place of service code
rc_pos_cdDefinition
ISO-11179 Definition
A two-digit code used on professional claims to identify the setting where a healthcare service was delivered to the patient, directly affecting the applicable fee schedule rate and facility versus non-facility payment determination under Medicare and commercial payer contracts. CMS maintains the Place of Service code set used on CMS-1500 professional claims, with common codes including 11 for physician office, 21 for inpatient hospital, 22 for hospital outpatient department, 23 for emergency room, 24 for ambulatory surgical center, 31 for skilled nursing facility, and 02 for telehealth in the patient home. The same procedure code carries different payment amounts depending on place of service — non-facility rates for office-based services exceed facility rates for the same service delivered in a hospital outpatient setting because the facility bills separately for overhead.
Healthcare data teams analyze pos_cd distributions to track care setting migration, identify place of service billing errors that affect reimbursement accuracy, and measure telehealth service volumes by place of service code.
Standard Abbreviation
rc_pos_cd
Category
Production DDL — FACT_CLAIM_TRANSACTION
CREATE OR REPLACE TABLE FACT_CLAIM_TRANSACTION (
clm_txn_key INTEGER NOT NULL -- surrogate key,
clm_id VARCHAR(50) NOT NULL -- claim identifier,
mbr_key INTEGER NOT NULL -- FK to DIM_MEMBER,
prvdr_key INTEGER NOT NULL -- FK to DIM_PROVIDER,
clm_typ_cd VARCHAR(10) -- claim type code,
tot_chrg_amt DECIMAL(18,2) -- total charged amount,
tot_alwd_amt DECIMAL(18,2) -- total allowed amount,
tot_pd_amt DECIMAL(18,2) -- total paid amount,
cntrct_adj_amt DECIMAL(18,2) -- contractual adjustment,
denial_ind CHAR(1) -- denial indicator,
denial_rsn_cd VARCHAR(10) -- denial reason code,
prior_auth_nbr VARCHAR(30) -- authorization number,
clm_lag_days SMALLINT -- claim lag days,
days_ar SMALLINT -- days in AR,
load_dt TIMESTAMP_NTZ NOT NULL -- load timestamp
);
Standard Snowflake DDL for the canonical finance 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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