Case Study

Guidehouse Helps Modernize CDC’s National Quitline Data Warehouse

The U.S. Centers for Disease Control and Prevention’s National Quitline Data Warehouse improves data transfer, accessibility, and epidemiological utility using Guidehouse’s integrated data analytics approach.

Challenge

The U.S. Centers for Disease Control and Prevention’s (CDC’s) National Quitline Data Warehouse (NQDW), part of the Office on Smoking and Health (OSH), is a large data repository that serves as a continuing national resource for data on the services, utilization, and success of 54 quitlines. This includes quitlines in all 50 states, the District of Columbia, Guam, Puerto Rico, and the National Asian Smokers' Quitline.

While NQDW data are submitted at regular intervals, formats vary by state and territory, resulting in inconsistent and incomplete submissions and processing delays that compromise data utility. Improvements were needed across the entire NQDW life cycle, from data collection and management to analysis, reporting, and epidemiological research.

 

Solution

For more than 15 years, Guidehouse has served most of CDC’s National Centers, Institutes, and Offices, supporting its Data Modernization Initiative, among other major cross-agency efforts.

With automation as a central focus, Guidehouse implemented a six-step approach to enhance data collection and analysis, tailor data processing, and build a secure data management process to ensure data integrity. This included developing a solution to automate data translation and quality checks to increase the consistency, accessibility, and utility of the quitline data.

Modernize CDC’s National Quitline Data Warehouse  

Impact

Aligned to CDC’s North Star Architecture and data modernization priorities, the approach has improved OSH’s ability to answer high-priority research questions. It also helped to modernize OSH’s processes, reducing the burden on and providing greater transparency to grantees.

NQDW data are used to assess and evaluate tobacco control programs and services, which informs research, decision-making, and technical assistance.

Additional improvements being made to enhance the utility and value of these data include:

  • Automation, requiring less manual data processing
  • Efficiencies in data collection and analysis resulting from process improvements in quitline data submissions
  • Dashboards used for program management across the entire NQDW data life cycle, summarizing current status in requesting and receiving data and laying the foundation for future data ingestion, processing, and analysis
  • Modernized data management and storage, enabled by transitioning to CDC’s Enterprise Data Analytics and Visualization platform in alignment with the North Star Architecture
  • Scientific support, including statistical analysis and manuscript preparation

The custom integrated data analytics approach provides critical steps to modernize CDC’s NQDW. In collaboration with OSH, Guidehouse developed a composite score analyzing 11 key data areas and three mandatory data areas to develop an average data quality score.

The six-step approach for enhanced data collection, used by Guidehouse, resulted in an improvement in the average data quality score, from 55.3% in 2021 to the current average data quality score of 82.2% for 2024. Improvements in processes, from data submission and consistency through data retrieval and analysis, are laying a solid foundation for the accessibility and utility of these data for state reporting, program benchmarking, and a range of future epidemiological analysis.


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