aco attribution
aco_attr_cdDefinition
ISO-11179 Definition
The algorithm-based process of assigning Medicare fee-for-service beneficiaries to a specific Accountable Care Organization based on their historical pattern of primary care utilization, determining which beneficiaries are included in the ACO attributed population for quality measurement and financial performance calculation. CMS uses a prospective and retrospective attribution methodology for MSSP — beneficiaries are preliminarily assigned based on prior year primary care utilization and final assignment is determined after the performance year ends based on actual utilization during the year. Attribution is step-sequential, first identifying beneficiaries who received a primary care service from an ACO physician with a primary care designation and then expanding to other ACO providers.
Healthcare data teams build attribution algorithms that replicate CMS methodology to project which beneficiaries will be attributed, track attributed population characteristics for risk stratification, and analyze attribution churn to understand which beneficiaries are gained and lost between performance years.
Standard Abbreviation
aco_attr_cd
Category
Production DDL — FACT_QUALITY_MEASURE
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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