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Healthcare Effectiveness Data and Information Set

hedis
quality·Updated Jun 23, 2026

Definition

ISO-11179 Definition

The Healthcare Effectiveness Data and Information Set (HEDIS) is a comprehensive performance measurement framework developed and maintained by the National Committee for Quality Assurance (NCQA) used by health plans to report quality metrics to employers, government programs, and consumers. HEDIS contains over 90 measures across six domains of care: effectiveness of care (clinical quality), access and availability of care, experience of care, utilization and risk-adjusted utilization, health plan descriptive information, and measures reported using electronic clinical data systems. Health plans submit HEDIS data annually to NCQA, which uses the results to produce plan-level quality ratings that influence Medicare Advantage Star Ratings, Medicaid managed care contract renewals, and commercial employer purchasing decisions.

HEDIS measures directly affect health plan revenue. In Medicare Advantage, CMS Star Ratings are heavily influenced by HEDIS clinical quality measures, and plans with 4 or 5 stars receive quality bonus payments that can represent hundreds of millions of dollars in additional revenue. Plans that fall below 3 stars face enrollment freezes and enhanced regulatory scrutiny.

For commercial and Medicaid markets, HEDIS scores influence employer contracting decisions and state contract awards. Each measure has a technical specification that defines the eligible population (denominator), the qualifying event or service (numerator), and the exclusion criteria — and these specifications change annually. Healthcare data engineers build HEDIS measure calculation pipelines that process claims, pharmacy, laboratory, and electronic clinical data to determine each member's denominator eligibility and numerator compliance for each measure.

Common engineering challenges include applying the correct measurement year dates, implementing complex exclusion logic (e.g., frailty exclusions in the Medicare population), handling hybrid measures that combine administrative claims with medical record data, and managing late claims that arrive after the initial measurement period closes. HEDIS value sets — published by NCQA and including the lists of ICD-10, CPT, NDC, and LOINC codes that qualify for each measure — must be versioned and updated annually. Key measures include Diabetes Care (HbA1c testing, nephropathy screening), Controlling High Blood Pressure, Breast Cancer Screening, Colorectal Cancer Screening, and Medication Adherence for Chronic Conditions.

Standard Abbreviation

hedis

Category

quality

Production DDL — FACT_QUALITY_MEASURE

FACT_QUALITY_MEASURE.sql
CREATE OR REPLACE TABLE FACT_QUALITY_MEASURE (
    qlty_key        INTEGER        NOT NULL  -- surrogate key,
    mbr_key         INTEGER        NOT NULL  -- FK to DIM_MEMBER,
    plan_key        INTEGER        NOT NULL  -- FK to DIM_PLAN,
    meas_yr         SMALLINT                 -- measurement year,
    hedis_meas_cd   VARCHAR(20)              -- HEDIS measure code,
    denom_ind       CHAR(1)                  -- denominator eligible,
    numer_ind       CHAR(1)                  -- numerator met,
    excl_ind        CHAR(1)                  -- exclusion indicator,
    gap_open_ind    CHAR(1)                  -- care gap open,
    star_rtg_nbr    DECIMAL(3,1)             -- star rating,
    qlty_scr        DECIMAL(5,2)             -- quality score,
    perf_thrsh_pct  DECIMAL(5,2)             -- performance threshold,
    raf_scr         DECIMAL(10,3)            -- risk adjustment factor,
    outreach_cnt    SMALLINT                 -- outreach attempts,
    load_dt         TIMESTAMP_NTZ  NOT NULL  -- load timestamp
);

Standard Snowflake DDL for the canonical quality table. Convert to BigQuery or Databricks →

Why This Term Matters

Quality measure data determines how payers and providers are rated and reimbursed under CMS Stars, HEDIS, and value-based care contracts. Data engineers who understand quality terminology build measure calculation pipelines that correctly attribute patients, apply denominator exclusions, and flag documentation gaps before submission deadlines. Incorrect quality data directly affects star ratings, pay-for-performance bonuses, and Medicare Advantage plan bids.

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