Impact of emerging technologies on radiology makes headlines
This week’s articles include: new audit shows causes of unnecessary CT and MR exams; analytics solutions expected to improve quality of care; photoacoustic imaging could guide breast cancer removal; population health management is the top driver of data analytics; and the debut of the first fully autonomous radiology interpretation system.
New audit pinpoints causes of ‘wasteful’ unnecessary scans – AuntminnieEurope
Radiologists’ failure to check the validity of requests for CT and MRI scans, along with ignorance among referring doctors of appropriateness criteria for imaging examinations, are the most important reasons for costly inappropriate requests of radiological exams, a new study from Saudi Arabia found. An audit of 674 CT and MRI scans revealed that 25% were inappropriate.
Recent iterations of Gartner’s Hype Cycle have placed “big data” and “advanced analytics with self-service delivery” at the peak of inflated expectations; “machine learning” now sits at the top of the curve. At HIMSS17, a vast array of IT solutions and educational presentations were in some way connected with analytics. The practice of modern medicine requires imaging analytics to deliver quality care.
A new technique based on photoacoustic imaging could help surgeons determine whether they’ve removed all cancerous tissue during breast surgery, according to a study. Researchers developed the technology to scan a tumor sample and produce images accurate enough to determine whether a tumor has been completely removed. They are working to make the technique fast enough to be used during surgery.
Data analytics frenzy fueled by population health management – Health Intelligence Network
With reimbursement for healthcare services increasingly based on clinical outcomes, patient experience and cost of care, the motivation to slice and dice patient and population data has never been stronger. Population health management is the top driver of data analytics for more than a quarter of respondents to the 2016 Data Analytics and Integration Survey by the Healthcare Intelligence Network.
A company called DeepRadiology announced the first “fully autonomous radiology interpretation system” at RSNA 2016. Whether the system described is real, hype, or somewhere in between, it illustrates the need for radiology to respect emerging technology.
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