A case study of the 1115 waiver using population health informatics to address disparities

Author:

Sitapati Amy M1,Berkovich Barbara2,Arellano April Moreno3,Scioscia Angela4,Friedman Lawrence S5,Millen Marlene6,Maysent Patricia7,Tai-Seale Ming8,Longhurst Christopher A910

Affiliation:

1. Division of General Internal Medicine and Division of Biomedical Informatics, Department of Medicine, University of California San Diego Health, San Diego, California, USA

2. Hahn School of Nursing, University of San Diego, San Diego, California, USA

3. Department of Medicine, University of California San Diego, San Diego, California, USA

4. Department of Obstetrics, Gynecology and Reproductive Science, University of California San Diego Health, San Diego, California, USA

5. Department of Medicine and Pediatrics, University of California San Diego Health, San Diego, California, USA

6. Division of General Internal Medicine and Division of Biomedical Informatics, Department of Medicine, Chief Medical Information Officer of Ambulatory and Affiliates, University of California San Diego, San Diego, California, USA

7. University of California San Diego Health, San Diego, California, USA

8. Department of Family Medicine and Public Health, and Information Services, University of California San Diego Health, San Diego, California, USA

9. Department of Biomedical Informatics, University of California San Diego Health, San Diego, California, USA

10. Department of Pediatrics, University of California San Diego Health, San Diego, California, USA

Abstract

Abstract As participants in the California Medicaid 1115 waiver, the University of California San Diego Health (UCSDH) used population health informatics tools to address health disparities. This case study describes a modern application of health informatics to improve data capture, describe health disparities through demographic stratification, and drive reliable care through electronic medical record-based registries. We provide a details in our successful approach using (1) standardized collection of race, ethnicity, language, sexual orientation, and gender identity data, (2) stratification of 8 quality measures by demographic profile, and (3) improved quality performance through registries for wellness, social determinants of health, and chronic disease. A strong population health platform paired with executive support, physician leadership, education and training, and workflow redesign can improve the representation of diversity and drive reliable processes for care delivery that improve health equity.

Funder

National Library of Medicine Training

NIH

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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