Date of Award

January 2015

Document Type

Open Access Thesis

Degree Name

Master of Public Health (MPH)

Department

School of Public Health

First Advisor

Xiaomei Ma

Abstract

Background: Racial disparity in chronic infection with hepatitis B virus is a major public health issue in the United States. Limited data exist on rates of screening and diagnosis collected from providers instead of patient self-reported surveys.

Methods: Data were extracted from electronic health records (EHRs) of practices in New York City for 2013. Three measures of hepatitis B (Hep B) screening and diagnosis were collected: 1) lab tests for hepatitis B virus surface antigen (HBsAg); 2) diagnosis via International Classification of Diseases, 9th edition (ICD-9) codes; and 3) of lab tests ordered, positive results. Generalized estimating equation models were used to analyze predictors of Hep B screening and diagnosis across three patient groups: Asians who preferred Chinese, Asians who preferred English, and non-Asian patients.

Results: The study population consisted of 377 practices, with an average of 20% (SD = 33%) Asian patients per practice. On average, 5% (SD = 10%), 0.2% (SD = 0.7%), and 1% (SD = 5%) of patients in a practice were screened, diagnosed, and HBsAg positive respectively. Chinese-preferred Asians were significantly more likely to undergo screening compared to English-preferred Asians (beta=0.97, p-value <.01) or non-Asians (beta = 0.89, p-value <.01). They were also more likely to be diagnosed compared to English-preferred Asians (beta = 1.78, p-value <.01) or non-Asians (beta = 2.96, p-value <.01).

Discussion: Practices were significantly more likely to screen for and make diagnosis of Hep B among Asian sub-groups, but rates remain low. This indicates a need for educational interventions targeting providers or by integrating Hep B quality metrics in EHRs. This analysis of 2013 data provided a baseline estimate of health care delivery patterns of Hep B of a hard-to-reach and high-risk population prior to screening recommendation changes in 2014.

Comments

This is an Open Access Thesis.

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