2024 Quality AI Lessons Learned
Tenasol’s Quality AI solution is used by several national and regional health plans to rapidly and accurately identify numerator evidence supporting HEDIS reporting. Clinical quality review teams reported that Tenasol’s solution significantly improved the detection and extraction of measure-specific information, leading to faster and more efficient reviews – saving time and money compared to costly, manual and labor-intensive review processes.
Tenasol clients also reported additional value based on Tenasol’s speed to delivery. Scalable, real-time processing of structured and unstructured data accelerated data time to value getting extracted discrete data and validated quality measure evidence from any record format within twenty-four (24) to seventy-two (72) hours, delivering improved workforce utilization without disrupting existing workflows.
Here are the key lessons learned which you may consider in evaluating Quality AI tools to augment your abstraction process:
Leverage all clinical sources – Identify all sources of data that can impact quality measure performance. Plans historically lean towards traditional data, such as PDF records, however, ADTs, CDAs and FHIR data can all have a positive impact on outcomes.
One Chart, Multi-Use – Health plans collect data for multiple programs each year. Prior to launching new chart-chase initiatives, plans should proactively leverage data across the enterprise (e.g. risk charts for quality), as it may eliminate the need for unnecessary chart acquisition and coding efforts, saving time and money.
Unify Data Processing – Invest in systems and processes that are capable of ingesting and extracting evidence from all available sources. Work collaboratively with your internal IT teams to streamline dataflows and select only vendors that demonstrate the ability to extract measure evidence in a unified way across all available data.
Prioritize Speed and Turnaround time – HEDIS season is a demanding time, with a limited window to complete the activities necessary for success. For our clients, Tenasol performs same or next-day data processing to ensure quality teams are never delayed with the latest insights necessary to complete abstraction in a timely manner.
HEDIS reporting is only as strong as the quality of the data you receive, therefore, ensuring high-quality, relevant, and complete records is essential for success. In addition to the takeaways above, enforcing consistent quality, resolution and relevance of data will help drive more efficient review and reporting during HEDIS season.
MY2025 Measure Updates
NCQA continues to advance its digital-first approach to quality measurement, and the HEDIS MY2025 specifications reflect this transition. Key updates include:
Transition to Digital-Only Reporting: Three previous hybrid measures have been retired and are now only reported as digital quality measures.
New Digital Measures: NCQA has introduced three new measures, all of which are based on Electronic Clinical Data Systems (ECDS) reporting.
Documented Assessment After Mammogram (DBM-E)
Follow-Up After Abnormal Mammogram Assessment (FMA-E)
Blood Pressure Control for Patients with Hypertension (BPC-E)
Enhancements for Equity and Outcomes: Several measures have been updated to strengthen health equity, behavioral health, maternal and child health as well as chronic disease management, including diabetes and cardiovascular conditions.
Race/Ethnicity Reporting: Significant changes have been made to race and ethnicity reporting requirements.
Expanded Screening Criteria: The age range for the Breast Cancer Screening measure has been broadened.
These updates are designed to promote comprehensive, patient-centered care and improved health outcomes across all domains.
Looking Ahead: Preparing for Digital Quality Measures (dQMs)
The future of HEDIS lies in a full transition to digital Quality Measures (dQMs), with a growing emphasis on real-time, interoperable data exchange. Tenasol is well positioned to support clients making this transition as or platform natively supports transformation of all available data to FHIR, in addition to providing tools for IT teams to visualize and validate evidence to optimize its use for digital quality. Health plans should begin taking the following steps:
Interoperability Readiness: Strengthen your interoperability infrastructure and ensure your systems can support Fast Healthcare Interoperability Resources (FHIR)-based data exchange.
Digital Data Source Expansion: Collaborate with EHR vendor partners to access and aggregate digital clinical data.
FHIR Enablement: Work with EHR vendors or vendors like Tenasol to ensure data can be sent in FHIR format. It is important for plans without FHIR capabilities to use tools like the Tenasol FHIR Transformation Solution. This solution enables ingestion and conversion of data from any format to FHIR.
The future of HEDIS is focused on digital quality. Plans that proactively invest in digital transformation and data quality will be better positioned to meet the evolving demands of HEDIS. To test and explore the Tenasol FHIR tool, click this link.
2025 LLM Implementation
In 2024, Tenasol took initial steps in testing and benchmarking approaches for using LLMs for many of its products. Limitations our described in our blog here. To summarize from a higher level:
LLM technology is ideal for summarization tasks which we have shown within our products.
Costs of generative LLM technology drastically reduced in 2024, and again in 2025 via model compression techniques, but still remain relatively high.
Costs of non-generative LLM technology remain low and effective. As of 2025, Tenasol is in QA of wider implementation of LLM classifiers.
Conclusion
Tenasol’s continued investment in digital innovation, particularly in FHIR transformation and large language model (LLM) integration, demonstrates a clear commitment to accelerating quality measurement and abstraction processes. Lessons from 2024 confirm the value of real-time, multi-source data processing, emphasizing speed, interoperability, and reuse across quality and risk programs. As NCQA pushes toward digital-only HEDIS reporting, plans that proactively unify and modernize their data infrastructure will be best positioned for success. Tenasol’s scalable tools, including its FHIR Viewer and LLM-based classifiers, enable rapid and reliable evidence extraction from structured and unstructured sources, supporting improved clinical outcomes and operational efficiency. As MY2025 ushers in expanded digital measures and equity-focused updates, organizations should prioritize readiness and collaboration with vendors like Tenasol to meet the evolving standards. In short, digital transformation is no longer optional—it's the key to sustainable, scalable quality performance in a rapidly shifting landscape.