Date of Award

January 2016

Document Type

Thesis

Degree Name

Medical Doctor (MD)

Department

Medicine

First Advisor

Leigh Evans

Second Advisor

Steven L. Bernstein

Abstract

Our study aims to determine the effects of race, insurance, and hospital characteristics on the management of threatened abortion and early pregnancy loss. In this retrospective cohort study using the National Hospital Ambulatory Medical Care Survey, patient record files from 2002-2010 with diagnoses of threatened abortion, hemorrhage in pregnancy, or incomplete, inevitable, or unspecified spontaneous abortion were examined using logistic regression. Primary outcomes were rates of admission and active management, defined as surgical termination or use of abortifacients misoprostol or Cytotec. Covariates included race/ethnicity, age, insurance, and hospital location, ownership, and metropolitan status.

Of 5,882,623 ED visits for threatened abortion and early pregnancy loss, 15% were admitted and 1.3% were actively managed. Compared to white women, black women were 0.83 times as likely to be admitted (95% CI 0.83-0.84), but 4.37 times as likely be actively managed (95% CI 4.25-4.50). Admission was more likely for “Other” women (Asian, Native Hawaiian, Native Alaskan, Native American, mixed race; OR 2.14, 95% CI 2.11-2.17), Medicaid/SCHIP (OR 1.24, 95% CI 1.22-1.25) and Self-pay (OR 1.04, 95% 1.03-1.05) compared to reference groups of white and privately insured women. Historically-marginalized groups, including uninsured, black, and “Other” women, were more likely to be actively managed. Exceptions were Latina (OR 0.84, 95% CI 0.80-0.89) and Medicaid/SCHIP-insured women (OR 0.13, 95% CI 0.12-0.15). Nonwhite women were less likely to be treated for pain, especially Latinas (OR 0.29, 95% CI 0.28-0.29).

The etiology of these disparities is complex, but providers may seek to better understand their own preconceptions of patient risk, and to strengthen social support, communication, and shared decision-making.

Comments

This thesis is restricted to Yale network users only. It will be made publicly available on 12/31/2019

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