Disconnected data and records allow people to slip through the cracks of complex cancer screening systems. Deep machine learning and artificial intelligence tools help automate the reportingo bring those patients to view of the clinical staff. Automated communications to patients and providers notify patients of their screening results and appointments to improve the continuum of care.

Located in Kentucky, Thynk Health operates from a region experiencing some of the highest rates of lung cancer in the nation. The team at Thynk Health had witnessed first-hand how manual, human entry of patient data was limiting the scalability of screening programs and was prone to error resulting in inaccurate and incomplete information. Frustrated with the inefficiencies surrounding lung cancer screening, a team of radiologists were determined to make a better solution and Thynk Health was born. Today, the complete cancer screening and incidental finding management solution, designed by radiologists and frontline physicians, provides the advanced technology hospitals require to identify and screen more at-risk patients, to help providers save time and energy lost on manual paperwork through hyper automation, and to ensure patients no longer slip through the many cracks of complex health systems. While Thynk Health initially focused on lung screening, under Jeff’s leadership, they have expanded across multiple modalities providing deep learning and hyper-automation to track patient nodules within entire populations of patients.

Thynk Health’s advanced, EHR-agnostic technology operates in the background of health systems core information technologies, using artificial intelligence and state-of-the-art deep learning technology to extract data from radiology reports, pathology reports, surgical notes, clinical notes, and unstructured and structured data sources to create a complete patient profile. This is an important differentiator in Thynk Health’s technology, there is absolutely no change to the provider workflow as you will see in many systems requiring findings to be tagged in a certain way. “With Thynk

Health’s uniquely advanced technology, our algorithms are rapidly customized to learn and analyze each organization and provider’s own style of reporting, so then both structured and unstructured data can be mined to identify at-risk patients, incidental findings, pulmonary nodules, and other imperative information,” says Jeff. “Just one example is how we help nurse navigators format and submit patients to the ACR Lung Screening Registry. This is required for providers to meet quality reporting to receive Medicare CT lung cancer screening payment. Prior to implementing our software, nurse navigators were spending 25-30 minutes combing through patient medical records to complete the registry form and submit. Thynk Health, operating within the EHR and other health data systems, automatically extracts the needed information and formats it for the ACR Lung Screening Registry submission.” The nurse navigator can click on the patient, review the data and submit with one-click.

According to Jeff, COVID-19 has created new challenges for cancer screening, in many cases, delaying screenings by several months and creating more difficulty for administrative and scheduling teams. Thynk Health’s cancer screening solution, tracks all screening follow-up, and downstream follow-up appointments. “Utilizing worklists, our solution prevents patients from falling through the cracks and ensures the success of lung cancer screening programs post COVID-19,” adds Jeff. “By parsing all pre-existing EHR and ACR data, organizations can automatically determine patients that may have been affected by the timing of COVID-19, send automated communications to patients and providers, and track all rescheduled appointments, ensuring every patient stays on track when safe to resume.” Thynk Health’s ability to access data through our EMR/EHR-agnostic platform allows us to identify patients who may have had an interval CT chest or PE protocol, and automatically identify nodules that may have been overlooked in the EMR, or update eligibility for their next screening.