25 Jul Health Data News Roundup: Medicare Advantage Plans High Enrollment; New TEFCA Flow-Down Resource; and USCDI v3 Released

Welcome to the Health Data Weekly News Roundup from IMAT Solutions. As the power of data continues to grow in the healthcare arena, today’s care organizations need to be on the forefront of all news and trends to help ensure that their data analytics efforts deliver accountable and informed care. Each week, we will provide you with the actionable news you need to meet these goals.

Medicare Advantage Plans See High Enrollment, Low Spending in 2022
Medicare Advantage plans are seeing low healthcare spending, strong diversity, and high enrollment in 2022 compared to 2021 and earlier years, according to the Better Medicare Alliance’s 2022 State of Medicare Advantage report.

UnitedHealthcare Cuts Out-of-Pocket Healthcare Costs for Insulin
UnitedHealthcare chas announced that it will eliminate out-of-pocket healthcare costs for insulin and other emergency use drugs for fully insured group health plan members.

Using Data Analytics to Improve Primary Care, Referral Management
Primary care facilities, often the first point of contact for many patients, may be hampered by outdated and inefficient processes, but data analytics can provide a potential solution.

The Sequoia Project Releases TEFCA Flow-Down Resource
The Sequoia Project, selected by ONC as the Recognized Coordinating Entity (RCE) for the TEFCA, has released a new resource to help healthcare organizations comply with the Common Agreement’s flow-down obligations.

ONC Releases United States Core Data for Interoperability Version 3
The ONC has released the United States Core Data for Interoperability Version 3 (USCDI v3), which expands upon USCDI v2 by adding new data classes and elements.

Data Exchange Among Doctors Widespread, but Challenges Remain: Report
Nearly two thirds of office-based physicians are engaged in some form of electronic health information exchange (HIE), and three quarters of those who exchange data say they have experienced improvements in quality of care, practice efficiency, and patient safety as a result, according to a new ONC study.

Mayo Clinic ML Can Predict Pancreatic Cancer Earlier Than Usual Methods
Mayo Clinic researchers have developed machine-learning models that can detect pancreatic cancer on pre-diagnostic CT scans substantially sooner than traditional methods for clinical diagnosis.