High-quality data is accurate, complete, relevant, timely, valid, and reliable.

High-quality data allows staff to analyze information and draw conclusions to make decisions. To make sure data is high quality, staff who enter and use health data need to be trained. Programs should also check to make sure their data management systems work well.

Here are some ways to tell if data is high quality:  

• Accurate: The information is factual, correct, and free from errors.
• Complete: No information is missing.
• Relevant: Data is appropriate for learning about an issue or problem.
• Timely: Data is current.
• Valid: The information measures what it is supposed to measure.
• Reliable: Data is dependable and consistent. 

Tips and Strategies for Data Quality

• Set up a process to collect high-quality data. Consider these questions:
  • What data will you collect?
  • Who will collect the data?
  • What tools will they use for data collection?
  • How will you train staff to make sure they know how to collect and enter the data for recordkeeping and reporting, whether you use paper forms or an electronic system?
• Set up a system to review your data. Consider these steps:
  • Regularly spot-check data for consistency, accuracy, and completeness.
  • Correct any data quality concerns at once.
  • Analyze the data to make sure it can answer your questions.
  • Review your data often so the information is current.
  • Draw conclusions and use them to make improvements if needed.  
• Use and share the data. Consider these groups who may be interested in your data or can help you get more data:
  • Governing body or Tribal Council
  • Policy Council
  • Program leaders, administrators, and staff  
  • HMHSAC and other community partners
  • Families

Learn More

• Use Data and Evaluation to Inform Decision-Making
• How to Find and Use Health Data
• What Is Quality Data for Programs Serving Infants and Toddlers?