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Recent Imaging Platform Collaboration Highlights EHR Solutions

National Decision Support Company (NDSC) announces collaborations with MEDITECH and McKesson Health Solutions.

Source: Thinkstock

By Elizabeth O'Dowd

- National Decision Support Company (NDSC) announced its collaboration with MEDITECH to integrate its CareSelect Imaging platform with MEDITECH’s electronic health record (EHR) solutions.

The federal mandate going into effect on January 1, 2018 will require healthcare providers to consult the Appropriate Use Criteria when ordering Medicare Part B advanced imaging services.

Through CareSelect, MEDITECH clients can access a list of guidelines covering a range of imaging conditions and the required functionality to generate payable claims.

The collaboration gives MEDITECH supported integration and access to NDSC’s CareSelect Imaging Clinical Decision Support Mechanism through the MEDITECH EHR. The support of NDSC’s mechanism enables compliance with CMS requirements outlined in the Protecting Access to Medicare Act of 2014. The act requires consultation of Appropriate Use Criteria when ordering advanced imaging tests for Medicare patients.

"Leading EHR vendors and health systems nationwide trust CareSelect Imaging to provide a complete solution to the requirements of the Protecting Access to Medicare Act and to power imaging stewardship programs," NDSC CEO Michael Mardini said in a statement. "MEDITECH's decision to work with NDSC will create positive impact across their large network of customer sites."

NDSC’s CareSelect Imaging provides a set of imaging Appropriate Use Criteria and indications that contain all medical specialty societies approved as qualified Provider-Led Entities by CMS. These societies include the American College of Cardiology, the National Comprehensive Cancer Network, and criteria from the American College of Radiology.

NDSC’s Comprehensive criteria supports 15,000 clinical end points and ensures Appropriate Use Criteria are available for advanced imaging orders to comply with CMS requirements. The solution also complies with CMS requirements for consultation for all advanced diagnostic imaging and covers CMS-established Priority Clinical Areas.

NDSC announced another partnership with McKesson Health Solutions that will leverage NDSC’s content delivery management engine used by the CareSelect solution.

McKesson Health System intends to use the content delivery system to advance automation and streamline utilization management.

"Our partnership with McKesson is a direct reflection of the capabilities and sophistication of our guideline delivery engine," Mardini stated. "NDSC's unique and sophisticated EHR data exchange and analysis capabilities, coupled with McKesson's InterQual evidence-based content and innovative review technologies, will allow clinicians and case managers to streamline utilization management and focus their time on managing patient care."

According to the release, the NDSC and McKesson partnership reflect the capabilities presented by the CareSelect solutions. Healthcare organizations are able to manage utilization, deliver complex care pathways, and automate complicated processes.

Medical imaging is becoming more important to healthcare organizations as more imaging technology is developed. Health IT infrastructures need to be able to handle the size of the image catalogs, not only for the introduction of new mandates and clinician convenience, but to prepare for artificial intelligence (AI) as well.

Several healthcare organizations and vendors are currently working to improve medical imaging technology using AI and machine learning.

Allegheny Health Network (AHN) selected M*Modal Fluency for Imaging. M*Modal has allowed AHN to implement a cohesive documentation strategy operating in conjunction AHN’s Epic EHR system. M*Modal Fluency for Imaging has assisted AHN in delivering approximately one million high quality radiology exams this year and has incorporated M*Modal’s speech recognition and natural language technologies into their EHR solution.

A computer can recognize and react to the patterns and pixels that make up a digital image by using an algorithm to calculate and measure the data in the images. The algorithm can take the image produced by a scan of a patient’s brain, heart, spine, etc., measure the image and compare it to other measured images in the stored data base with confirmed diagnoses.

Collecting and storing images is a significant part of improved patient care. Storing and consulting images now will assist clinicians in using future AI solutions to make more informed decisions about patient health. 


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