Question 1

What is platform engineering for healthcare products?

Accepted Answer

Platform engineering for healthcare is the practice of building a reusable, self-service, compliant data and infrastructure foundation that product teams build on instead of each team assembling its own pipelines. For data-heavy products, it is primarily a governed, HIPAA-aligned data platform for ingestion, storage, processing, and delivery.

Question 2

Why is building data infrastructure for healthcare harder than other industries?

Accepted Answer

Healthcare data is large and varied, including HL7, FHIR, genomic data, device streams, imaging, claims, and unstructured text. Much of it is protected health information subject to HIPAA, interoperability with EHR systems is often required, lineage and governance are important for auditability, and real-time and batch workloads may share the same platform.

Question 3

What are the core components of a healthcare data platform?

Accepted Answer

Core components include ingestion and interoperability, a governed data layer such as a lakehouse, security and compliance controls, batch and streaming processing, data quality and observability, FinOps cost control, and analytics and machine learning readiness.

Question 4

How do you make a healthcare data platform HIPAA compliant?

Accepted Answer

HIPAA-aligned healthcare platforms use security controls designed into the architecture, including isolated network environments, encryption at rest and in transit, customer-managed encryption keys where appropriate, least-privilege access controls, immutable audit logs, consent and PHI tracking, and controlled data paths. Organizations must also apply administrative and operational safeguards appropriate to their specific use case.

Question 5

What is the difference between platform engineering and building data pipelines?

Accepted Answer

A pipeline generally solves a specific workflow for one team. A platform addresses recurring needs such as security, compliance, scale, governance, and cost at the foundation layer, then provides reusable self-service capabilities and guardrails to multiple product teams.

Question 6

How do you control cloud costs for data-heavy healthcare products?

Accepted Answer

Cloud costs can be managed through FinOps practices built into the platform, including cost visibility before deployment, workload-based autoscaling, appropriate use of spot or preemptible capacity, storage tiering, and monitoring that connects spend to data volume and workload behavior.

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