The CARTS Data Quality Department plays a crucial role in ensuring the reliability and usefulness of crash data, with a particular focus on timeliness, completeness, accuracy, and uniformity. The team supports CARTS' overall objective of providing accurate and reliable crash data to support informed decision-making and effective traffic safety initiatives.

Early crash data quality efforts involved reviewing state crash data submitted on paper reports, which were manually entered and evaluated in-house for accuracy and completeness. As part of these efforts, the department promoted the transition of law enforcement agencies to electronic crash reporting, resulting in significant improvements in data accuracy, completeness, and timeliness.

Since that time, the CARTS Data Quality team has participated in additional federal, state, and peer programs to continually refine and strengthen its practices. These efforts ensure that data quality processes evolve alongside changing stakeholder needs, shifting areas of focus, and advancements in technology that influence crash data reporting.

Key Responsibilities:

• Continuous Monitoring and Review:
  Data Quality staff regularly monitor and review crash data submitted by law enforcement agencies across Louisiana. This ongoing oversight allows the team to identify irregularities, inconsistencies, and potential errors, improving the overall usefulness of the data.
• Collaborative Problem-Solving:
  When data inconsistencies or errors are identified, the Data Quality team collaborates closely with CARTS staff and external stakeholders to develop and implement effective solutions. This collaborative approach ensures that concerns are addressed promptly and effectively.
• Recommendations and Guidance:
  The Data Quality team provides recommendations and guidance to support improve in data quality, including outreach programs, training sessions, instructional videos, and detailed documentation. These resources help law enforcement agencies to collect and report crash data accurately and consistently, while also supporting stakeholders who use and interpret the data.