State-Level Population Estimates of Individuals Subject to and Not Meeting Proposed Medicaid Work Requirements.
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ABSTRACT:
SUBMITTER: Silvestri DM
PROVIDER: S-EPMC6248197 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description: Not available
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Project description:Alternative approaches in Medicaid are proliferating under the Trump administration. Using a novel telephone survey, we assessed views on health savings accounts, work requirements, and Medicaid expansion. Our sample consisted of 2,739 low-income nonelderly adults in three Midwestern states: Ohio, which expanded eligibility for traditional Medicaid; Indiana, which expanded Medicaid using health savings accounts called POWER accounts; and Kansas, which has not expanded Medicaid. We found that coverage rates in 2017 were significantly higher in the two expansion states than in Kansas. However, cost-related barriers were more common in Indiana than in Ohio. Among Medicaid beneficiaries eligible for Indiana's waiver program, 39 percent had not heard of POWER accounts, and only 36 percent were making required payments, which means that nearly two-thirds were potentially subject to loss of benefits or coverage. In Kansas, 77 percent of respondents supported expanding Medicaid. With regard to work requirements, 49 percent of potential Medicaid enrollees in Kansas were already employed, 34 percent were disabled, and only 11 percent were not working but would be more likely to look for a job if required by Medicaid. These findings suggest that current Medicaid innovations may lead to unintended consequences for coverage and access.
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Project description:In June 2018 Arkansas became the first US state to implement work requirements in Medicaid, requiring adults ages 30-49 to work twenty hours a week, participate in "community engagement" activities, or qualify for an exemption to maintain coverage. By April 2019, when a federal judge put the policy on hold, 18,000 adults had already lost coverage. We analyze the policy's effects before and after these events, using a telephone survey performed in late 2019 of 2,706 low-income adults in Arkansas and three control states compared with data from 2016 and 2018. We have four main findings. First, most of the Medicaid coverage losses in 2018 were reversed in 2019 after the court order. Second, work requirements did not increase employment over eighteen months of follow-up. Third, people in Arkansas ages 30-49 who had lost Medicaid in the prior year experienced adverse consequences: 50 percent reported serious problems paying off medical debt, 56 percent delayed care because of cost, and 64 percent delayed taking medications because of cost. These rates were significantly higher than among Arkansans who remained in Medicaid all year. Finally, awareness of the work requirements remained poor, with more than 70 percent of Arkansans unsure whether the policy was in effect.
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Project description:To provide state-level estimates of obesity-attributable costs of absenteeism among working adults in the United States.Nationally representative data from the National Health and Nutrition Examination Survey for 1998 to 2008 and from the Behavioral Risk Factor Surveillance System for 2012 are examined. The outcome is obesity-attributable workdays missed in the previous year because of health and their costs to states.Obesity, but not overweight, is associated with a significant increase in workdays absent, from 1.1 to 1.7 extra days missed annually compared with normal-weight employees. Obesity-attributable absenteeism among American workers costs the nation an estimated $8.65 billion per year.Obesity imposes a considerable financial burden on states, accounting for 6.5% to 12.6% of total absenteeism costs in the workplace. State legislatures and employers should seek effective ways to reduce these costs.
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Project description:IntroductionGraph metrics have been proposed as potential biomarkers for diagnosis in clinical work. However, before it can be applied in a clinical setting, their reproducibility should be evaluated.MethodsThis study systematically investigated the effect of two denoising pipelines and different whole-brain network constructions on reproducibility of subject-specific graph measures. We used the multi-session fMRI dataset from the Brain Genomics Superstruct Project consisting of 69 healthy young adults.ResultsIn binary networks, the test-retest variability for global measures was large at low density irrespective of the denoising strategy or the type of correlation. Weighted networks showed very low test-retest values (and thus a good reproducibility) for global graph measures irrespective of the strategy used. Comparing the test-retest values for different strategies, there were significant main effects of the type of correlation (Pearson correlation vs. partial correlation), the (partial) correlation value (absolute vs. positive vs. negative), and weight calculation (based on the raw (partial) correlation values vs. based on transformed Z-values). There was also a significant interaction effect between type of correlation and weight calculation. Similarly as for the binary networks, there was no main effect of the denoising pipeline.ConclusionOur results demonstrated that normalized global graph measures based on a weighted network using the absolute (partial) correlation as weight were reproducible. The denoising pipeline and the granularity of the whole-brain parcellation used to define the nodes were not critical for the reproducibility of normalized graph measures.
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Project description:Fast signaling from vision and proprioception to muscle activation plays essential roles in quickly correcting movement. Though many studies have demonstrated modulation of the quick sensorimotor responses as depending on context in each modality, the contribution of multimodal information has not been established. Here, we examined whether state estimates contributing to stretch reflexes are represented solely by proprioceptive information or by multimodal information. Unlike previous studies, we newly found a significant stretch-reflex attenuation by the distortion and elimination of visual-feedback without any change in motor tasks. Furthermore, the stretch-reflex amplitude reduced with increasing elimination durations which would degrade state estimates. By contrast, even though a distortion was introduced in the target-motor-mapping, the stretch reflex was not simultaneously attenuated with visuomotor reflex. Our results therefore indicate that the observed stretch-reflex attenuation is specifically ascribed to uncertainty increase in estimating hand states, suggesting multimodal contributions to the generation of stretch reflexes.
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Project description:BackgroundNational estimates of influenza burden may not reflect state-level influenza activity, and local surveillance may not capture the full burden of influenza.MethodsTo provide state-level information about influenza burden, we estimated excess pneumonia and influenza (P&I) and respiratory and circulatory (R&C) hospitalizations and deaths in Colorado from local hospital discharge records, death certificates, and influenza virus surveillance using negative binomial models.ResultsFrom July 2007 to June 2016, influenza was associated with an excess of 17 911 P&I hospitalizations (95%CI: 15 227, 20 354), 30 811 R&C hospitalizations (95%CI: 24 344, 37 176), 1,064 P&I deaths (95%CI: 757, 1298), and 3828 R&C deaths (95%CI: 2060, 5433). There was a large burden of influenza A(H1N1) among persons aged 0-64 years, with high median seasonal rates of excess hospitalization among persons aged 0-4 years. Persons aged ≥65 years experienced the largest numbers and highest median seasonal rates of excess hospitalization and death associated with influenza A (H3N2). The burden of influenza B was generally lower, with elevated median seasonal rates of excess hospitalization among persons aged 0-4 years and ≥65 years.ConclusionsThese findings complement existing influenza surveillance. Periodic state-level estimates of influenza disease burden may be useful for setting state public health priorities and planning prevention and control initiatives.
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Project description:Spatial or temporal aspects of neural organization are known to be important indices of how cognition is organized. However, measurements and estimations are often noisy and many of the algorithms used are probabilistic, which in combination have been argued to limit studies exploring the neural basis of specific aspects of cognition. Focusing on static and dynamic functional connectivity estimations, we propose to leverage this variability to improve statistical efficiency in relating these estimations to behavior. To achieve this goal, we use a procedure based on permutation testing that provides a way of combining the results from many individual tests that refer to the same hypothesis. This is needed when testing a measure whose value is obtained from a noisy process, which can be repeated multiple times, referred to as replications. Focusing on functional connectivity, this noisy process can be: (a) computational, for example, when using an approximate inference algorithm for which different runs can produce different results or (b) observational, if we have the capacity to acquire data multiple times, and the different acquired data sets can be considered noisy examples of some underlying truth. In both cases, we are not interested in the individual replications but on the unobserved process generating each replication. In this note, we show how results can be combined instead of choosing just one of the estimated models. Using both simulations and real data, we show the benefits of this approach in practice.
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Project description:Choline is an essential nutrient for humans that is used to synthesize membrane phospholipids and the neurotransmitter acetylcholine. Betaine, a metabolite of choline, functions as a methyl-group donor in the conversion of homocysteine to methionine, and is important for renal function. Accurate analysis of choline intake was previously not possible because the choline content of most foods was not known. Using new and recently published data on the concentrations of choline in common foods, we measured the choline content of diets consumed ad libitum by healthy adult volunteers housed in a clinical research center and compared these with estimates of choline intake derived from 3-d food records kept by subjects immediately before study enrollment. Mean choline intake in this subject population met or slightly exceeded the current Adequate Intake (AI) of 7 mg/(kg . d) set by the Institute of Medicine. Men and women consumed similar amounts of choline per day (8.4 and. 6.7 mg/kg, respectively; P = 0.11). Choline intakes estimated from the 3-d food records were significantly lower than this (when expressed as mg/kg, or as total mg, but not when normalized to energy intake), suggesting underreporting of food intake. Intake of betaine, which may spare choline utilization as a methyl-group donor, was 5.3 mg/(kg . d) in men and 4.7 mg/(kg . d) in women. Intake of folate, vitamin B-12, and methionine + cysteine, were similar and sufficient in all subjects. The current recommended AI for choline seems to be a good approximation of the actual intake of this nutrient.
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