The National Health Plan Collaborative has created this toolkit of resources, lessons, best practices and case studies to help other health plans join the effort to reduce disparities. The toolkit shares what the Collaborative's members have done to develop and test new methods of measuring and addressing racial and ethnic disparities so that other health care decision-makers and leaders can learn from this work, implement these best practices and make the case for addressing the unacceptable differences in health care and health outcomes for health plan members throughout the country.
Useful resources featured in this toolkit include:
- Health plan case studies;
- Sample tools, forms, policies and resources for implementation;
- Videos of experts talking about the importance of reducing disparities and about firsthand experiences in developing and implementing interventions; and
- A compilation of resources in the field.
Introduction: Answers to why disparities in health and health care should be addressed and a description of the National Health Plan Collaborative.
Data Collection: A summary of national and local policies on data collection; a description of why it is important to collect primary race, ethnicity and language data; and methods the health plans have used for collecting race, ethnicity and language data.
Language Access: A discussion of why patient-provider communication is important; state and federal policies that affect language assistance in health care; how to plan for language services; how to implement interpretation services; how to provide materials in different languages; and how to ensure the quality of language access services.
Business Case: Tools and information for making the business case for improving quality and addressing disparities in your health plan.
Acknowledgements The National Health Plan Collaborative would like to thank the Agency for Healthcare Research and Quality, the Robert Wood Johnson Foundation, the Center for Health Care Strategies and the RAND Corporation for their support and technical assistance in the creation of this toolkit.
- 1. What Categories of Race/Ethnicity to Use?
- 2. Direct REL Data Collection Methods
- 3. Section 5: Case Studies
- 3.1. Harvard Pilgrim Health Care: Pilot Test of IVR Outreach Calls as a Mechanism for Collecting REL Data
- 3.2. Molina Healthcare's TeleSalud Program: Providing Direct Access to Language Services
- 3.3. Kaiser Permanente: Qualified Bilingual Staff Model
- 3.4. Kaiser Permanente: Health Care Interpreter Certificate Program
- 4. Indirect REL Data Collection Methods
- 5. Chapter 5: Promising Practices in Interpreter Training and Competency Assessments