PalTech helps a Healthcare ​​Payer Tech Reclaim Data Control and Cuts Costs 

Executive Summary: 

When slow data reporting threatened patient care and rising costs strained operations, a leading U.S. healthcare tech company, managing complex Medicare and Medicaid populations, needed a scalable, cost-effective solution. 

Responsible for coordinating over 2,000 nurse practitioners and managing vast volumes of clinical data from multiple payer clients, the organization faced inefficiencies with outdated reporting systems and growing third-party dependencies. 

We, along with our client, worked together to create a modern, Databricks-powered data lakehouse solution that unified fragmented data sources, enabled low-cost, high-speed processing, and empowered decision-makers through Power BI and GenAI-augmented analytics—all with future-ready scalability and minimal operational overhead. 

Business Problem: 

Data bottlenecks were putting patients and operations at risk 

• Multiple Tableau reports lacked customization and scalability. 

• Slow data cycles delayed patient analytics and risked payer relationships. 

• High reliance on third-party vendors for nurse visit reporting inflated operational costs. 

• Data silos and absence of real-time insights limited visibility and responsiveness. 

A transformation was needed—fast, scalable, and intelligent. 

Solutions Implemented 

To address these challenges, the healthcare payer tech company partnered with PalTech— a trusted Databricks partner with decades of experience in architecting high-performance, scalable data ecosystems. PalTech’s long-standing expertise in managing complex data architectures and orchestrating multi-technology integrations positioned them the ideal partner. Recognizing the client’s need for speed, accuracy, and cost efficiency, PalTech engineered a robust data lakehouse from the ground up, consolidating disparate data sources into a unified, reliable platform. 

Implementation: 

• Architecture 
  We created a segmented arch, with each section symbolizing a step in progress. 
• Delta Tables & Liquid Clustering
  Optimized read/write performance with Databricks’ Delta Lake and liquid clustering for large datasets. 
• Cost-Optimized Pipelines
  Designed for low-volume, low-volatility data streams to reduce compute costs, replacing bulky SQL/SSIS logic. 
• Delta Processing Time
  Used Auto Loader with file notifications to incrementally process data efficiently and used partitioning the Delta tables by relevant columns to reduce scan time. 
• Configurable Minimal Code Design
  Onboarding notebooks were leveraged to streamline the integration of new clients into the system. Predefined validation rules were applied to ensure data quality during the onboarding process. 
• Automated Schedules & Job Chaining
  Implemented Databricks Jobs with task dependencies and error handling notebooks to enable automated, dependency-aware scheduling of data pipelines ensuring optimized resource usage and reliable, sequential execution of workflows. 
• Federated Data Catalogs
  Automated addition of new source catalogs, breaking silos and supporting seamless data federation across systems. 
• Collaborative Analysis
  Leveraging a secure, privacy-centric Data Clean Room environment, we conducted deep analysis to derive actionable insights while ensuring no sensitive or personally identifiable information was exposed. Upon completion, the findings are exported in a user-friendly, easily consumable format for seamless application. 
• Monitoring and Alerts
  A custom alerting job has been implemented in Databricks along with retries to support automated data validation and notify. This solution enables timely communication of data issues through structured email notifications. Enabled Real-Time Query Monitoring on DBSQL with Alerts. 
• Augmented Analytics
  Utilized Databricks AI/BI suite to develop interactive dashboards and deploy Genie for conversational analytics, enabling self-service insights across the organization. 
• Power BI Integration
  Integrated Power BI with Databricks to enable seamless visualization of Lakehouse data allowing real-time reporting and interactive dashboards directly on top of Reporting Delta tables.