Catastrophic personal injuries are life-altering events in Lexington, Kentucky. Under U.S. law, catastrophic personal injury prevents a person from gainful work. These types of injuries might involve a severed neck, a permanent functional disability or a fatality. Poor medical care and misdiagnosis are common causes of a catastrophic injury.
Radiology malpractice in oncology
Oncology is the most common reason for radiology malpractice cases that involve high-severity harm. Only about 4% of national imaging is cancer-related, but 44% of radiologic cases are diagnosis disputes. Reports estimate that 40,000 to 4 million people in the U.S. will suffer a serious misdiagnosis-related injury annually.
Medical malpractice trend
One studied database contains medical malpractice claims from commercial and captive insurers around the U.S. Cancers account for 37.8% of high-severity diagnostic errors. Vascular events and infections are the next highest high-severity diagnostic errors.
For reports examining radiology malpractice from 2008 to 2017, radiology was a part of 3.9% of all claims. Of those claims, 12.8% were diagnostic allegations. Oncology was in 44% of the radiology cases with misdiagnosis. The oncology errors were higher than other medical conditions. In cases involving the patient disagreeing with the diagnosis, the case harmed the patient 79% of the time. Non-oncologic cases only ended in harm to the patient 42% of the time.
About 80% of oncologic radiology malpractice suits involve misinterpreting images. CT, MRI and mammography were the most common. After the paid claims and advanced imaging use, there were an extra 1,389 exams at a state level. The exams didn’t include interventional radiologist claims and nuclear medicine. Reducing cancer-related malpractice claims could limit wasteful imaging.
Some ways to lower cancer misdiagnosis include subspecialty oncology imaging certification, oncologic imaging fellowships and better AI. Community practices handle large volumes of oncologic imaging, so with better education and safer AI applications, patient care could be less error-prone.