Agile Transformation for Scalable Healthcare IT
summary
Healthcare IT shifts from years to weeks by adopting two week sprint cadence, embedding HIPAA controls, access management, audit logging and data lineage as backlog items, and validating AI via shadow mode then limited pilot and controlled expansion; scaling uses Agile Release Trains (ART) and program increments, measures success with time to value, sprint predictability, defect escape rates, model accuracy, alert acceptance and provider satisfaction, and treats compliance as continuous rather than a final gate.
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chapters (15)
- 0:00Agile in Regulated AI Era
- 0:59Why Waterfall Fails Now
- 2:16Cost of Standing Still
- 3:10From Waterfall to Agile
- 4:29Sprint Cadence in Healthcare
- 5:26Governance and Compliance Built In
- 6:27Cross Disciplinary Collaboration
- 7:24Agile for AI and LLMs
- 8:13Incremental AI Validation
- 9:19Layered Capability Delivery
- 10:08Building Agile Ready Culture
- 10:46Scaling with SAFe
- 11:47Common Transformation Pitfalls
- 12:26Measuring Agile Success
- 13:21Key Takeaways and Closing
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