member acuity
mbr_acuityDefinition
ISO-11179 Definition
A scored or tiered measure of a health plan member clinical complexity and intensity of healthcare needs, used to determine appropriate care management program assignment and resource allocation. Member acuity incorporates diagnosis burden, functional status, healthcare utilization patterns, medication complexity, and social determinants of health to produce a composite severity score. High-acuity members typically have multiple comorbidities, frequent hospitalizations, polypharmacy, and unmet social needs requiring intensive care management.
Medicare Advantage Special Needs Plans use acuity assessments to tailor individualized care plans. Healthcare data teams build acuity scoring pipelines that aggregate clinical and claims data into composite scores, maintain acuity history to track changes over time, and integrate acuity scores with care management platforms for nurse caseload management and intervention prioritization.
Standard Abbreviation
mbr_acuity
Category
Production DDL — DIM_MEMBER
CREATE OR REPLACE TABLE DIM_MEMBER (
mbr_key INTEGER NOT NULL -- surrogate key,
mbr_id VARCHAR(50) NOT NULL -- member identifier,
mbr_first_nm VARCHAR(100) -- first name,
mbr_last_nm VARCHAR(100) -- last name,
mbr_birth_dt DATE -- date of birth,
mbr_gndr_cd CHAR(1) -- gender code M/F/U,
mbr_age SMALLINT -- age in years,
mbr_state_cd CHAR(2) -- state code,
mbr_zip_cd VARCHAR(10) -- zip code,
mbr_elig_ind BOOLEAN -- eligibility indicator,
mbr_enrl_dt DATE -- enrollment date,
mbr_term_dt DATE -- termination date,
mbr_plan_cd VARCHAR(20) -- plan code,
mbr_dual_elig_cd VARCHAR(10) -- dual eligibility code,
load_dt TIMESTAMP_NTZ NOT NULL -- load timestamp
);
Standard Snowflake DDL for the canonical member table. Convert to BigQuery or Databricks →
Why This Term Matters
Member and enrollment data governs who receives care and who pays for it — making it foundational to every downstream healthcare analytics workflow. Data engineers who understand member terminology build eligibility pipelines that prevent coverage gaps, correctly identify dual-eligible members, and support accurate risk adjustment submissions to CMS. Enrollment errors directly affect capitation payments and can trigger CMS corrective action plans.
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