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Erschienen in: Journal of Digital Imaging 3/2016

28.10.2015

Radiology Quality Measure Compliance Reporting: an Automated Approach

verfasst von: Marc Kohli, Duane Schonlau

Erschienen in: Journal of Imaging Informatics in Medicine | Ausgabe 3/2016

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Abstract

As part of its ongoing effort to improve healthcare quality, the Center of Medicare and Medicaid Services (CMS) has transitioned from monetary rewards to reimbursement penalties for noncompliance or nonparticipation with its quality measurement initiatives. More specifically, eligible providers who bill for CMS patient care, such as radiologists, will face a 2 % negative payment adjustment, if they fail to report adequate participation and compliance with sufficient CMS quality measures in 2015. Although several methods exist to report participation and compliance, each method requires the gathering of relevant studies and assessing the reports for compliance. To aid in this data gathering and to prevent reduced reimbursements, radiology groups should consider implementing automated processes to monitor compliance with these quality measure standards. This article describes one method of creating an automated report scanner, utilizing an open source interface engine called Mirth Connect, that may facilitate the data gathering and monitoring related to reporting compliance with CMS standard #195 Stenosis measurement in Ultrasound Carotid Imaging Reports. The process described in this article is currently utilized by a large multi-institutional radiology group to assess for report compliance and offers the user near real time surveillance of compliance with the quality measure.
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Metadaten
Titel
Radiology Quality Measure Compliance Reporting: an Automated Approach
verfasst von
Marc Kohli
Duane Schonlau
Publikationsdatum
28.10.2015
Verlag
Springer International Publishing
Erschienen in
Journal of Imaging Informatics in Medicine / Ausgabe 3/2016
Print ISSN: 2948-2925
Elektronische ISSN: 2948-2933
DOI
https://doi.org/10.1007/s10278-015-9835-z

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