Using Data to Drive Smarter Healthcare Decisions
Turning an idea into $1.5M in revenue at HealthJoy.
tl;dr
Situation
HealthJoy wanted to improve outcomes for self-funded employers by proactively guiding employees to better, more cost-effective care. A promising idea emerged: integrate data from third-party administrators (TPAs) to identify upcoming procedures and intervene early. But no infrastructure or tooling existed to support this vision.
Task
As the newly hired Senior Product Manager, I was tasked with turning this raw idea into a functioning, scalable system. That meant sourcing and normalizing disparate healthcare data, enabling outreach workflows, and proving measurable ROI to both clients and internal stakeholders.
Action
I designed and built a custom ETL pipeline to ingest claims, eligibility, and pre-authorization data from multiple TPA sources. I taught myself SQL, Looker, and Redash to deliver dashboards for concierge teams, and developed a dynamic Google Sheets ROI model for use by sales and partnerships. I also personally handled TPA relationships, technical mappings, and validation of messy, non-standardized data feeds.
Result
Within 12 months, the new TPA data integration program generated over $1.5M in additional revenue. It became a core component of HealthJoy’s go-to-market strategy, empowering proactive care interventions and closing key deals with a trusted, transparent ROI narrative.
Role
Senior Product Manager, TPA Integration
Summary
At HealthJoy, I turned a conceptual idea from a sales exec into a high-impact capability: integrating data from third-party administrators (TPAs) to enable smarter, more proactive healthcare navigation. In just one year, I built a full ETL pipeline from scratch, empowered our concierge team to intervene before costly treatments happened, and created a predictive ROI model that helped generate $1.5M in new revenue.
The Challenge
HealthJoy served several self-funded employers—companies that pay for employee healthcare costs out of pocket rather than buying insurance plans. Every unnecessary or overly expensive treatment directly affected their bottom line.
We realized that TPAs—external administrators who manage claims, pre-authorizations, and eligibility data—held critical early-warning signals. For instance, a pre-authorization for a knee replacement (essentially a doctor's request for insurance approval) could tell us *in advance* that someone was headed toward an expensive procedure.
If HealthJoy could tap into that data in real-time, we could:
Identify upcoming procedures
Intervene early with better alternatives
Save the employer money, while providing higher-quality care to the employee
But no infrastructure for this existed. No integrations. No pipelines. No user-facing tooling.
What I Did
Built A Scalable Infrastructure
Designed and implemented an ETL system (Extract, Transform, Load) that collected data from multiple TPAs and funneled it into a unified analytics database.
Taught my self and used SQL, Looker, Snowflake, and Redash to process and visualize the data.
Personally normalized inconsistent formats across TPAs. For example:
Mapped CPT codes (procedure codes used for billing) and ICD-10 codes (diagnostic codes) that were labeled differently by each TPA.
Identified and standardized provider IDs (unique codes for clinics, doctors, etc.) across data sets.
Note:
In U.S. healthcare, there's very little standardization between vendors. The same field might be named differently or use conflicting formats across TPAs.
Enabled Proactive
Healthcare Outreach
Created Looker dashboards for our Healthcare Concierge team—a human support team who guides employees through benefits decisions.
These dashboards flagged upcoming procedures and provided concierge reps with data to suggest better options.
Example:
If an employee was pre-authorized for a knee replacement at Facility A, the concierge could check cost and quality ratings at nearby facilities and proactively recommend Facility B, which might be closer, cheaper, or higher-rated.
Built a Transparent ROI Model
Used years of historical claims and concierge data to build a predictive ROI model—calculating potential cost savings from steering employees to better care.
Built an interactive, client-facing Google Sheets tool that dynamically pulled data and let teams simulate ROI using real-world inputs.
Ensured full transparency by exposing the math and logic behind the model—an important trust signal in healthcare sales.
Why This Mattered:
In healthcare, vendors often make vague ROI claims. Our model stood out because it was data-driven, clear, and client-adjustable.
Collaborated Cross-Functionally
Managed relationships with TPA partners, serving as both the technical and business point of contact.
Led weekly syncs with engineering, concierge ops, business intelligence, and partner teams.
Balanced data complexity, regulatory privacy requirements, and user needs to create a secure, useful system.
Results
$1.5M+ in new revenue in the first year—attributed directly to the TPA data program.
New product capabilities became a key sales differentiator, helping close partnerships and upsells.
The ETL and dashboard infrastructure became a foundation for future data-driven outreach programs.
Strong relationships built with partners and internal teams—plus a mentor gained along the way.
This project was a turning point for me as a product leader. I had no prior experience with medical claims or healthcare infrastructure—but I dove in, learned quickly, and shipped something that fundamentally changed how HealthJoy worked with TPAs and customers.
In one year, I:
Built an ETL system from scratch
Learned advanced SQL, Looker, and cloud data tooling
Became fluent in U.S. healthcare data formats (CPT, ICD-10, NPI, etc.)
Created a live ROI model used by sales, partnerships, and customer success
Delivered measurable revenue and strategic impact
It was messy, complicated, and deeply rewarding…