98
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Out-of-pocket spending and financial burden among low income adults after Medicaid expansions in the United States: quasi-experimental difference-in-difference study

      research-article

      Read this article at

      ScienceOpenPublisherPMC
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objective

          To examine the association between expansion of the Medicaid program under the Affordable Care Act and changes in healthcare spending among low income adults during the first four years of the policy implementation (2014-17).

          Design

          Quasi-experimental difference-in-difference analysis to examine out-of-pocket spending and financial burden among low income adults after Medicaid expansions.

          Setting

          United States.

          Participants

          A nationally representative sample of individuals aged 19-64 years, with family incomes below 138% of the federal poverty level, from the 2010-17 Medical Expenditure Panel Survey.

          Main outcomes and measures

          Four annual healthcare spending outcomes: out-of-pocket spending; premium contributions; out-of-pocket plus premium spending; and catastrophic financial burden (defined as out-of-pocket plus premium spending exceeding 40% of post-subsistence income). P values were adjusted for multiple comparisons.

          Results

          37 819 adults were included in the study. Healthcare spending did not change in the first two years, but Medicaid expansions were associated with lower out-of-pocket spending (adjusted percentage change −28.0% (95% confidence interval −38.4% to −15.8%); adjusted absolute change −$122 (£93; €110); adjusted P<0.001), lower out-of-pocket plus premium spending (−29.0% (−40.5% to −15.3%); −$442; adjusted P<0.001), and lower probability of experiencing a catastrophic financial burden (adjusted percentage point change −4.7 (−7.9 to −1.4); adjusted P=0.01) in years three to four. No evidence was found to indicate that premium contributions changed after the Medicaid expansions.

          Conclusion

          Medicaid expansions under the Affordable Care Act were associated with lower out-of-pocket spending and a lower likelihood of catastrophic financial burden for low income adults in the third and fourth years of the act’s implementation. These findings suggest that the act has been successful nationally in improving financial risk protection against medical bills among low income adults.

          Related collections

          Most cited references18

          • Record: found
          • Abstract: found
          • Article: not found

          Too much ado about two-part models and transformation? Comparing methods of modeling Medicare expenditures.

          Many methods for modeling skewed health care cost and use data have been suggested in the literature. This paper compares the performance of eight alternative estimators, including OLS and GLM estimators and one- and two-part models, in predicting Medicare costs. It finds that four of the alternatives produce very similar results in practice. It then suggests an efficient method for researchers to use when selecting estimators of health care costs. Copyright 2004 Elsevier B.V.
            • Record: found
            • Abstract: found
            • Article: not found

            Interaction terms in nonlinear models.

            To explain the use of interaction terms in nonlinear models. We discuss the motivation for including interaction terms in multivariate analyses. We then explain how the straightforward interpretation of interaction terms in linear models changes in nonlinear models, using graphs and equations. We extend the basic results from logit and probit to difference-in-differences models, models with higher powers of explanatory variables, other nonlinear models (including log transformation and ordered models), and panel data models. EMPIRICAL APPLICATION: We show how to calculate and interpret interaction effects using a publicly available Stata data set with a binary outcome. Stata 11 has added several features which make those calculations easier. LIMDEP code also is provided. It is important to understand why interaction terms are included in nonlinear models in order to be clear about their substantive interpretation. © Health Research and Educational Trust.
              • Record: found
              • Abstract: not found
              • Article: not found

              Testing hypotheses about interaction terms in nonlinear models

                Author and article information

                Contributors
                Role: research scientist
                Role: K T Li professor of health policy
                Role: professor of health policy
                Role: assistant professor of medicine and health policy
                Journal
                BMJ
                BMJ
                BMJ-US
                bmj
                The BMJ
                BMJ Publishing Group Ltd.
                0959-8138
                1756-1833
                2020
                5 February 2020
                : 368
                : m40
                Affiliations
                [1 ]Division of General Internal Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA
                [2 ]Department of Health Policy and Management, Harvard T H Chan School of Public Health, Boston, MA, USA
                [3 ]Department of Medicine, Harvard Medical School, Boston, MA, USA
                [4 ]Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA, USA
                [5 ]Department of Health Policy and Management, UCLA Fielding School of Public Health, Los Angeles, CA, USA
                [6 ]UCLA Center for Health Policy Research, Los Angeles, CA, USA
                [7 ]Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
                Author notes
                Correspondence to: H Gotanda Hiroshi.Gotanda@ 123456cshs.org (or @HiroshiGotanda on Twitter)
                Author information
                http://orcid.org/0000-0003-4238-0171
                http://orcid.org/0000-0002-1937-4833
                Article
                goth052217
                10.1136/bmj.m40
                7190017
                32024637
                43e47b73-5c1c-408e-ac43-c02633389602
                © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 04 December 2019
                Categories
                Research
                1779

                Medicine
                Medicine

                Comments

                Comment on this article

                Related Documents Log