Applied Evidence

An FP’s guide to AI-enabled clinical decision support

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The FDA clearance statement for this technology7 limits its use, emphasizing that it is intended only as a screening tool, not a stand-alone diagnostic system. Because ­IDx-DR is being used in primary care, the FDA states that patients who have a positive result should be referred to an eye care professional. The technology is contraindicated in patients who have a history of laser treatment, surgery, or injection in the eye or who have any of the following: persistent vision loss, blurred vision, floaters, previously diagnosed macular edema, severe nonproliferative retinopathy, proliferative retinopathy, radiation retinopathy, and retinal vein occlusion. It is also not intended for pregnant patients because their eye disease often progresses rapidly.

A large-scale validation study performed on data from Kaiser Permanente Northwest found that it is possible to estimate a person's risk of colorectal cancer by using age, gender, and complete blood count.

Additional caveats to keep in mind when evaluating this new technology include that, although the software can help detect retinopathy, it does not address other key issues for this patient population, including cataracts and glaucoma. The cost of the new technology also requires attention: Software must be used in conjunction with a specific retinal camera, the Topcon TRC-NW400, which is expensive (new, as much as $20,000).

Eye with artificial intelligence IMAGE: ©GETTY IMAGES

Speaking of cost: Health care providers and insurers still question whether implementing AI-enabled systems is cost-­effective. It is too early to say definitively how AI and machine learning will have an impact on health care expenditures, because the most promising technological systems have yet to be fully implemented in hospitals and medical practices nationwide. Projections by Forbes suggest that private investment in health care AI will reach $6.6 billion by 2021; on a more confident note, an Accenture analysis predicts that the best possible application of AI might save the health care sector $150 billion annually by 2026.8

What role might this diabetic retinopathy technology play in family medicine? Physicians are constantly advising patients who have diabetes about the need to have a regular ophthalmic examination to check for early signs of retinopathy—advice that is often ignored. The American Academy of Ophthalmology points out that “6 out of 10 people with diabetes skip a sight-saving exam.”9 When a patient is screened with this type of device and found to be at high risk of eye disease, however, the advice to see an eye-care specialist might carry more weight.

Screening colonoscopy: Improving patient incentives

No responsible physician doubts the value of screening colonoscopy in patients 50 years and older, but many patients have yet to realize that the procedure just might save their life. Is there a way to incentivize resistant patients to have a colonoscopy performed? An ML-based software system that only requires access to a few readily available parameters might be the needed impetus for many patients.

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