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Clusters, Maps, and Hotspots: Small Area Analysis in Maternal and Child Health

URL 1: https://altarum.adobeconnect.com/_a758956138/dataspeak081215

URL 2: https://mchb.hrsa.gov/sites/default/files/mchb/aug2015slides.pdf

Date Developed: 08/12/2015. Source: U.S. Maternal and Child Health Bureau. Presenter(s): Russell S. Kirby, PhD, MS, FACE; Michael Kramer, PhD, MMSc; Thomas J. Stopka, PhD, MHS . Type: Webinar Archive. Level: Intermediate Advanced. Length: 60 minutes.

Annotation

Maternal and child health professionals are increasingly interested in how health outcomes, risk factors, and health resources vary over space and time. Knowledge about how these factors differ across small segments of the population, such as across different counties or neighborhoods, can help health professionals design interventions for the populations who are most at need. Innovative and rigorous small area analyses are needed to help inform public health decisions that can improve maternal and child health. This DataSpeak presentation gives an overview of the applications of small area analysis for maternal and child health with real world examples based on these analyses.

Learning Objectives

• Review basic principles of mapping and its uses for studying spatial aspects of health phenomena.

• Introduction to small area analysis.

Special Instructions

Webinar recorded using Adobe Connect. Post-Webinar Q&As: https://mchb.hrsa.gov/sites/default/files/mchb/MaternalChildHealthInitiatives/dataspeak/aug2015qa.pdf Transcript: https://mchb.hrsa.gov/sites/default/files/mchb/MaternalChildHealthInitiatives/dataspeak/aug2015transcript.pdf

This project is supported by the Health Resources and Services Administration (HRSA) of the U.S. Department of Health and Human Services (HHS) under grant number UE8MC25742; MCH Navigator for $180,000/year. This information or content and conclusions are those of the author and should not be construed as the official position or policy of, nor should any endorsements be inferred by HRSA, HHS or the U.S. Government.