Let's Analyze, Build, and Collaborate to Make Better Healthcare!

Let's Create Your High-quality Data-driven Projects, One by One

The mimilabs workspace is a publicly accessible data lakehouse that hosts thousands of publicly available healthcare datasets, e.g., datasets from the Centers for Medicare & Medicaid Services, Centers for Disease Control and Prevention, Food & Drug Administration, etc. Specifically, we work with publicly available datasets that can impact:

• healthcare policy
• healthcare administration
• healthcare management and operation
• healthcare finance
• population health
• social determinants of health, and
• any other R&D functions that can (in)directly support the above areas

We ensure all the datasets are up-to-date, correctly parsed, transparently traceable, and ready to be queried. You can just log in to the workspace, query, transform, and extract the data you need - no need to maintain the data ingestion pipelines for messy public datasets.

-- All public datasets are timestamped and up-to-date.
-- Just fill out the {schema} and {table} fields, and run the query right away!
SELECT * FROM mimi_ws_1.{schema}.{table} LIMIT 10;

If you work in healthcare, you will end up using publicly available datasets every day. You may be interested in how many doctors are in a particular geographic area to find the best location for your new clinic. Or, you may be curious about the contracted rates for a set of procedure codes for a group of doctors. You may want to understand the provider performance in different value-based care contracts and find the best providers. With an increasing volume of publicly available datasets and pounding emphasis on the social determinants of health, these data sources present endless possibilities for applications in healthcare.

However, many layers of issues are blocking us from tapping the full potential of these public datasets: Some of the challenges are:

• Difficulty in finding relevant datasets
• Complexity in reading and processing the data
• Dependence on additional datasets for context
• Lack of practical examples for learning

We are tackling these issues by offering a collaborative data cleanroom and combining it with an AI Assistant. So, join us. Let's analyze, build, and collaborate to make better healthcare!