Accelerate Data Foundations for AI
A healthcare organization wanted to use data and AI to improve patient outcomes and reduce the cost of care.
Their current data architecture contained data that was siloed and of questionable quality.
Their data platform could not scale to store and process data sets due to size and complexity.
It was difficult to make insights available and actionable in the clinical setting.
Built a unified cloud data analytics and AI platform to ingest, validate, cleanse and integrate diverse data at scale.
Helped to train and mentor an in-house data analytics team to provide data science, analytics, visualization and monitor data quality.
Created standards and reusable templates for presenting insights to clinicians.
Established robust governance and audit processes to improve data quality, identify algorithm bias and validate models.
Combined data from multiple sources such as EHRs, genome sequencers and medical imaging devices and presented insights to clinicians as intuitive reports and interactive dashboards.
Allowed clinicians to make earlier, better diagnoses and identify targeted treatments, reducing the cost of care while improving patient outcomes.
Identified opportunities to streamline administration and create operational efficiencies.