Enhancing Healthcare Quality Insights with Snowflake – A Recap from HIMSS

Events

We were thrilled to participate in the HIMSS Conference this year, where Mass General Brigham joined Snowflake to co-present “Enhancing Healthcare Quality Insights: Leveraging Snowflake, Python, and Tableau for Faster Performance Metrics.” Mike Pandolfi provided valuable insights into how migrating on-premises data warehouses and other manual sources to Snowflake significantly improved the performance and availability of their OCMO Quality Dashboard in Tableau.

Leveraging Snowflake for Enhanced Healthcare Insights

This presentation covered several innovative Snowflake technologies that played a crucial role in optimizing data transformation and availability:

Snowflake Stored Procedures
- Stored SQL used to load and transform data for specific ETL steps, ensuring data integrity and consistency.
Snowflake Python Libraries: Connector and SQLAlchemy
- Enabled connecting and loading Snowflake tables from a Python notebook outside the Snowflake environment, enhancing flexibility and functionality.
Snowflake SnowSQL Commands

Utilized the PUT command to place CSV files from a local location into a Snowflake stage, streamlining the ETL process and ensuring efficient data management.

Additional tools such as Azure Data Factory, Python Notebooks, and Vizient APIs were integral to the success of this implementation. Azure Data Factory facilitated the copying of tables from on-premises EDW into Snowflake, while Python Notebooks handled data download from APIs, light transformations, and staging. Finally, Tableau connected to Snowflake SQL tables, providing a powerful platform for visualizing and exploring quality metrics across four critical domains—Effectiveness, Equity, Experience, and Safety.

Creating Actionable Insights from Diverse Data Sources

The implementation integrated data from various sources, including Epic Clarity, Vizient, HCAHPS, Real-Time Surveys, NDNQI, and NHSN, into a unified OCMO Quality Dashboard. By structuring unstructured data and centralizing it in Snowflake, we enabled seamless analysis and reporting.

Using Snowflake’s advanced tools, we extracted key insights from clinical data, such as effectiveness measures, equity assessments, patient experience feedback, and safety protocols. These extracted elements were then organized into structured formats, making the data much easier to analyze and incorporate into reports. This capability allows clinician-researchers to utilize previously untapped data, providing deeper insights into healthcare quality and outcomes.

Lowering Barriers to Data Exploration

The ability to structure unstructured data dramatically lowers the barriers to data exploration. With Snowflake’s Python Libraries and SQL capabilities, researchers can perform complex transformations and queries with ease. Tableau’s integration with Snowflake SQL tables allows for the creation of detailed and summary dashboards, enabling quick trend exploration and informed decision-making.

Furthermore, Snowflake’s centralized governance and security through role-based access control (RBAC) ensure that data remains secure while being readily accessible for analysis. This comprehensive approach not only enhances the accuracy and depth of clinical research but also fosters a more inclusive and collaborative environment for healthcare professionals.

Our collaboration with Snowflake and Mass General Brigham at HIMSS showcased how these innovative tools and technologies are making a significant impact on healthcare quality insights. By reducing barriers to data exploration and facilitating rapid, accurate reporting, we are paving the way for more efficient and effective healthcare improvements.

For more information and to learn how Prominence Advisors can help your organization leverage its data, explore our innovative data enablement solutions.

Together, let’s move mountains and make a transformative impact in healthcare.