Employer-Based Insurance: Coverage and Cost

Explores the variation in cost by employers and enrollees, types of employers that offer coverage, access to coverage by workers, and how costs would change, especially for small businesses, if new policies required coverage for all full-time workers

Where Do the Sick Go? Health Insurance and Employment in Small and Large Firms

Small firms that offer health insurance to their employees may face variable premiums if the firm hires an employee with high-expected health costs. To avoid expensive premium variability, a small firm may attempt to maintain a workforce with low-expected health costs. In addition, workers with high-expected health costs may prefer employment in larger firms with health insurance rather than in smaller firms. This results in employment distortions. We examine the magnitude of these employment distortions in hiring, employment, and separations, using the Medical Expenditure Panel Survey from 1996 to 2001. Furthermore, we examine the effect of state small group health insurance reforms that restrict insurers’ ability to deny coverage and restrict premium variability on employment distortions in small firms relative to large firms. We find that workers with high-expected health cost are less likely to be new hires in small firms that offer health insurance, and are less likely to be employed in insured small firms. However, we find no evidence that state small group health insurance reforms have reduced the extent of these distortions. Estimating the magnitude of employment distortions in insured small firms is essential in refining reforms to the small group health insurance market. The difficulties that small firms face in obtaining and maintaining health insurance for their employees have been widely documented (Brown, Hamilton and Medoff, 1990; McLaughlin,1992; Fronstin and Helman, 2000). Only 45% of firms with fewer than 50 employees offer health insurance compared to 97% of firms with 50 or more employees (AHRQ, 2002). This low proportion has been attributed, in part, to the high administrative cost of health insurance for small firms, the low demand for insurance among workers in these firms, and the unwillingness of insurers to take on small firm risks (McLaughlin, 1992, Fronstin and Helman, 2000, Monheit and Vistnes, 1999). In recent decades, small firms that provide health insurance to their employees were in a precarious position. Their premiums were calculated yearly, based on the expected value of their health care utilization. Hence, a single high cost employee could lead to a substantial surcharge on the premiums for the firm (Zellers, McLaughlin, and Frick, 1992). In a survey of small employers that did not offer health insurance, 75 percent claimed that an important reason for not offering insurance was high premium variability (Morrisey, Jensen and Morlock, 1994). Concerns about these problems fueled the passage of numerous state small group health insurance reforms in the 1990s that implemented premium rating reforms and restrictions on pre-existing condition exclusions. While a few states have implemented premium rating reform that has severely restricted small group insurers’ ability to use health status to set premiums, in most states, these reforms have been moderate. Assuming that firms are unable to perfectly tailor individual wages to individual health insurance costs, unexpectedly high premiums may impose a large burden on small firms. Paying high premiums, possibly financed by borrowing at high interest rates, may increase the risk of bankruptcy. If small firms choose not to pay high premiums, and instead drop insurance coverage, they renege on the implicit compensation contract with workers. Employers may opt to raise employee contributions to cover higher costs but large increases may lead to healthier employees dropping coverage. Faced with this predicament, small firms may choose to prevent expensive premium variability by maintaining a work force that has a low-expected utilization of health care services. Thus, the link between employment and health insurance in small firms may result in a welfare loss if it prevents individuals with high-expected health costs from being employed in small firm jobs in which they may have high match specific productivity. Employers may obtain information about employees’ medical conditions in several ways. Before the passage of the 1990 Americans with Disabilities Act (ADA), half of all employers conducted pre-employment medical examinations (U.S. Congress, 1988). Most small group employers required the completion of a family health questionnaire for insurance coverage (Zellers et al., 1992, Cutler 1994). While ADA now restricts employer inquiries on employee health, it does not apply to firms with under 15 employees. In addition, employer compliance with the ADA may be hindered because its stipulations about pre-employment health inquiries are vague. Medical inquires are allowed if they pertain to the applicant’s ability to perform the job. In addition, medical information is explicitly allowed in the use of medical underwriting for insurance (Epstein, 1996). The media continues to report cases where employers easily obtain employee medical records (Rubin, 1998), or employees have been laid-off because of high health costs (O’Connor, 1996), or employee premiums have been adjusted to reflect the employee’s claims experience (Kolata, 1992). The Health Insurance Portability and Accountability Act of 1996 (HIPAA) includes a nondiscrimination provision that bars a group health plan or issuer from discriminating in eligibility or contributions on the basis of a health status-related factor. However, HIPAA allows medical underwriting and allows insurers to rate groups of employees based on health status as long as the premium rate for all employees is blended. This stipulation prevents employers from requiring higher cost employees to contribute a higher premium share, but does not shield employers from bearing the costs for a sick worker. Economists have typically believed that health insurance is an attribute of “good jobs” and workers do not choose jobs based on whether or not the job provides health insurance. In fact, this precept is behind the notion that employment is a mechanism for minimizing adverse selection in the market for health insurance (see, for example, Gruber and Levitt, 2000). However, a number of recent studies have suggested that worker demand for health insurance may play an important role in employment decisions. Workers with high-expected family costs may prefer jobs that offer health insurance, and conversely, workers with low preferences for health insurance may sort into jobs that lack health insurance. (Monheit and Vistnes, 1999, Monheit and Vistnes, 2006, Royalty and Abraham, 2005, Bundorf and Pauly, 2004). In this paper, we use the Medical Expenditure Panel Survey (MEPS) from 1996 to 2001 to examine the magnitude of employment distortions for workers with high-expected health costs. Since health insurance and employment are linked, health insurance may be an important determinant of employment outcomes. High-expected health costs may reduce the probability that workers are employed in firms where they have the highest match specific productivity. We estimate the magnitude of distortions in hiring, employment, and separations. Furthermore, we examine the effect of state small group health insurance reforms that restrict insurers’ ability to deny coverage and restrict premium variability on employment distortions in small firms relative to large firms. Estimating the magnitude of employment distortions in insured small firms and understanding the effect of small group regulation on these distortions is essential in deciding optimal public policy towards the small group health insurance market.

The factors contributing to teacher predictions of spelling ability, and the accuracy of their assessments

In this study, teachers of kindergarten and Grade 1 French-speaking students indicated the likelihood their students would develop later writing difficulties. Results showed that language measures, language background, the education levels of parents, and home literacy practices predicted whether children would be identified as at-risk. Moreover children’s oral language skills accounted for even more of the variance in teacher ratings than other variables. Spelling performance assessed 1-year later from a subset of children indicated that the teacher predictions were accurate. Thus, teachers appear to be an effective source for predicting children’s future literacy performance

Development of a tool to screen risk of literacy delays in French-speaking children: PHOPHLO

Literacy is crucial for success, both professionally and personally. Oral language skills are closely related to literacy development in children. When a child has weak oral language skills, they will have difficulty achieving reading and writing competencies within the expected time frame. In this paper, we present results from a longitudinal and cross-sectional study of the relationship between oral language skills in pre-literate children, and one aspect of their literacy skills in early elementary school—specifically, spelling. The study was conducted with French-speaking children and French-language learners from Quebec, a population that has been understudied in this area. We developed a predictive tool that will allow teachers and other professionals to assess oral language skills in young children and to predict those children at risk for literacy difficulties. Specifically, we screened children’s speech perception, speech production, phonological awareness, and morphology production abilities at entry to first grade and predicted spelling skills at the end of second grade. The screening tool that we developed proved to have a sensitivity of 71% and a specificity of 93% as a screen for poor spelling abilities.La littératie est un élément crucial du succès à la fois professionnel et personnel. Les habiletés de langage oral sont intimement liées au développement de la littératie chez les enfants. En effet, lorsqu’un enfant a de faibles habiletés de langage oral, il aura plus de difficulté à développer ses habiletés de lecture et d’écriture dans les délais prévus. Nous présentons les résultats d’une étude longitudinale et transversale qui explore les liens entre les habiletés de langage oral chez des enfants n’ayant pas appris à lire ou à écrire et leurs habiletés de littératie au premier cycle du primaire. Cette étude a été menée auprès d’enfants franco-québécois natifs et non natifs, une population peu étudiée dans ce domaine. Nous avons créé un outil prédictif qui permettra aux enseignants et autres professionnels d’évaluer les habiletés de langage oral des enfants et de prédire ceux qui sont à risque de présenter des difficultés de littératie. Plus spécifiquement, nous avons évalué les habiletés de perception et de production de la parole, de conscience phonologique et de production morphologique d’enfants débutant leur première année du primaire. Nous avons prédit leurs habiletés d’orthographe à la fin de leur deuxième année (fin du premier cycle du primaire). L’outil développé a démontré une sensibilité de 71% et une spécificité de 93% pour dépister les faibles habiletés d’orthographe

Crop Updates 2010 - Farming Systems

This session covers twenty papers from different authors: Pests and Disease 1. Preserving phosphine for use in Grain Storage Industry, Christopher R Newman, Department of Agriculture and Food Farming Systems Research 2. Demonstrating the benefits of grazing canola in Western Australia, Jonathan England, Stephen Gherardi and Mohammad Amjad, Department of Agriculture and Food 3. Buloke barley yield when pasture-cropped across subtropical perennial pastures, David Ferris, Department of Agriculture and Food, Phil Ward and Roger Lawes, CSIRO 4. Is pasture cropping viable in WA? Grower perceptions and EverCrop initiatives to evaluate, David Ferris, Tim Wiley, Perry Dolling, Department of Agriculture and Food, Philip Barrett-Lennard, Evergreen farming 5. Best-bet management for dual-purpose canola, John Kirkegaard, Susan Sprague, Hugh Dove and Walter Kelman, CSIRO, Canberra, Peter Hamblin, Agritech Research, Young, NSW 6. Pasture in cropping systems – with and without sheep, Brad Nutt and Angelo Loi, Department of Agriculture and Food 7. Can technology substitute for a lupin break? Wayne Parker, Department of Agriculture and Food 8. Canola row spacing with and without long term stubble retention on a sandy clay loam at Merredin, Glen Riethmuller, Department of Agriculture and Food 9. Impact of stubble retention on water balance and crop yield, Phil Ward1, Ken Flower2,3, Neil Cordingley2 and Shayne Micin1, 1CSIRO, Wembley, Western Australia, 2Western Australian No-Till Farmers Association, 3University of Western Australia Analysis and Modelling 10. Using POAMA rainfall forecasts for crop management in South-West WA, Senthold Asseng1, Peter McIntosh2,3, Mike Pook2,3, James Risbey2,3, Guomin Wang3, Oscar Alves3, Ian Foster4, Imma Farre4 and Nirav Khimashia1, 1CSIRO Plant Industry, Perth, 2CSIRO Marine and Atmospheric Research, Hobart, 3Centre for Australian Weather and Climate Research (CAWCR), A partnership between the Australian Bureau of Meteorology and CSIRO, Melbourne, 4Department of Agriculture and Food 11. Adaption to changing climates and variability – results of the Agribusiness Changing Climates regional workshop, Anderson W3, Beard D3, Blake J3, Grieve R1, Lang M3, Lemon J3, McTaggart R3, Gray D3, Price M2 and Stephens D3, 1Roderick Grieve Farm Management Consultants, 2Coffey International P/L, 3Department of Agriculture and Food 12. Farmers’ management of seasonal variability and climate change in WA, DA Beard, DM Gray, P Carmody, Department of Agriculture and Food 13. Is there a value in having a frost forecast for wheat in South-West WA? Imma Farre1, Senthold Asseng2, Ian Foster1 and Doug Abrecht3, 1Department of Agriculture and Food, CSIRO, Floreat, 2CSIRO Plant Industry, Perth 3Department of Agriculture and Food, Centre for Cropping Systems 14. Does buying rainfall pay? Greg Kirk, Planfarm Agricultural Consultants 15. Which region in the WA wheatbelt makes best use of rainfall? Peter Rowe, Bankwest Agribusiness 16. POAMA – the Predictive Ocean-Atmosphere Model for Australia, Guomin Wang and Oscar Alves, Centre for Australian Weather and Climate Research (CAWCR), A partnership between the Australian Bureau of Meteorology and CSIRO, Melbourne 17. Exploring the link between water use efficiency and farm profitability, Cameron Weeks, Planfarm and Peter Tozer, PRT Consulting Precision Agriculture 18. A plethora of paddock information is available – how does it stack up? Derk Bakker, Department of Agriculture and Food 18. Variable rate prescription mapping for lime inputs based on electromagnetic surveying and deep soil testing, Frank D’Emden, Quenten Knight and Luke Marquis, Precision Agronomics, Australia 19. Trial design and analysis using precision agriculture and farmer’s equipment, Roger Lawes, CSIRO Sustainable Ecosystems, Centre for Environment and Life Sciences, Floreat 20. Farmer perspectives of precision agriculture in Western Australia: Issues and the way forward, Dr Roger Mandel, Curtin Universit

Toward visualization of nanomachines in their native cellular environment

The cellular nanocosm is made up of numerous types of macromolecular complexes or biological nanomachines. These form functional modules that are organized into complex subcellular networks. Information on the ultra-structure of these nanomachines has mainly been obtained by analyzing isolated structures, using imaging techniques such as X-ray crystallography, NMR, or single particle electron microscopy (EM). Yet there is a strong need to image biological complexes in a native state and within a cellular environment, in order to gain a better understanding of their functions. Emerging methods in EM are now making this goal reachable. Cryo-electron tomography bypasses the need for conventional fixatives, dehydration and stains, so that a close-to-native environment is retained. As this technique is approaching macromolecular resolution, it is possible to create maps of individual macromolecular complexes. X-ray and NMR data can be ‘docked’ or fitted into the lower resolution particle density maps to create a macromolecular atlas of the cell under normal and pathological conditions. The majority of cells, however, are too thick to be imaged in an intact state and therefore methods such as ‘high pressure freezing’ with ‘freeze-substitution followed by room temperature plastic sectioning’ or ‘cryo-sectioning of unperturbed vitreous fully hydrated samples’ have been introduced for electron tomography. Here, we review methodological considerations for visualizing nanomachines in a close-to-physiological, cellular context. EM is in a renaissance, and further innovations and training in this field should be fully supported

Analysis of Using the Total White Blood Cell Count to Define Severe New-onset Ulcerative Colitis in Children

Objectives: The aim of this study was to assess common laboratory tests in identifying severe ulcerative colitis in children at diagnosis. Methods: A cohort of 427 children 4 to 17 years of age newly diagnosed with ulcerative colitis (UC) was prospectively enrolled. Boosted classification trees were used to characterize predictive ability of disease attributes based on clinical disease severity using Pediatric Ulcerative Colitis Activity Index (PUCAI), severe (65+) versus not severe (<65) and total Mayo score, severe (10-12) versus not severe (<10); mucosal disease by Mayo endoscopic subscore, severe (3) versus not severe (<3); and extensive disease versus not extensive (left-sided and proctosigmoiditis). Results: Mean age was 12.7 years; 49.6% (n = 212) were girls, and 83% (n = 351) were Caucasian. Severe total Mayo score was present in 28% (n = 120), mean PUCAI score was 49.8 ± 20.1, and 33% (n = 142) had severe mucosal disease with extensive involvement in 82% (n = 353). Classification and regression trees identified white blood cell count, erythrocyte sedimentation rate, and platelet count (PLT) as the set of 3 best blood laboratory tests to predict disease extent and severity. For mucosal severity, albumin (Alb) replaced PLT. Classification models for PUCAI and total Mayo provided sensitivity of at least 0.65 using standard clinical cut-points with misclassification rates of approximately 30%. Conclusions: A combination of the white blood cell count, erythrocyte sedimentation rate, and either PLT or albumin is the best predictive subset of standard laboratory tests to identify severe from nonsevere clinical or mucosal disease at diagnosis in relation to objective clinical scores

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe