Informatics

The goal of health informatics systems is to enable smooth transfer of data and cybersecurity across the healthcare enterprise. This includes patient information, images, subspecialty reporting systems, lab results, scheduling, revenue management, hospital inventory, and many other health IT systems. These systems include the electronic medical record (EMR) admission discharge and transfer (ADT) system, hospital information system (HIS), radiology picture archiving and communication systems (PACS), cardiovascular information systems (CVIS), archive solutions including cloud storage and vendor neutral archives (VNA), and other medical informatics systems.

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Julius Bogdan, vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America, explains considerations for healthcare system information technology (IT) management teams on the implementation of artificial intelligence (AI). He also discusses ideally how AI should be integrated into medical IT systems, and some of the issues AI presents in the complex environment of real-world patient care." #AI #HIMSS

VIDEO: How hospital IT teams should manage implementation of AI algorithms

Julius Bogdan, vice president and general manager of the HIMSS Digital Health Advisory Team for North America, explains considerations for healthcare IT teams on the implementation of artificial intelligence (AI).

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Concerns raised over how hospitals can validate radiology AI algorithms

As artificial intelligence (AI) adoption expands in radiology, there is growing concern that AI algorithms need to undergo quality assurance (QA) reviews.

Bibb Allen, MD, FACR, chief medical officer of the American College of Radiology (ACR) Data Science Institute, and former ACR president, explains how hospitals or radiology departments can conduct quality assurance (QA) assessments on artificial intelligence (AI) algorithms they adopt to ensure they are accurate. The ACR established the Assess-AI Registry and AI-Lab to help with validating and tracking AI QA for FDA-cleared algorithms.

VIDEO: Validation monitoring for radiology AI to ensure accuracy

Bibb Allen, MD, FACR, Chief Medical Officer of the American College of Radiology (ACR) Data Science Institute, and former ACR president, explains how hospitals or radiology departments can conduct quality assurance assessments on artificial intelligence algorithms they adopt to ensure they are accurate. 

An overview of artificial intelligence (AI) in radiology with Keith Dreyer with the ACR. Images shows a COVID-19 lung CT scan reconstruction from Siemens Healthineers. #AI #radAI #ACR

VIDEO: Overview of radiology AI by Keith Dreyer

Keith J. Dreyer, DO, PhD, FACR, American College of Radiology (ACR) Data Science Institute Chief Science Officer, explains the state of AI in radiology in 2022. 

radiology reporting EHR health record CDS AUC

Structured reporting templates reduce turnaround times by as much as 35 minutes

A new paper published in Academic Radiology details one institution’s transition from free text to structured reporting templates and the resultant departmental impact.

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SIIM 2022: OTech's training assets acquired by SIIM

In addition to the eBooks, study guides and a Virtual Hospital Platform simulator for hands-on training that were acquired, SIIM will now also own various “go to market” courses in subjects such as PACS, DICOM, HL7 and FHIR.

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SIIM 2022: 5 ways voice-triggered macros can improve radiologist workflow

Voice-triggered macros are spoken voice commands that trigger a subsequent command in order to perform a specified task. Software that achieves this is easily implemented into workflows and can complete virtually innumerable tasks. 

SIIM 2022: 7 ways to be ever-prepared for cyberattack

Some decisions after a cyberattack are reactive and made on the fly, but imaging operations can take a number of steps ahead of time to plan for unplanned downtime and limit the impact of a temporary outage.

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