Examining multimorbidity differences across racial groups: a network analysis of electronic medical records

Pankush Kalgotra,Ramesh Sharda,Julie M Croff

doi:10.1038/s41598-020-70470-8

Abstract

Health disparities across ethnic or racial groups are typically examined through single behavior at a time. The syndemics and multimorbidity health disparities have not been well examined by race. In this study, we study health disparities by identifying the networks of multimorbidities among individuals from seven population groups based on race, including White, African American, Asian, Hispanic, Native American, Bi- or Multi-racial and Pacific Islander. We examined a large electronic medical record (EMR) containing health records of more than 18.7 million patients and created multimorbidity networks considering their lifetime history from medical records in order to compare the network properties among seven population groups. In addition, the networks at organ system level depicting the relationship among disorders belonging to different organ systems are also compared. Our macro analysis at the organ-level indicates that African-Americans have a stronger multimorbidity network followed by Whites and Native Americans. The networks of Asians and Hispanics are sparse. Specifically, the relationship of infectious and parasitic disorders with respiratory, circulatory and genitourinary system disorders is stronger among African Americans than others. On the other hand, the relationship of mental disorders with respiratory, musculoskeletal system and connective tissue disorders is more prevalent in Whites. Similar other disparities are discussed. Recognition and explanation of such differences in multimorbidities inform the public health policies, and can inform clinical decisions as well. Our multimorbidity network analysis identifies specific differences in diagnoses among different population groups, and presents questions for biological, behavioral, clinical, social science, and policy research.

Highlights

Health disparities across ethnic or racial groups are typically examined through single behavior at a time
The proportion test (chi-squared (χ2) test) comparing the number of connections present with respect to the maximum number of possible connections found that there is no statistical difference between the two types of networks (African American: χ2 = 0, p = 1; White: χ2 = 0.001, p = 0.98; Hispanics: χ2 = 0.059, p = 80; Asian: χ2 = 0.033, p = 0.85)
The number of diagnoses pairs i.e. connections in African-Americans were the highest followed by the White, Native Americans, Asians and Hispanics

Summary

Introduction

Health disparities across ethnic or racial groups are typically examined through single behavior at a time. We study health disparities by identifying the networks of multimorbidities among individuals from seven population groups based on race, including White, African American, Asian, Hispanic, Native American, Bi- or Multi-racial and Pacific Islander. Our multimorbidity network analysis identifies specific differences in diagnoses among different population groups, and presents questions for biological, behavioral, clinical, social science, and policy research. We focus on identifying the multimorbidity (a medical condition when two or more diseases are diagnosed in a patient simultaneously) differences by race/ethnicity using the medical data of more than 18.7 million patients in US hospitals, and propose some research questions. It is important to understand the health disparities from comorbidity and multimorbidity lens because if patients belonging to a particular group develop distinct diseases simultaneously, it can have a significant impact on clinical and policy decisions. Our paper is a descriptive analytics paper where our main contribution is to uncover interesting comorbidity patterns across ethnic/racial groups based upon a very large data warehouse, and pose new questions for future research

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Conclusion