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care gap closure

care_gap_clsr
quality·Updated Jul 21, 2026

Definition

ISO-11179 Definition

The completion of a required service or clinical action that removes a member from the open care gap list and counts them in the quality measure numerator. Care gap closure can occur through claims submission documenting the completed service, supplemental data from medical record review, or provider attestation. Tracking care gap closure rates by service type, provider, and care manager is essential for quality improvement program performance measurement and ROI analysis.

Standard Abbreviation

care_gap_clsr

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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