device level

dev_lvl

supply

Updated 5/16/2026

Definition

Hierarchy tier assigned to a medical device within an organizational or classification structure in EHR, supply chain, or MDM systems. Used by data engineers to build parent-child device taxonomies, apply roll-up logic in reporting, and support tiered access controls or cost allocation models in healthcare analytics platforms.

Standard Abbreviation

dev_lvl

Database Usage

-- Example column naming
CREATE TABLE claims (
  clm_id VARCHAR(50),
  dev_lvl VARCHAR(20),  -- device level (max 20 chars)
  ...
);

-- Example in SELECT
SELECT
  clm_id,
  dev_lvl as device_level
FROM claims;

Example database column name

ISO-11179 snake_case standard

-- Recommended column name
dev_lvl

-- Example DDL
CREATE TABLE healthcare_data (
  record_id   VARCHAR(50)   NOT NULL,
  dev_lvl      VARCHAR(20),  -- device level (max 20 chars)
  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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