invoice end date
inv_end_dtDefinition
The date marking the conclusion of the billing period or validity window associated with an invoice record. Captured as inv_end_dt in PBM, claims, and vendor management systems, this field defines the upper boundary of service or billing coverage, supports period-based financial reconciliation, and is used alongside the effective date to validate invoice applicability within reporting and payment workflows.
Standard Abbreviation
inv_end_dt
Category
finance
Database Usage
-- Example column naming
CREATE TABLE claims (
clm_id VARCHAR(50),
inv_end_dt DATE, -- invoice end date (date only, no time)
...
);
-- Example in SELECT
SELECT
clm_id,
inv_end_dt as invoice_end_date
FROM claims;Example database column name
ISO-11179 snake_case standard
-- Recommended column name
inv_end_dt
-- Example DDL
CREATE TABLE healthcare_data (
record_id VARCHAR(50) NOT NULL,
inv_end_dt DATE, -- invoice end date (date only, no time)
created_dt TIMESTAMP NOT NULL DEFAULT NOW()
);Column names follow the ISO-11179 naming convention: lowercase, underscore-separated, using the standard abbreviation as a prefix where applicable.
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.
Common uses in healthcare data
- Healthcare data warehouse schema design and modeling
- Interoperability and cross-system data exchange
- ETL pipeline development and orchestration
- Master data management (MDM) programs
- Analytics and business intelligence reporting
- Epic and Cerner data extraction for cross-system analytics pipelines
- Snowflake healthcare data cloud architecture with cross-functional data sharing
- Databricks Lakehouse ingestion pipelines for multi-source healthcare data integration
Related Healthcare Standards
HIPAA (45 CFR Parts 160–164)
The foundational regulation governing healthcare data privacy, security, and electronic transaction standards across the US healthcare system.
HL7 FHIR R4
The dominant healthcare interoperability standard defining how clinical and administrative data is structured and exchanged between systems.
CMS Data Programs
CMS operates multiple data standards programs including NPPES, ICD coding, and Medicare reporting that touch nearly every area of healthcare data.
Data Quality Considerations
- Date format inconsistency is the most pervasive data quality issue across healthcare source systems — enforce ISO 8601 (YYYY-MM-DD) at ingestion before data reaches Snowflake or Databricks.
- Healthcare data frequently contains free-text clinical notes mixed with structured code fields — validate that structured columns do not contain narrative text before loading into your data warehouse.
- Cross-system identifier linkage requires deterministic matching rules — document your linkage keys and enforce foreign key constraints in your Snowflake or Databricks data model to prevent orphaned records.
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