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Health StatisticsShaping policy and practice to improve the population's health$
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Daniel J. Friedman, Edward L. Hunter, and R. Gibson Parrish

Print publication date: 2005

Print ISBN-13: 9780195149289

Published to Oxford Scholarship Online: September 2009

DOI: 10.1093/acprof:oso/9780195149289.001.0001

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Health Statistics from Nonhealth Sources

Health Statistics from Nonhealth Sources

Chapter:
(p.161) Chapter 7 Health Statistics from Nonhealth Sources
Source:
Health Statistics
Author(s):

Walter Phillip Bailey

Amy Brock Martin

Elizabeth H. Corley

Daniel J. Friedman

R. Gibson Parrish II

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195149289.003.0007

Traditional health statistics provide a baseline of information that helps characterize the health of a population or population subgroup. Where health statistics often fall short is in their ability to identify factors that affect population health but fall outside the traditional purview of public health agencies or health care providers. The term complementary data is used to refer to data on those factors that affect population health and yet are not generally collected by, or analyzed within, U.S. public health agencies. Examples include data on air and water quality monitoring, transportation, employment, crime, abuse and neglect, tax revenues from the sale of tobacco and alcohol, and housing characteristics. This chapter describes the major types of complementary data and presents examples of the use of such data. The examples provide an understanding of the variety of ways in which complementary data can be used. When both traditional health data and complementary data contain sufficient detail to enable linkage, powerful tools for assessing communities, designing and targeting programs, evaluating programs, creating knowledge, and informing the public emerge.

Keywords:   public health agencies, complementary data, data systems, population health statistics, health care providers, complementary data

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