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hospice enrollment indicator

hospice_ind
quality·Updated Jul 21, 2026

Definition

ISO-11179 Definition

A flag identifying that a member is enrolled in a hospice program, used as a required exclusion criterion in most HEDIS measures since hospice-enrolled members have elected comfort-focused rather than curative or preventive care and should not be included in preventive screening or chronic disease management measure denominators. Accurate hospice identification from claims and enrollment data is critical for HEDIS measure compliance and avoiding attribution of inappropriately low performance rates for end-of-life populations.

Standard Abbreviation

hospice_ind

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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