Complete, High Quality Data
Developing standards and open-source tools to enable interoperable data that can be shared and analyzed to unlock transformative clinical insight.
Latest Posts
Getting Started with CQL: Technical Implementation for Vendors
Transitioning from the Quality Data Model to Clinical Quality Language (CQL) impacts health IT vendors who implement electronic Clinical Quality Measures (eCQM). This HIMSS18 presentation by James Bradley, MITRE and Bryn Rhodes, ESAC provides an overview of the CQL architecture, building a CQL execution engine, and using Open Source execution engines—focusing on the JavaScript execution engine used in Bonnie.
Predictive Analytics for Mental Health Outcomes: A Case for Novel Applications of the Hedonometer
Learn about the latest collaborative pursuit between Computational StoryLab at the University of Vermont and MITRE in applying the Hedonometer as an initial screening tool to identify veterans at greatest risk to attempt suicide. A HIMSS18 presentation by Josh Park and Lisa Tompkins-Brown from MITRE.
Using Predictive Analytics to Save Lives
Experts from Johns Hopkins University and MITRE discuss new research and technology. A HIMSS18 presentation by Jay Schnitzer, MD, MITRE, Sybil Klaus, MD, MITRE, and James Fackler (Johns Hopkins).
Empowering Patients In Their Own Healthcare
Watch how Kristina Sheridan identifies and evaluates methods to empower patients with chronic illnesses to better manage their care and to fully engage with providers to improve their health outcomes.
Simplifying Clinical Notes to Reduce Provider Burden
MITRE’s Andre Quina shares early findings from research with healthcare providers to capture high quality health data from clinical notes as part of routine care to reduce burden and improve patient care.
Making Sense of Data for Healthcare Providers
MITRE’s Dr. Sarah Corley and Dr. Sybil Klaus discuss the research and initiatives under way to turn data into knowledge for healthcare providers, including using predictive analytics to identify risk factors and how to improve patient outcomes through a...
Solving the Health Data Interoperability Riddle
MITRE’s VP and Chief Technology Officer, Dr. Jay Schnitzer, speaks about the challenges and potential solutions for improving data interoperability for healthcare, and MITRE’s neutral role in bringing the right partners and the right health data systems...
Improving Health Outcomes by Connecting Data
MITRE’s Dr. Sarah Corley and Dr. Sybil Klaus discuss the research and tools needed for clinicians to better use data and reduce the current electronic health record provider input burden. Watch their take on how natural language processing and machine learning can help solve these difficult problems, predict risk for disease, and contribute to a holistic view of patient records.
Using Data Interoperability to Improve Care for Veterans
With more veterans relying on care from multiple providers, it’s important that all clinicians involved in the patient’s care be able to see a holistic view of the symptoms, history, and treatments. MITRE’s VP and Chief Technology Officer Dr. Jay Schnitzer talks about the research under way and the vision for achieving interoperability of electronic health record data for better healthcare outcomes.
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