Digital Library
Welcome to Our New Digital Library
Our new library will let you sort, filter and search for resources in one place. Compiled by CHCANYS staff the library contains tools, materials, reference guides, video recordings and more from a variety of topic areas. From Digital Health and Clinical resources to Policy and Advocacy materials, find everything you need in one convenient database.
Using Granular Race, Ethnicity, and Language (REaL) Data in DRVS to Advance Health Equity in partnership with Azara Healthcare
Health Equity, Chronic Disease, and the Populations We Care For: A Diverse Webinar Series Part 3 Read More »
Health Equity and Chronic Disease in People Identifying as LGBTQIA+
Health Equity, Chronic Disease, and the Populations We Care For: A Diverse Webinar Series Part 2 Read More »
Health Equity and Chronic Disease in People Identifying as LGBTQIA+: Exploring Diabetes Disparities
Health Equity, Chronic Disease, and the Populations We Care For: A Diverse Webinar Series Part 2 Read More »
Health Equity and Chronic Disease in People of Color
Health Equity, Chronic Disease, and the Populations We Care For: A Diverse Webinar Series Part 1 Read More »
REaL Health Information Exchange Slides
Session 1 3/11/2022 Read More »
Health Equity & Data Collection Slides
Jamila Michener, PhD, Associate Professor of Government and Public Policy, Read More »
A Path Forward: Reflections after a Decade of Gathering Granular Ethnicity Information from Patients in a Community Health Care Setting
Elizabeth Lever, MS, Chief Information Officer, Institute for Family Health Read More »
Health Equity and REaL Data Collection Webinar
March 11, 2022 Read More »
REaL Data Collection Slides
This training leverages the AHA Disparities Toolkit to educate health centers on the value and importance of collecting accurate data on patients’ race, ethnicity, and language (REaL). Read More »
REaL Data Collection Video
This training leverages the AHA Disparities Toolkit to educate health centers on the value and importance of collecting accurate data on patients’ race, ethnicity, and language (REaL). Read More »