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Use High-Quality Clinical Data to Secure HEDIS Quality Bonus

Medicare Advantage (MA) plans are waiting with bated breath for the Centers of Medicare & Medicaid Services (CMS) to release its proposed 2026 Part D Star Ratings measures, scheduled for October. Historically, the data that determines Star Ratings has consistently been derived from four sources: administrative data, Health Effectiveness Data and Information Set HEDIS® scores, Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey, and Health Outcomes Survey (HOS). The significance of each of these metrics is in a constant state of flux due to CMS’s yearly adjustments to the Star Rating criteria, as well as the varying importance assigned to different measures.

The forthcoming 2026 Star Ratings, formulated based on care provided during the 2024 plan year, are poised to strike a significant financial impact on some of the largest payers in the healthcare industry. This is a result of CMS’s projected intention to reduce the weight of patient experience/complaint measures, while reemphasizing the importance of HEDIS and performance measures. Amid these shifting dynamics is the transition from “Hybrid” to Electronic Clinical Data Systems (ECDS) HEDIS reporting methods.  

ECDS represents an interconnected data repository housing a plan member’s personal health information and a comprehensive record of their interactions with the healthcare system. The adoption of the HEDIS ECDS reporting standard offers health plans a systematic approach for gathering and reporting structured electronic clinical data. One of the HEDIS reporting measures that will be transitioning from “Hybrid” to “ECDS” starting in Measurement Year (MY) 2024 is the colorectal cancer screening (COL). 

The current COL reporting method can be accomplished through two approaches: one involves solely using administrative data, commonly known as the “administrative method,” while the other combines administrative data with medical record reviews for a select group of members, referred to as the “hybrid method”. Under the hybrid method, organizations have the flexibility to choose a random sample size and perform chart chasing for non-compliant cases, with the goal of capturing data to achieve compliance. However, with the transition to ECDS, the approach shifts significantly. Sampling patients will no longer be a part of the process; instead, the focus will be on utilizing all available data.

In navigating this evolving metrics landscape, the strategic importance of high-quality clinical data should not be underestimated. Clinical data collected and stored within ECDS should be trustworthy and reflect the true state of a patient’s health and medical history. If the data is inaccurate or of low quality, it can lead to incorrect assessments of healthcare quality and potentially compromise patient care.

The Strategic Role of High-Quality Clinical Data in Quality Measurements

Clinical data is increasingly important for accurate, effective quality measurement to improve care – especially for patient-specific measures focused on outcomes. Clinical data can be timely, updated with recent and historical member information, and contains rich clinical elements, such as lab test results, vital signs, and problem diagnoses, which are not present in other data sets. 

However, the complexities of clinical data documentation across provider networks create barriers to effectively harnessing this vital health information. Our studies show that more than 50% of clinical data cannot be used in its native form due to non-conformant codes, details buried in text, redundancy, and other systemic data quality issues. When data quality is subpar, the compliance scores for HEDIS do not offer a precise representation of actual care quality.

The presence of inaccurate and incomplete data poses a significant hurdle for the majority of health plans, impairing their capacity to fully optimize their performance in relation to Value-Based Payment Modifier (VBPM) accountability measures. This encompasses HEDIS scores and Star Ratings, as well as state-driven incentive programs.

How Health Plans are Overcoming Clinical Data Quality Issues 

Current approaches to data quality improvement involve skilled data scientists and analysts wielding multiple tools to make clinical data structurally and semantically normalized and interoperable. The sheer volume of clinical data cannot readily be handled using these traditional approaches, and with a continual influx of data and changes to terminologies and standards, the work is never done. As such, these approaches are costly, inefficient, and limiting.

To get the most benefit from clinical data for HEDIS and quality improvement, organizations are investing in robust clinical data transformation and integration solutions. Availity Fusion’s comprehensive process to normalize, enrich, reorganize, deduplicate, and summarize multi-source, multi-format data in real time increases the usability of clinical data for HEDIS reporting, as well as other digitally enabled use cases. 

The following examples demonstrate how Availity Fusion’s upcycled clinical data, which is normalized and consistent with the HEDIS value set, can improve HEDIS reporting accuracy and enable identification of care gaps.

Utilizing high-quality clinical data for HEDIS and other quality measurements empowers health plans to proactively address potential gaps in care and maximize their chances of securing and retaining quality bonuses. This not only enhances financial stability but also presents a tremendous opportunity to shift measurement from an operational burden to an instrumental tool to equitably compare care quality across sites of care and enable more informed healthcare decisions. 

While Availity Fusion is not a HEDIS measurement engine specifically, upcycled data provided by Availity Fusion ensures that existing HEDIS measurement utilities are yielding a clear, accurate view of patients. By partnering with Availity, an organization can transform its data to automatically and more accurately reflect the quality of care delivered to patients. As a result, healthcare organizations can foster more transparent and evidence-based approaches to resource allocation, enabling targeted improvements in patient outcomes and elevating overall healthcare standards.

Download Clinical Data Asset to Revolutionize HEDIS Reporting & Compliance to learn how Availity Fusion’s Upcycling Data™ technology can help your health plan drive accurate HEDIS results, quality management, and care gap closure. 

Ashley Basile, Ph.D., Chief Product Officer of Clinical Solutions at Availity 

As Chief Product Officer of Clinical Solutions, Ashley is responsible for corporate and product strategy, and leads the product management, clinical informatics, and marketing teams. Ashley brings over fifteen years’ experience in senior product and strategy leadership to her role at Availity.

Ashley previously led product and strategy for Optum’s provider and payer analytic product portfolio, overseeing 8 analytic products and launching a flagship product that leveraged integrated clinical and claims data to support population health management for providers and payers. She also served as Vice President of Client Analytic Services, building a new client-facing analytics team to support large integrated health systems and payer organizations with cost management, provider performance and value-based care delivery. 

Ashley holds a Ph.D. from the Harvard Business School and Graduate School of Arts and Sciences in Health Care Management and Policy, where she received multiple teaching awards and published over a dozen articles on healthcare improvement and management, including a Harvard Business School case study used nationwide on implementing collaborative accountable care.