Literature DB >> 30789766

Private Insurance Coverage for Diabetes Before and After Enactment of the Preexisting Condition Mandate of the Affordable Care Act, 2005-2016.

Mary A M Rogers1, Catherine Kim1, Joyce M Lee1, Tanima Basu1, Renuka Tipirneni1.   

Abstract

OBJECTIVES: To examine private insurance coverage for persons with diabetes before and after enactment of the preexisting condition mandate of the Affordable Care Act (ACA) in the United States.
METHODS: We conducted a nationwide study in adults aged 20 to 59 years with private health insurance with the Clinformatics Data Mart Database (2005-2016). We used fixed-effects negative binomial regression to evaluate differences in pre-post mandate trends.
RESULTS: There was a 4% decline in prevalence rates of type 1 diabetes in adults with private health insurance before the mandate and an 11% increase afterward (P < .001). Coverage increased to the greatest extent (-6% before, +20% after) in those aged 50 to 59 years (P < .001). For type 2 diabetes, there was a significant decline in prevalence before the mandate, which increased afterward in those aged 40 to 49 years (-4% before, 3% after; P = .031) and 50 to 59 years (-6% before, 15% after; P < .001).
CONCLUSIONS: Adults with diabetes may have benefited in obtaining private health insurance after implementation of the preexisting condition mandate of the ACA. Public Health Implications. Efforts to limit enforcement of these protections are likely to contribute to setbacks in access to care.

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Year:  2019        PMID: 30789766      PMCID: PMC6417562          DOI: 10.2105/AJPH.2018.304933

Source DB:  PubMed          Journal:  Am J Public Health        ISSN: 0090-0036            Impact factor:   9.308


  2 in total

1.  Access to health insurance: experiences and attitudes of those with genetic versus non-genetic medical conditions.

Authors:  Nancy E Kass; Amy M Medley; Marvin R Natowicz; Sara Chandros Hull; Ruth R Faden; Laura Plantinga; Lawrence O Gostin
Journal:  Am J Med Genet A       Date:  2007-04-01       Impact factor: 2.802

2.  Use of administrative and electronic health record data for development of automated algorithms for childhood diabetes case ascertainment and type classification: the SEARCH for Diabetes in Youth Study.

Authors:  Victor W Zhong; Emily R Pfaff; Daniel P Beavers; Joan Thomas; Lindsay M Jaacks; Deborah A Bowlby; Timothy S Carey; Jean M Lawrence; Dana Dabelea; Richard F Hamman; Catherine Pihoker; Sharon H Saydah; Elizabeth J Mayer-Davis
Journal:  Pediatr Diabetes       Date:  2014-06-09       Impact factor: 4.866

  2 in total

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