Finding and Using Health Statistics
Class Experience Level
Beginner, Intermediate, Advanced

How many Americans are affected by cardiovascular disease each year? Are there geographic gaps in access to health care? How do the leading causes of death in the United States differ from those worldwide? Do mRNA vaccines, like the COVID-19, cause cardiovascular events? Does the use of oral contraceptives (birth control pills) increase the risk of breast cancer? The answers to these important questions and many others can be found in data collected by government, private, and non-profit agencies and organizations. The health statistics reported by these groups are critical to monitoring trends in the health status of populations, planning how health care resources are distributed, and evaluating the effectiveness of public health interventions. 

Designed by the National Library of Medicine for health professionals, health sciences librarians and students, this class describes different types of health statistics, how they are collected, and where they can be found.

This presentation meets the NLM/NIH strategic plan goal of building a workforce for data-driven research and health in order to address increasing health information access and use.

Objectives:

After completing this course, you will be able to: 

Explain what health statistics measure and how to use them to assess general health 

List the statistical terms commonly used when reading about health statistics 

Describe different ways health information can be collected, and the pros and cons of each method 

Locate a variety of online sources for health statistics 

Create strategies to find specific health statistics 

By registering for this class, you are agreeing to the NNLM Code of Conduct

Class Details

Platform: Moodle
CE Credits: 3.00
CE Categories: CHES, CHIS Level 1, CHIS Level 2, DSS Level 1
Class Experience Level: Beginner, Intermediate, Advanced
This is a National NNLM class.
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Class Contacts

Host/Instructor: Katherine Majewski
Technical Assistance: Michael Tahmasian