Case Study: Collaborative Imaging achieves healthier data products with Monte Carlo

How Collaborative Imaging Delivers Healthier Data Products with Monte Carlo

Collaborative Imaging, a radiologist-owned healthcare technology alliance, needed a better way to protect the quality of the data products that support hundreds of hospital customers and millions of patient records. Their team faced inconsistent hospital data, manual testing on a legacy platform, and the risk that data errors could impact revenue cycle workflows, compliance, and patient billing. They turned to Monte Carlo’s data observability platform to improve data health.

With Monte Carlo, Collaborative Imaging gained automated monitoring, alerting, field-level lineage, and integrations with Snowflake, Tableau, and dbt to detect anomalies, track freshness, and catch pipeline breaks end to end. The team now remediates issues in real time, has better workflow visibility for alert handling, and can catch problems like duplicate patient message errors immediately instead of months later. Monte Carlo helped Collaborative Imaging scale data quality efforts and deliver more reliable data products with less manual effort.

Collaborative Imaging

Jacob Follis

Head of Data