LungGPS™ Patient Management Platform

Designed to identify, track, automate, and simplify patient management—potentially leading to earlier diagnoses and more treatment options.([FOOTNOTE=LeMense GP, Waller EA, Campbell C, Bowen T. Development and outcomes of a comprehensive multidisciplinary incidental lung nodule and lung cancer screening program. BMC Pulm Med. 2020;20(1):115.],[ANCHOR=],[LINK=])

• Enrolls patients into a management protocol with automated notifications, reminders, and status updates 
• Monitors and manages patients to help avoid losing them to follow-up
• Uses natural-language AI processing to mine radiology reports in real time to identify incidental lung nodule findings

Cloud-based patient and data management, workflow, guideline compliance, and reporting.

• Automates routine tasks based on standardized clinical workflow protocols (e.g., Lung-RADS™*) 
• Generates physician and patient finding letters
• Required data can be uploaded to the American College of Radiology (ACR) and the Lung Cancer Screening Registry (LCSR) to ease submission workflow
• Enrolls and tracks patient status throughout various pre-defined workflow steps

Image processing and analytics, radiology workflow, and standardized reporting.

• Designed to reduce inter-reader variability in nodule measurement and reporting
• Offers consistent, quantitative lung nodule analysis: strict Lung-RADS™* conformance, volumetric and average diameter values, volume change percentage with doubling times, and comparisons of values over time
• Uses integrated computer-aided detection (CAD) of suspicious lung nodules

Consolidates valuable patient informatics, enabling the care team to spend time where it matters: discussing the next steps in your patient's care.

• Creates one dashboard to view the relevant patient details and can be used to facilitate physician treatment recommendation(s). 
• Facilitates collaborative, multidisciplinary diagnostic, treatment, and follow-up decisions by review committees and thoracic tumor boards
• Ability to securely integrate clinical patient information from multiple sources, including EMRs, lab systems, pathology, radiology, and genomics