{"id":1774,"date":"2024-03-13T16:54:46","date_gmt":"2024-03-13T16:54:46","guid":{"rendered":"https:\/\/www.intelerad.com\/en\/?post_type=resource-library&p=1774"},"modified":"2024-05-15T20:49:36","modified_gmt":"2024-05-15T20:49:36","slug":"uc-health","status":"publish","type":"resource-library","link":"https:\/\/www.intelerad.com\/en\/case-studies\/uc-health\/","title":{"rendered":"UC Health"},"content":{"rendered":"\t\t
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Summary<\/h3>\n\n

Medical imaging is a key part of a patient\u2019s health record and clinical trial workflows. These workflows are complex; they often involve hunting down imaging off a clinical PACS onsite, requesting imaging be sent from an outside facility, or, worse yet, waiting for imaging data discs to arrive by mail. This process can take anywhere from a few hours when imaging is onsite, to days and weeks if imaging is mailed or brought by courier service from an outside facility. UC Health sought to automate their process of managing medical imaging for clinical trials and securely upload, anonymize, and match imaging data with non-imaging clinical data. Working with Intelerad, they launched an academic research cloud PACS at their facility.<\/p>\n\n

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InteleShare Research\u2122 enables us to integrate our imaging research in a way that wasn\u2019t possible before.<\/p>\n<\/blockquote>\n

ACHALA VAGAL, MD, MS Vice Chair of Research, Associate Professor of Radiology, University of Cincinnati Medical Center<\/p>\n\n

New Automatic Workflow<\/h3>\n\n

UC partnered with Intelerad to electronically share imaging externally and internally. Internally, a lightweight piece of software called a gateway was installed to automatically send imaging from the clinical PACS to the research PACS.<\/p>\n

Intelerad handled everything from quickly setting up individual research folders to large multi-site research trials. The facility can now customize timepoint fields, project users and roles, case report forms, and trial workflows.<\/p>\n

Intelerad\u2019s automation provides the capability to remove patient health information (PHI) from the DICOM tags client-side before the study leaves the sending facility, eliminating the risk of accidentally leaving PHI tags in place.<\/p>\n

Centrally managed and automated workflows enable studies to be routed to end destinations including local file directories, research repositories, and third-party viewers or post-processing systems. Incoming studies from outside sites are routed through configurable workflows with automated sharing to organizations, locations, groups, and users like Quality Assurance personnel and investigators. Each project may have their own customizable electronic case report form (eCRF) that allows the gathering of radiological data that can be later exported and linked to their associated clinical data.<\/p>\n

Success Across Trials<\/h3>\n

Assessing Population-based Radiological Brain Health in Stroke Epidemiology (APRISE) Study:<\/b> This NIH funded population-based study is focused on stroke recurrence in the greater Cincinnati area and utilizing imaging variables in addition to clinical and demographic data to build prediction models of recurrent stroke. This is a large study with multiple clinical imaging studies that are being gathered from various facilities. Today, 5 gateways have been set up to automate sending of patient imaging from facilities in the area that are participating in this study.<\/p>\n

Overcoming Unique Anonymization Challenges<\/h3>\n

One of the key challenges for APRISE during the deployment was conserving subject IDs of approximately 4000 patients from the parent study that has been going on for many decades. The parent study had all the clinical data that needed to be lined up with the imaging data from the study that was setup using Intelerad. Intelerad needed to create a custom workflow to conserve imaging IDs from the parent study, anonymize all the imaging data (CT, MR, CTA, MRA) coming in from numerous regional hospitals, collect all the radiological data generated by the radiologists from viewing the images, and export radiological data in a way that would allow lining up with the clinical data as specified by the statisticians of the parent study. Intelerad was able to successfully configure a workflow that allowed seamless integration from multiple sites and made the imaging available for central interpretation.<\/p>\n

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Intelerad\u2019s engineering team was able to setup an infrastructure and customize a workflow that met all the needs of a very complicated study.<\/p>\n<\/blockquote>\n

Vivek Khandwala PHD, Research Associate, Department of Radiology, University of Cincinnati<\/p>\n

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Overview<\/strong><\/p>\n