What are HEDIS (Healthcare Effectiveness Data and Information Set) measures?

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What Are HEDIS Measures?

HEDIS (Healthcare Effectiveness Data and Information Set) measures are standardized performance metrics developed by the National Committee for Quality Assurance (NCQA) that assess healthcare quality and effectiveness across managed care organizations, used to evaluate provider and system performance, guide quality improvement initiatives, and determine reimbursement in value-based payment programs. 1

Core Purpose and Function

HEDIS represents a systematic approach to measuring healthcare quality that partners with over 90% of the nation's managed care organizations to collect, audit, and report standardized performance data. 2 These measures serve three primary functions according to the AHA/ACC Task Force on Performance Measures:

  • Performance assessment: Identifying and characterizing gaps in quality of care by comparing provider, practice, or system performance against national benchmark standards or tracking improvement over time 1
  • Quality improvement design: Providing data to develop and implement targeted quality improvement plans that address identified care gaps 1
  • Reimbursement determination: Reporting outcomes as part of healthcare quality payment programs where organizations base provider reimbursement on achievement and reporting of performance metrics 1

Measurement Approach and Data Sources

HEDIS measures are based primarily on analyses of administrative data sets, electronic health records, national data registries, and administrative databases. 1, 3 This standardized data collection approach allows for feasible and actionable measurement across diverse healthcare settings. 1

The measures typically assess discrete aspects of the care delivery process rather than outcomes alone, which helps minimize the effects of population differences between health plans. 4 However, this administrative data-based approach has limitations—different plans may use varying data collection methods, and lack of risk adjustment can result in incorrect conclusions about care quality. 3

Clinical Application Example: Hypertension Control

A concrete example demonstrates how HEDIS functions in practice. The HEDIS Hypertension Control Measure assesses adults 18-85 years of age with diagnosed hypertension using specific blood pressure thresholds:

  • Ages 18-59 years: Blood pressure <140/90 mm Hg 1
  • Ages 60-85 years with diabetes: Blood pressure <140/90 mm Hg 1
  • Ages 60-85 years without diabetes: Blood pressure <150/90 mm Hg (updated to <140/90 mm Hg in 2018) 1

Performance data from 1999-2017 showed measurable improvements in hypertension control rates across Commercial HMO, Commercial PPO, Medicaid HMO, Medicare HMO, and Medicare PPO populations, demonstrating HEDIS measures' utility in tracking quality improvement over time. 1

Evidence for Effectiveness

The AHA/ACC gives a Class 2a recommendation (Level of Evidence: B-NR) for using performance measures in combination with other quality improvement strategies at patient-, provider-, and system-based levels to facilitate optimal hypertension control. 1 This moderate-quality evidence comes from well-designed nonrandomized studies, including observational data from Kaiser Permanente of Northern California showing that effective performance measures can help improve gaps in care. 1

No randomized controlled trials of HEDIS or other performance measures have been published, which represents a significant evidence gap. 1

Implementation Requirements

When implementing HEDIS measures, healthcare organizations should identify measures that:

  • Meet established ACC/AHA standards for performance measurement 1
  • Include key components influencing hypertension detection, treatment, and control sustainability (medical care, cost of care, patient-reported factors) 1
  • Address the most pressing gaps in care for the specific healthcare provider, practice, or system 1

Common Pitfalls and Limitations

A critical caveat is that HEDIS measures have shown variable success across different clinical domains. While some measures (like beta-blocker use after myocardial infarction or cervical cancer screening rates) have been highly useful in promoting population health, others like the Antidepressant Medication Management (AMM) measures have been less successful. 2 This highlights that linking quality measures to specific clinical strategies is essential for achieving successful treatment outcomes. 2

The reliance on administrative data and process measures rather than outcome data represents another limitation. 3 Alternative methods using standardized surveys could provide actual outcome data and inform interventions to improve quality, though these are not currently the standard approach. 3

Practical Application in Community Settings

Community pharmacy-based programs have successfully used HEDIS measures to demonstrate value. In one randomized controlled trial, a pharmacist-directed diabetes management program achieved significantly better results: 46.7% of intervention participants reached the A1C goal versus 9.1% of controls (P<0.002), and 53.3% achieved blood pressure goals versus 22.7% of controls (P<0.02). 5 The odds of achieving two of three HEDIS standards were 5.87 times greater in the intervention group. 5

This demonstrates that HEDIS measures can serve as practical tools for designing outcomes research projects and gaining acceptance and reimbursement for pharmaceutical services from managed care organizations seeking accreditation. 6

References

Guideline

Guideline Directed Topic Overview

Dr.Oracle Medical Advisory Board & Editors, 2025

Research

Evaluation of a diabetes management program using selected HEDIS measures.

Journal of the American Pharmacists Association : JAPhA, 2012

Research

Applying managed care performance measures in community pharmacy-based outcomes research.

Journal of the American Pharmaceutical Association (Washington, D.C. : 1996), 1999

Professional Medical Disclaimer

This information is intended for healthcare professionals. Any medical decision-making should rely on clinical judgment and independently verified information. The content provided herein does not replace professional discretion and should be considered supplementary to established clinical guidelines. Healthcare providers should verify all information against primary literature and current practice standards before application in patient care. Dr.Oracle assumes no liability for clinical decisions based on this content.

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