Events Calendar

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AACP Annual Meeting
2015-07-11 - 2015-07-15    
All Day
The AACP Annual Meeting is the largest gathering of academic pharmacy administrators, faculty and staff, and each year offers 70 or more educational programs that cut across [...]
Engage, Innovation in Patient Engagement
2015-07-14 - 2015-07-15    
All Day
MedCity ENGAGE is an executive-level event where the industry’s brightest minds and leading organizations discuss best-in-class approaches to advance patient engagement and healthcare delivery. ENGAGE is the [...]
mHealth + Telehealth World 2015
2015-07-20 - 2015-07-22    
All Day
The role of technology in health care is growing year after year. Join us at mHealth + Telehealth World 2015 to learn strategies to keep [...]
2015 OSEHRA Open Source Summit
2015-07-29 - 2015-07-31    
All Day
Join the Premier Open Source Health IT Summit! Looking to gain expertise in both public and private sector open source health IT?  Want to collaborate [...]
Events on 2015-07-11
AACP Annual Meeting
11 Jul 15
National Harbor, Maryland
Events on 2015-07-14
Events on 2015-07-20
Events on 2015-07-29
2015 OSEHRA Open Source Summit
29 Jul 15
Bethesda
Articles News

Hospitals are now aware of the development process for several health AI technologies. Will anything change as a result?

EMR Industry

A new federal regulation mandates that certain health AI makers reveal information about bias, testing, and other topics.

They know what the ones and zeroes buzzing away in the background are up to, don’t they? Clinicians click away at workstations in hospitals.

In actuality, physicians and health systems frequently lack critical knowledge about the algorithms they use for tasks like anticipating the start of serious illnesses. Federal regulators now mandate that electronic health record (EHR) businesses provide clients with a wide range of information regarding artificial intelligence tools in their software, which proponents say is a positive start.

Clinicians should have been able to see a model card, often known as a “nutrition label,” since the beginning of January. This label should include information on the variables that go into a prediction, whether a tool has been evaluated in the real world, how the tool’s authors addressed potential bias, cautions about improper use, and more.