digital evolution

digital health data services

As electronic clinical data continue to become more prevalent and affordable within healthcare quality reporting, Advent is your partner in navigating the digital evolution to improve the completeness and accuracy of performance measure reporting. CMS continues to emphasize reporting of electronic Clinical Quality Measures (eCQMs) while NCQA expands the Electronic Clinical Data Systems (ECDS) measure domain—both are significant contributors to the changes impacting healthcare data collection and reporting.

Advent is fully committed to staying at the forefront of digital reporting, and maintaining an intimate knowledge of how the digital evolution impacts health plans and other stakeholders. Members of our team are active participants in digital measure workgroups and collaboratives while attending and presenting at national healthcare technology conferences. With this experience, we are better able to understand current regulations and reporting requirements impacting healthcare organizations and provide superior insights into the future of digital reporting. We work closely with our business partners, policy-makers, and technology experts to ensure we have the latest information to share with our clients.

Trust Advent to provide the thought leadership necessary for organizations to thrive in the turbulent evolution to digital reporting in health care. Advent can assist you in determining how policy changes may impact your organization and keep you abreast of the best methods to prepare for the future of healthcare quality reporting.

Continuing Advent’s thought leadership in digital reporting, Matt Flores, one of our digital reporting specialists, was asked by Linguamatics (an IQVIA company) to publish a blog discussing possible applications of Natural Language Processing (NLP) in HEDIS reporting. In his blog, he discusses how NCQA’s digital evolution is changing the reliance on medical record collection toward gathering digital information from clinical sources. NLP and other machine learning algorithms have great potential to bridge many information gaps, as well as to serve other valuable functions in HEDIS reporting including in the promotion of data quality, collection of social determinants of health, and enabling outcomes-based measurement. We hope you can take a moment to read it here.