Can Big Data Prevent a Medical Misdiagnosis?
Forbes recently published an article on how software can pair patients with doctors who are most likely to give them an accurate diagnosis. The article explains how Grand Rounds, a mobile app, can help people find doctors in their area who have the most experience treating specific health conditions. According to the creators of Grand Rounds, the service can help decrease the chances of a misdiagnosis.
Grand Rounds uses a database of 700,000 physicians, or about 96 percent of all doctors in the United States. The app then uses insurance-claims data and biographical information on the doctors to help patients make a selection. For example, a patient suffering chronic headaches could look for a doctor in their area who specializes in diagnosing neurological conditions.
The theory behind the app, is that patients can select doctors who are most likely to offer a correct diagnosis. In addition, the app allows patients to find doctors who will offer a second opinion. Patients, companies and health care providers can use Grand Rounds.
How Might Big Data Help Provide an Accurate Diagnosis?
Grand Rounds is not the first organization or company to take notice of using big data to provide an accurate diagnosis. Companies like Google are creating artificial intelligence programs that can pour through tens of thousands of case files to diagnose conditions like diabetic retinopathy.
Google’s AI program learned what diabetic retinopathy looked like by reviewing 128,175 images of the disease. According to a study published in the Journal of the American Medical Association, the program can detect diabetic retinopathy on-par with human ophthalmologists.
Misdiagnosis is the most common medical error in the United States. If companies can find a way to prevent misdiagnosis, they may help save lives.