and superimposed degenerative diseases.
Quick detection and localization of any vertebral fracture are paramount to prevent neurological deterioration or paralysis after trauma. Experts from health tech firms and health systems believe AI can expedite the process of detection and localization of vertebral fractures – a difficult task even for highly-skilled radiologists.
2.2. Avoid unnecessary spine surgeries
Over 90% of spine problems can be successfully treated non-surgically. But, for the remaining 10%, physicians have to choose the most effective and appropriate surgery.
Surgeries to treat back pain don’t just mean a traditional cut-open surgery. It could also be a minimally invasive procedure, in which small incisions and tools are used to treat spine conditions of severity, mild to moderate.
For instance, in the case of herniated discs, the damaged part of the disc can be removed through endoscopy. But this is possible only when the size of the herniated disc is below 2 to 3mm. If the size is bigger than 3mm, then a cut-open surgery is the optimal solution.
So to opt for the right surgery it is paramount the right diagnosis is made. But as humans, we have an innate nature to make biased decisions that are mostly, consciously and unconsciously, shaped by what motivates us. Hence, even a well-experienced radiologist can also interpret a herniated disc of 3 mm to be 4 mm during eyeballing.
This is why there is an increased amount of inter-observer and intra-observer variability in the radiology world.
With the help of AI, such inter- and intra- observer variabilities can be reduced dramatically. Apart from increasing the accuracy of diagnosis, AI can also enable physicians to choose the appropriate surgical treatment for back pain and help in avoiding the sheer chance of unnecessary surgeries and related complications.
2.3. Prevent health insurance fraud claims
Despite all the effective measures taken by both insurance providers and health systems, they are still struggling to shield themselves from fraudsters. According to the National Health Care Anti-Fraud Association, healthcare fraud costs the U.S. nearly $68 billion annually, which is 3% percent of the nation’s annual healthcare expenditure.
Both insurance providers and healthcare providers lack the resources and bandwidth to scrub through thousands of medical claims every day to effectively detect fraud claims.
AI algorithms when trained on health insurance fraud historical data can screen all the insurance claim documents quickly and red flag the suspicious ones.
In the case of spine injuries, health insurance fraud occurs mostly in the form of:
- Identity theft
- Adding treatments that were not necessary
- Including treatments that were not delivered or administered
Training AI algorithms on the relevant procedures for different spine conditions will help health systems and insurers quickly identify fraudulent claims associated with spine injuries.
By preventing health insurance frauds with the help of AI, health systems and insurance providers can prevent other fallouts like increasing insurance costs, delays in claim settlement due to strict scrutiny, and unintended customer harassment.
3. Summing Up
Healthcare has been evolving since the technology revolution. Since then breakthroughs in healthcare have always outnumbered setbacks and failures. In the new age of AI, the healthcare industry is likely to take the next big step in spine care. To start with, health systems are now more eager to try out AI applications in their radiology workflow.
A real-time example would be Synapsica’s solutions, Spindle and SpindleX, AI tools to automate spine reading and reporting that are becoming increasingly popular.