Leading content services and enterprise imaging provider to showcase technology innovation and interoperability
Hyland Healthcare, recognized as a leader in the Gartner Magic Quadrant for Content Services Platforms for the past 12 years, returns to the Health Information Management System Society’s (HIMSS) annual trade show to support attendees’ quest to re-imagine healthcare interoperability through the company’s scalable content services and enterprise medical imaging solutions.
Recent HIMSS 2022 State of Connected Care and Interoperability research reveals that managing unstructured data represents one of the most significant obstacles for health systems. On average, more than 60% of health systems surveyed do not have unstructured patient records and medical images available for decisions at the point of care. Electronic medical records (EMRs) alone typically do not natively incorporate the more than 75% of patient data that is unstructured. Hyland will demonstrate how an enterprise content services and medical imaging platform addresses this challenge by connecting unstructured content, medical images and data, and linking it for use by key stakeholders within their core systems. As a result, health systems and payers accelerate business processes, decrease errors, streamline workflows and improve insight for decisions.
More than 3,700 health systems and payers across the globe rely on Hyland to support their business objectives with two recent examples including:
- A recent HIMSS success story shared how UNC Health achieved “One Patient, One Chart” and provided improved operational efficiency enterprise wide by integrating Hyland’s content services and medical imaging technology within its Epic workflow. “We have eliminated nine PACS and three reporting systems,” says Vineeta Khemani, director of information services division architecture and clinical systems at UNC Health Care. “This not only results in hard cost savings, but also reduces annual support and enhancement costs.” Additionally, UNC Health added document capture, machine learning classification, extraction of data and automated workflow to its enterprise resource planning (ERP) platform to improve its “clean pass-through” and invoice-processing rates. Matthew Castellano, system executive director for IT, Business and Revenue Cycle Systems and Innovation, UNC Health notes “Hyland offered solutions that were extensive and scalable across many enterprise use cases, which drives investment value.”
- The Etemadi Research Group at Northwestern Medicine, through a collaboration with Google Health, created a novel machine learning algorithm to predict lung cancer more accurately and earlier than radiologists alone. Its use of Hyland’s Acuo vendor neutral archive (VNA) to extract and deidentify medical imaging data and metadata speeds predictions to notify patients of their results earlier. Acuo’s RESTful API query engine allows extraction of key metadata (study modalities, kernels, etc.) that enables Etemadi Research Group to reduce and remove bias in the datasets used to train and validate machine learning (ML) algorithms, without having to extract every eligible DICOM element. The world class Etemadi engineers combined with the high throughput and scalable extraction and deidentification pipeline capabilities of Acuo provide for continual innovation to drive the rapidly changing, AI-enabled future of radiology.
Finally, Hyland presents the following new innovations and partnerships that enhance interoperability, insight and healthcare efficiency at HIMSS22:
- The newly launched Hyland Clinician Window enables providers to solve the challenge of delivering the more than 75 percent of patient content that is unstructured within EMR workflows. Colleen Sirhal, chief clinical officer and VP of customer success describes one customer’s success: “The Hyland Clinician Window is helping physicians at a notable health system in Washington view the patient chart within Epic, saving time by rapidly reviewing patient consult notes, EKGs and medical images captured by any affiliated hospital. In addition, they can see external patient records stored in health information networks through cross enterprise document sharing (XDS). Physicians especially like the gallery view that enables multiple images to be combined in one page, including the ability to dive deeper into the images for advanced analysis through Hyland’s NilRead diagnostic viewer that provides access to all medical imaging systems.”
- Enhancements to Alfresco Elasticsearch assist payers by streamlining operations and improving member services efficiency. It delivers true enterprise-wide search, enhanced scalability and simplified index management.
- Improved data processing and analytics within its EI portfolio enables physicians and clinical teams to speed research of large medical imaging study batches through specialized queries, analyzing values of every DICOM header tag, including pixel data. Hyland’s bi-directional DICOM web service APIs and rules-based enterprise DICOM routing provides the integration infrastructure to fuel data and AI processing pipelines for advanced analytics.
- New functionality in Hyland Workflow allows diagnosticians to improve processing, eliminate errors and enhance productivity by extrapolating quantitative data for inclusion in clinical documentation workflow processes.
- Expanded collaboration with AWS to support customers’ growing needs for cloud services. Join Hyland at the AWS booth #1041 on Tuesday, March 15th at 10 am to learn why Hyland and AWS fit into the IT strategy of health system Tufts Medicine, formerly known as Wellforce, as they continue to drive a new standard of healthcare in Massachusetts.
- SyntheticMR which uses AI to provide volume and population-based reference measurements of the brain tissues, including the industry-first Myelin segmentation, has partnered with Hyland to speed radiologist reporting. Hyland’s PACSgear Modlink will enable radiologists to provide accurate reporting while eliminating the typical hours of radiologist time wasted manually dictating quantitative data into reports.