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  • Author
    Bethlehem Michael
  • PI

    Dr. Janet Pregler, Dr. Heather McCreath

  • Co-Author

  • Title

    Factors Contributing to the Inability to Access Care Amongst MIDUS Participants

  • Program


  • Other Program (if not listed above)

    Leichtman-Levine-TEM Summer Mentorship in Women's Health Research

  • Abstract

    Background: Healthcare access includes the ability to gain entry into the healthcare system, to access places to obtain needed services, and to connect with providers that address the needs of their patients [1]. Factors such as insurance status, ability to pay for healthcare services, neighborhood, race and ethnicity, gender, and age influence individuals’ ability to access the care they need and in turn, how they utilize healthcare resources. [1,2]. The implementation of the Patient Protection and Affordable Care Act (ACA) in 2010 has shifted healthcare structures in an effort to improve access to health insurance, minimize healthcare costs, and expand access to care [3]. It is important to assess healthcare access prior to and after the implementation of the ACA to better understand the shifts in the US healthcare structure in recent years.

    Objectives: In this study, we characterize healthcare access for two cohorts of MIDUS participants and investigate factors that can impact self-reported inability to get care needed.

    Methods: We analyzed phone interview and survey responses from 2 cohorts from the Midlife in the US (MIDUS) Study: respondents to a follow-up survey in 2004-2006 (N=5555) of the original cohort and the initial survey of the cohort recruited 2011-2014 (N=3577).  We used chi-square and t-tests to evaluate differences by cohort for healthcare access, defined as needed care but couldn’t get it within the past 12 months, and demographic and psychosocial variables: gender, age, race, education, income, insurance type, perceived neighborhood quality, experiences of lifetime discrimination, experiences of receiving inferior medical care, negative work-to-family spillover, and negative family-to-work spillover. We then examined relationships between needed care and the other variables through bivariate analyses and logistic regression.

    Results: No differences by cohort were observed. Several variables were significantly associated with needing care in the logistic model: gender (men less likely to need care (OR=0.62, 95% CI 0.47-0.82), insurance type (those with no insurance more likely to need care vs those with insurance of different types), race (White participants less likely to need care than Black participants (0.55, 0.38-0.79) and other non-White participants (0.59, 0.42-0.83)), education (those with high school or less (1.51, 1.06-2.16) and with some college/Associates’ degree (1.76, 1.26-2.43) were more likely to need care than those with college education), lifetime experiences discrimination (1.26, 1.19-1.35), and negative work-to-family spillover (1.13, 1.08-1.18).

    Conclusion: Several demographic variables were associated with needing care but being unable to get it.  Of note, two psychosocial variables (lifetime discrimination and negative work to family spillover) were also associated with needing care. Such findings illustrate how problems with access to care require multi-faceted solutions.

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