Indication scoping and codeset mapping now take minutes, down from hours per assignment.
HEALTHCARE ANALYTICS FIRM / DATA AND ANALYTICS
Patient-journey analysis now takes one day, not weeks.
A healthcare analytics firm analyzes $1.1 trillion in annual Medicare claims across Parts A, B, C, and D. Indication scoping took hours, cohort building required repeated handoffs, and Treatment Journey deliverables took days or weeks to revise. PivotX connected codeset identification, cohort assembly, journey reconstruction, and output formatting in a coordinated multi-agent pipeline.
Industry
Healthcare
Function
Data and Analytics
Pipeline
Multi-agent, HIPAA-compliant
Platform
Google Cloud Platform
RESULTS
Hours to minutes
Days to same-day
Cohort building and refinement now run the same day, eliminating multi-day handoffs.
70% faster
Iteration time on complex Treatment Journey deliverables cut by 70%.
Analysts now spend more time interpreting findings and advising clients and less time assembling data.
THE SITUATION
Accurate patient-journey analysis was taking days or weeks.
The client helps pharmaceutical manufacturers, payers, and research organizations define patient populations, map medical codes, and reconstruct treatment journeys using claims data covering 100% of Medicare Part A, B, C, and D.
The work was accurate but slow because indication scoping and codeset mapping required hours. Cohort refinements meant repeated handoffs between analysts and data engineers. Complex deliverables could take days or weeks, with each revision adding more manual work.
01
Indication scoping and codeset mapping measured in hours per assignment
02
Cohort building required repeated handoffs between analysts and engineers
03
Complex Treatment Journey deliverables took days to weeks
04
Each revision created more manual work instead of carrying previous output forward.
THE WORK
What we built
01
A HIPAA-compliant analytics pipeline on Google Cloud
Before working with PivotX, analysts and data engineers passed work back and forth across medical-code selection, cohort assembly, treatment-journey reconstruction, and output formatting.
PivotX built a HIPAA-compliant pipeline on Google Cloud. BigQuery processes Medicare claims at scale, Vertex AI Vector Search finds information based on meaning, and the Gemini Data Analytics API converts analysts' questions into structured data queries. Specialized AI agents complete each stage in sequence.
Analysts can now move from a research question to a completed analysis through one connected workflow, reducing the manual handoffs between analysts and data engineers.
02
Faster analysis with a traceable record
Analysts also needed to show clients how each cohort was defined, which medical codes were used, and how the analysis reached its conclusions.
PivotX designed each agent to record its decisions before passing the work to the next stage. The final output includes a documented record that analysts and clients can review.
Indication scoping now takes minutes, cohorts can be built the same day, and Treatment Journey iteration is 70% faster.
WHERE THIS TRANSFERS
Where this applies
Your analysts spend most of their time assembling data, leaving less time to interpret it.
Long iteration cycles leave clients waiting for revisions before they can act on the findings.
Compliance requires a defensible record, and your current process doesn't produce one automatically.
Proof
Pilots that became operating procedure.
PivotX has taken companies from initial assessment to production-grade AI in weeks, not quarters. The cases below aren’t proofs of concept. They’re actual production.
Which procurement workflow is creating the longest delay?
We can review the manual steps, handoffs, and systems involved and identify a practical place to begin.