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annual wellness visit flag

awv_flg
population·Updated Jul 4, 2026

Definition

ISO-11179 Definition

A flag indicating that a member completed an annual wellness visit, a Medicare-covered preventive service including a health risk assessment and personalized prevention plan, during the measurement year. Annual wellness visit completion is a key quality metric and an opportunity to close multiple care gaps in a single encounter.

Standard Abbreviation

awv_flg

Category

population

Production DDL — FACT_POPULATION_RISK

FACT_POPULATION_RISK.sql
CREATE OR REPLACE TABLE FACT_POPULATION_RISK (
    pop_risk_key     INTEGER       NOT NULL  -- surrogate key,
    mbr_id           VARCHAR(20)   NOT NULL  -- member identifier,
    msrmt_prd_dt     DATE          NOT NULL  -- measurement period date,
    risk_score       DECIMAL(8,4)            -- risk score,
    risk_tier_cd     VARCHAR(10)             -- risk tier code,
    raf_score        DECIMAL(8,4)            -- RAF score,
    hcc_cnt          INTEGER                 -- HCC condition count,
    chrnc_cond_cnt   INTEGER                 -- chronic condition count,
    ed_visit_cnt     INTEGER                 -- ED visit count,
    admit_cnt        INTEGER                 -- admission count,
    gap_in_care_cnt  INTEGER                 -- gaps in care count,
    care_mgmt_flg    BOOLEAN                 -- care management flag,
    outreach_sts_cd  VARCHAR(20)             -- outreach status code,
    model_vrsn       VARCHAR(20)             -- risk model version,
    rec_creat_dt     TIMESTAMP     NOT NULL  -- record created date
);

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

Why This Term Matters

Healthcare data terminology is foundational for any data engineer working in this industry. Precise understanding of standard terms enables accurate schema design, reduces downstream data quality issues, and ensures pipelines meet the regulatory and interoperability requirements imposed by HIPAA, HL7 FHIR, and CMS reporting frameworks. Without this foundation, even technically well-built pipelines produce data that fails validation when it reaches payers or regulators.

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