Data Warehousing for Hospitals: Clinical, Operational, and Financial Data in One Trusted Layer

A hospital builds a data warehouse and the clinical leadership doesn't trust it. The reasons are familiar: the warehouse encounter count differs from the EHR by a few percent because exclusion logic differs (which encounters count as inpatient, which as observation, how transfers are handled). The patient demographics show race and ethnicity values that differ from the EHR because the warehouse used a different mapping. The financial metrics don't tie to the cost report or the IPPS payment reconciliation because the dimensional model didn't encode DRG assignment correctly. Each difference is small. Together they make the warehouse a parallel reality the clinical and finance teams treat with suspicion.

Hospital data warehousing done right encodes the EHR semantics correctly from day one. Encounter classification logic that matches what the EHR considers inpatient vs observation vs outpatient. Patient demographics with the value mappings the EHR uses. Provider attribution that matches credentialed providers. MS-DRG assignment from the EHR's grouper logic. Quality measure denominators that match the eCQM specifications. And reconciliation against the EHR after every load that proves the warehouse matches the source. Done with this discipline, the warehouse is the trusted analytics source. Done generically, it stays a parallel reality.