Data in hospitals
clinical and operational data: EHR and claims data, quality and outcomes measurement, interoperability, and privacy under HIPAA.
This block builds data fluency for healthcare provider organizations such as hospitals, physician groups, and integrated delivery networks. You will learn how core data concepts apply to clinical, operational, and claims environments, then map the datasets that actually drive provider decisions: EHR records, HL7 and FHIR feeds, claims, registries, and quality reporting streams. You will assess data quality and governance using measures suited to patient-level information, and benchmark analytics against recognized provider standards. The block closes with the regulatory and privacy rules that constrain provider data, including HIPAA, plus the governance structures and practical audits that keep clinical data trustworthy, interoperable, and compliant across care settings.
What you'll master
- Identify and evaluate the core provider datasets (EHR, claims, HL7/FHIR, registries) needed for a given clinical or operational question
- Define and apply data-quality and governance metrics appropriate to patient-level clinical and administrative data
- Benchmark provider analytics against sector standards such as CMS quality measures and HEDIS
- Design and run practical data privacy checks and audits to verify HIPAA compliance and data integrity
Key terms
Modules
Covers the core hospital data concepts: clinical versus claims data, quality metrics, interoperability, and PHI governance.
Explores the hospital data landscape, patient identity, data quality scoring, and governance operating models.
Examines privacy laws, consent rules, access governance, and running practical data audits.
Latest articles
Recent articles from the blog that apply to Healthcare Providers.
- One HCP, six records: why identity resolution is pharma's most expensive data problemA single cardiologist can exist as six different entities across a pharma company's CRM, claims data, and prescriber analytics systems, and none of them match. Until identity resolution works in practice, every downstream decision, from sampling allocations to pharmacovigilance reporting, is built on a fractured foundation.
- GxP integrity, 21 CFR Part 11, and GDPR: what happens when three regulatory regimes collidePharma CDOs operate at the intersection of three distinct regulatory systems, each with its own logic, its own enforcement body, and its own definition of what a data record actually is. Understanding where those systems conflict, not just where they overlap, is the difference between audit readiness and a consent notice architecture that accidentally destroys your audit trail.
- Privacy-enhancing technologies in practice: the hype is ahead of the implementationPrivacy-enhancing technologies have generated serious boardroom attention, and the underlying science is real. But the gap between pilot programs and production-grade deployment is wider than most CDOs are being told.
- Privacy-enhancing technologies in practice: a CDO playbookPrivacy-enhancing technologies have moved from cryptography research papers into production pipelines at major financial institutions and healthcare networks. This playbook gives CDOs a concrete sequence to deploy PETs without stalling analytics programmes or exposing the organisation to regulatory backlash.