Data analytics refer to the practice of collecting, interpreting, and reporting information to make informed decisions. Data science can be applied in areas such as selection, training and coaching or to determine if an investment program warrants consideration. Ultimately the goal is to help organizations make more informed decisions that increase performance.
CDC’s SUID and SDY Case Registry provides data about sudden unexplained infant death (SUID) and sudden unattended child deaths (SUDY), and also works with 10 participating sites using both data from this Case Registry as well as enhanced investigations to identify risk factors associated with these deaths.
The SUDY component builds upon the work of the SUID Case Registry by including a network of local health departments and community-based organizations in collecting surveillance data on SUID/SDY deaths. Working in concert with the CDC, these partners will identify local factors which increase risks and develop evidence-based strategies to decrease them.
Information regarding sudden infant death syndrome (SUID) deaths and sudden dysentery deaths (SUDY) are vital components of public health responses, and timely reporting allows action to be taken to prevent future unsolved SUID cases. The CDC will provide updates as they become available.
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SUDY is often applied to questions of selection and training, but can also be used to assess whether certain programs or approaches will enhance performance. Furthermore, it can help test validity hypotheses as well as make decisions on how best to proceed.
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