Social Security Disability Insurance Enrollment and Health Care Employment.
Ontology highlight
ABSTRACT: Objective
To examine the relationship between Social Security Disability Insurance (SSDI) enrollment and health care employment.Data sources
State-year level data from government and other publicly available sources for all states (2000-2014).Study design
Population-weighted linear regression analyses model associations between each health care employment measure and each SSDI enrollment measure (i.e., SSDI overall, physical, or mental health enrollment rates), controlling for factors associated with health care employment, state fixed effects, and secular time trends.Data collection
Data are gathered from publicly available sources.Principal findings
A one standard deviation increase in SSDI enrollment per 100,000 population is associated with a statistically significant 2.6 and 4.5 percent increase in the mean employment rate per 100,000 population for health care practitioner and technical occupations and health care support occupations, respectively. The size of this relationship varies by the type of disabling condition for SSDI enrollment (physical versus mental health).Conclusions
Social Security Disability Insurance enrollment is significantly associated with health care employment at the state level. Quantifying the magnitude of this relationship is important given high SSDI enrollment rates as well as evolving policy and demographic shifts related to the SSDI program.
SUBMITTER: Pellegrini LC
PROVIDER: S-EPMC6051978 | biostudies-literature |
REPOSITORIES: biostudies-literature
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| S-EPMC5648004 | biostudies-literature
Project description:IntroductionThe cost of the Social Security Disability Insurance (DI) program has increased over time though recent reports showed that disability incidence and prevalence rates have started declining. We explored whether occupation was one of the risk factors for the rising number of disabled workers who received DI benefits during 1992-2016.MethodsWe used a cohort of 16 196 Health and Retirement Survey respondents between the age of 51 and 64 years who were followed from their date of entry until they received DI benefits, died, reached full retirement age, or reached the end of the follow-up period (2016). We used the extended stratified Cox proportional hazard model. Because one-third of the respondents in our cohort did not report their longest-held occupation, we used a multiple-imputation method.ResultsThe hazard of receiving DI benefits was 51%, 78%, 81%, and 85% higher among workers with longest-held occupations in sales, mechanics and repair, protective services, and personal services, respectively than among workers with longest-held occupations in the reference managerial occupation. The hazard of receiving DI benefits was more than double among workers with longest-held occupations in the construction trade and extractors, transportation operation, machine operators, handlers, and food preparation than among workers with the longest-held occupation in the reference managerial occupation.ConclusionImproving the overall working conditions in these occupations would help reduce worker suffering and the number of applicants for DI benefits, thereby reducing the burden of workplace injury and illness on the DI program.
| S-EPMC8016398 | biostudies-literature
Project description:This article examines the effects of UK welfare reform since 2008 on people with mental health conditions and disabilities. The results have been profound, particularly during a time of economic austerity, damaging the social safety net and pushing many vulnerable people into poverty and hardship. It has perpetuated inequalities and increased the social exclusion of disabled groups. The holes in the safety net require repair, alongside extensive social policy reform to both protect and empower people with disabilities and long-term conditions.
| S-EPMC7525580 | biostudies-literature
Project description:ObjectiveTo determine racial/ethnic differences in the use of conventional synthetic or biologic disease-modifying anti-rheumatic drugs (csDMARDs or bDMARDs, respectively) and long-term glucocorticoids (GC) or opioids among beneficiaries of the Social Security Disability Insurance (SSDI) with rheumatoid arthritis (RA) and <65 years old.MethodsSerial cross-sectional analyses of Centers for Medicare and Medicaid Services claims data (2007, 2011, and 2014) for individuals <65 years old with RA receiving SSDI Medicare and Medicaid, no longer working because they were considered disabled. Generalized estimating equation models were used to determine whether the proportion of patients who used csDMARD, bDMARD, long-term GC, and long-term opioids differed by race/ethnicity.ResultsThere were 12,931; 15,033; and 15,599 participants in 2007, 2011, and 2014, respectively. The overall use of csDMARD without bDMARD among beneficiaries of the SSDI were 31.1%, 30.3%, and 29.2%; 50.2%, 51.7%, and 53.8% used bDMARDs; 37.6%, 36.1%, and 34.4% used long-term GC; and 61.1%, 63.8%, and 63.7% used long-term opioids in years 2007, 2011, and 2014 respectively. The use of csDMARDs without bDMARDs was higher and the use of bDMARDs was lower among Blacks compared to Whites (adjusted absolute difference: +3.0%, +5.0%, and +3.3% for csDMARDs without bDMARDs and -4.6%, -5.7%, and -4.0% for bDMARDs in 2007, 2011, and 2014, respectively; all p<0.05). The use of bDMARDs was higher among Hispanics compared to Whites (adjusted absolute difference: +7.1%, +7.3%, and +7.5% in 2007, 2011, and 2014, respectively; all p<0.05). Long-term GC use was lower among Hispanics than among Whites only in year 2014 (absolute percentage point difference of -4.2%); no other difference in long-term GC use was identified. Whites were the patients with the highest use of long-term opioids (more than two third in each calendar year).ConclusionRacial and ethnic differences exists in regards to the treatment of RA among beneficiaries of the SSDI. These findings suggest that this already vulnerable population of patients with RA can also have a racial and ethnic disparity that can contribute to additional disease burden and that should be examined in order to inform future interventions or even inform future policy changes to the SSDI.
| S-EPMC8018290 | biostudies-literature
Project description:ObjectiveTo compare cardiovascular disease (CVD) rates in rheumatoid arthritis (RA) beneficiaries of the Social Security Disability Insurance (SSDI) with commercially insured RA patients.MethodWe created three cohorts of RA patients aged < 65 years for SSDI and three for Marketscan using claims data from 2006 to 2016. The cohort definitions were as follows: (1) cohort 1: ≥ 2 diagnosis codes for RA occurring 7-365 days apart with ≥ 1 diagnosis code from a rheumatologist; (2) cohort 2: ≥ 1 diagnosis code for RA from a rheumatologist and a disease-modifying antirheumatic drugs (DMARDS); and (3) cohort 3: cohort 2, plus initiation of a new biologic/tofacitinib. We used Cox regression to determine the CVD risk comparing SSDI vs. Marketscan. Models were sequentially adjusted for age and sex (model 1); model 1 + diabetes, smoking, and high CVD risk (model 2); and model 2 + dual eligible (Medicare and Medicaid), subsidy, and state buy in (model 3).ResultsThere were 380,336 RA patients, mean age 53.3 (SD 8.1) years, 21-24% male. Prevalence of comorbidities was higher in SSDI vs. Marketscan. SSDI RA patients in cohort 2 (model 3) had higher CVD risk (HR 1.23 (1.14-1.33). In cohort 3 (model 3), CVD risk was not statistically significantly different between SSDI and Marketscan (HR 0.89 (0.69-1.15).ConclusionRA patient beneficiaries of the SSDI had higher risk for CVD events than those employed. The differences in CVD events between SSDI and Marketscan were partially attributable to differences in CVD risk factors.
| S-EPMC9396772 | biostudies-literature
Project description:ObjectiveEvery year, thousands of patients die waiting for disability benefits from the Social Security Administration. Some qualify for expedited service under the Compassionate Allowance (CAL) initiative, but CAL software focuses exclusively on information from a single form field. This paper describes the development of a supplemental process for identifying some overlooked but gravely ill applicants, through automatic annotation of health records accompanying new claims. We explore improved prioritization instead of fully autonomous claims approval.Materials and methodsWe developed a sample of claims containing medical records at the moment of arrival in a single office. A series of tools annotated both patient records and public Web page descriptions of CAL medical conditions. We trained random forests to identify CAL patients and validated each model with 10-fold cross validation.ResultsOur main model, a general CAL classifier, had an area under the receiver operating characteristic curve of 0.915. Combining this classifier with existing software improved sensitivity from 0.960 to 0.994, detecting every deceased patient, but reducing positive predictive value to 0.216.DiscussionTrue positive CAL identification is a priority, given CAL patient mortality. Mere prioritization of the false positives would not create a meaningful burden in terms of manual review. Death certificate data suggest the presence of truly ill patients among putative false positives.ConclusionTo a limited extent, it is possible to identify gravely ill Social Security disability applicants by analyzing annotations of unstructured electronic health records, and the level of identification is sufficient to be useful in prioritizing case reviews.
| S-EPMC7651957 | biostudies-literature
Project description:BackgroundHealth insurance enrollment is a difficult financial decision with large health impacts. Challenges such as low health insurance literacy and lack of knowledge about choosing a plan further complicate this decision-making process. Therefore, to support consumers in their choice of a health insurance plan, it is essential to understand how individuals go about making this decision.ObjectiveThis study aims to understand the sources of information used by individuals to support their employer-provided health insurance enrollment decisions. It seeks to describe how individual descriptive factors lead to choosing a particular type of information source.MethodsAn introduction was presented on health insurance plan selection and the sources of information used to support these decisions from the 1980s to the present. Subsequently, an electronic survey of 151 full-time faculty and staff members was conducted. The survey consisted of four sections: demographics, sources of information, health insurance literacy, and technology acceptance. Descriptive statistics were used to show the demographic characteristics of the 126 eligible respondents and to study the response behaviors in the remaining survey sections. Proportion data analysis was performed using the Cochran-Armitage trend test to understand the strength of the association between our variables and the types of sources used by the respondents.ResultsIn terms of demographics, most of the respondents were women (103/126, 81.7%), represented a small household (1-2 persons; 87/126, 69%), and used their insurance 3-12 times a year (52/126, 41.3%). They assessed themselves as having moderate to high health insurance literacy and high acceptance of technology. The most selected and top-ranked sources were Official employer or state websites and Official Human Resources Virtual Benefits Counselor Alex. From our data analysis, we found that the use of official primary sources was constant across age groups and health insurance use groups. Meanwhile, the use of friends or family as a primary source slightly decreased as age and use increased.ConclusionsIn this exploratory study, we identified the main sources of health insurance information among full-time employees from a large state university and found that most of the respondents needed 2-3 sources to gather all the information that they desired. We also studied and identified the relationships between individual factors (such as age, gender, and literacy) and 2 dependent variables on the types of primary sources of information. We encountered several limitations, which will be addressed in future studies.
| S-EPMC8391737 | biostudies-literature
Project description:BackgroundVision health is an important aspect of health worldwide. Visual impairment (VI) is associated with poor quality of life and is usually more prevalent in rural areas. To help rural populations obtain vision care, health insurance policies have emerged throughout the world. However, some existing literatures show that health insurance enrollment's impact on the overall physical health of rural population has been minimal. Focusing on vision health among adults in rural China, our study aims to investigates the impact of health insurance on vision health, heterogeneity of the effect, and the moderating effect of health insurance enrollment on the impact of chronic physical diseases and basic eye diseases on vision health.MethodsPrimary data were collected through a nation-wide epidemiological survey of vision health conducted in rural China in 2018, with a sample size of 28,787 used in our statistical analysis. Instrumental variables regression and Heckman selection models were conducted to examine the impact of health insurance enrollment and reimbursement ratio adults' vision health outcomes. Subsample regressions by sex, age, education level, and whether with eye diseases were further conducted to explore the heterogeneity in our results. We then examined whether health insurance enrollment moderates the impact of chronic physical diseases and basic eye diseases on vision health through the method of introducing interaction terms.ResultsParticipating in health insurance reduced the probability of VI by 2.15 %. The reimbursement rate increasing by 1 % point may reduce the probability of worsening VI by 6.12 %. Men (-0.0235, P = 0.0002) benefit more from insurance enrollment than women (-0.0201, P = 0.0082) with respect to vision health. From the young adult group to the oldest group, the marginal effect of health insurance increased from - 0.0068 (P = 0.0394) to -0.0753 (P < 0.0001). The marginal effect on VI was most significant in people with lower education levels and weakened with increased education levels. People with basic eye diseases (-0.0496, P = 0.0033) benefit more from participating insurance than the people without basic eye diseases (-0.0196, P = 0.0001) with respect to vision health. The moderating effects of health insurance enrollment on the impacts of cerebral infarction (-0.1225, P < 0.0001), diabetes (-0.0398, P = 0.0245), hyperlipidemia (-0.1364, P = 0.0271), mental illness (-0.1873, P = 0.0010), glaucoma (-0.1369, P = 0.0073), diabetic retinopathy (-0.1560, P = 0.0043), and retinal vein obstruction (-0.2018, P = 0.0155) on vision health were significantly negative.ConclusionsThe results suggest that participation in health insurance and higher health insurance reimbursement ratios reduced the risk of VI in the sampled adults. Health insurance has the most significant effect in in vulnerable groups. Heath insurance enrollment moderates the impacts of several chronic physical and basic eye conditions on vision health. Our findings have potential implications for reforming health insurance policies to improve vision health conditions in rural areas of developing countries.
| S-EPMC8325859 | biostudies-literature
Project description:The COVID-19 pandemic represents a major threat to health and economic well-being in the USA, especially for older and disabled workers, and may spill over onto Social Security. We use individual-level from the Current Population Survey, state-level monthly Social Security administrative data on disability benefit applications, and national-level monthly data on Social Security retirement benefit applications to assess the impact of the pandemic on older adults' employment and benefit claiming. State-level monthly Google Trends data are used as a leading indicator of future claiming in the population. We find that employment for older workers dropped substantially more than would have been predicted prior to the pandemic: employment for 50-61-year-olds was 5.7 pp (8.3 percent) lower, while employment for 62-70-year-olds was 3.9 pp (10.7 percent) lower. We find declines in labor force exit due to disability (4-5 percent), applications for disability insurance (15 percent), the average age of disability program applicants, and Google searches for disability (7 percent). We contrast with prior periods of economic downturn and explore potential mechanisms, finding evidence for both supply- and demand-side explanations.Supplementary informationThe online version contains supplementary material available at 10.1007/s00148-022-00915-z.
| S-EPMC9251032 | biostudies-literature
Project description:Physical and mental impairments represent the 2 largest health condition categories for which workers receive Social Security disability benefits. Comprehensive assessment of physical and mental impairments should include aspects beyond medical conditions such as a person's underlying capabilities as well as activity demands relevant to the context of work. The objective of this article is to describe the initial conceptual stages of developing new measurement instruments of behavioral health and physical functioning relevant for Social Security work disability evaluation purposes. To outline a clear conceptualization of the constructs to be measured, 2 content models were developed using structured and informal qualitative approaches. We performed a structured literature review focusing on work disability and incorporating aspects of the International Classification of Functioning, Disability and Health as a unifying taxonomy for framework development. Expert interviews provided advice and consultation to enhance face validity of the resulting content models. The content model for work-related behavioral health function identifies 5 major domains: (1) behavior control, (2) basic interactions, (3) temperament and personality, (4) adaptability, and (5) workplace behaviors. The content model describing physical functioning includes 3 domains: (1) changing and maintaining body position, (2) whole-body mobility, and (3) carrying, moving, and handling objects. These content models informed subsequent measurement properties including item development and measurement scale construction, and provided conceptual coherence guiding future empirical inquiry. The proposed measurement approaches show promise to comprehensively and systematically assess physical and behavioral health functioning relevant to work.
| S-EPMC4010070 | biostudies-literature