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behavioral health encounter identifier

bh_enctr_id
behavioral·Updated Jul 4, 2026

Definition

ISO-11179 Definition

A unique identifier assigned to a single behavioral health visit, session, or service event recorded within a patient's treatment episode. This identifier links all clinical documentation, billing records, and outcome measurements associated with that specific encounter, and is distinct from the broader episode-of-care identifier that may span multiple encounters across a treatment course. Used in behavioral health data warehouses to join encounter-level facts to claims, clinical notes, and quality measure calculations.

Standard Abbreviation

bh_enctr_id

Category

behavioral

Production DDL — FACT_BH_ENCOUNTER

FACT_BH_ENCOUNTER.sql
CREATE OR REPLACE TABLE FACT_BH_ENCOUNTER (
    bh_enctr_key    INTEGER        NOT NULL  -- surrogate key,
    enctr_id        VARCHAR(50)    NOT NULL  -- encounter identifier,
    mbr_id          VARCHAR(20)    NOT NULL  -- member identifier,
    prvdr_npi       VARCHAR(10)              -- rendering provider NPI,
    enctr_dt        DATE           NOT NULL  -- encounter date,
    svc_type_cd     VARCHAR(20)              -- service type code,
    diag_cd         VARCHAR(7)               -- primary diagnosis code,
    diag_cd_2       VARCHAR(7)               -- secondary diagnosis code,
    bh_cond_cd      VARCHAR(20)              -- behavioral health condition,
    lvl_of_care_cd  VARCHAR(20)              -- level of care code,
    session_cnt     INTEGER                  -- session count,
    auth_nbr        VARCHAR(30)              -- authorization number,
    fac_type_cd     VARCHAR(20)              -- facility type code,
    paid_amt        DECIMAL(12,2)            -- paid amount,
    rec_creat_dt    TIMESTAMP      NOT NULL  -- record created date
);

Standard Snowflake DDL for the canonical behavioral 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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