COBRA: Continuation of Employer Group Health Insurance, March 2007

COBRA stands for Consolidated Omnibus Budget Reconciliation Act *COBRA is not insurance; it is the law, since 1985. COBRA allows employees and their dependents to continue employer group health insurance for several months when that insurance would usually end. *Insurance plans under COBRA are private health plans, not plans sold by the government. *The U.S. Departments of Labor and Treasury enforce COBRA.

COBRA: Continuation of Employer Group Health Insurance, 2007

Medicare Deductible, co-insurance and premiuns form, and rescription drugs plans.

Self-selection and risk selection on the Swiss health insurance market

Abstract This thesis presents three empirical studies in the field of health insurance in Switzerland. First we investigate the link between health insurance coverage and health care expenditures. We use claims data for over 60 000 adult individuals covered by a major Swiss Health Insurance Fund, followed for four years; the data show a strong positive correlation between coverage and expenditures. Two methods are developed and estimated in order to separate selection effects (due to individual choice of coverage) and incentive effects ("ex post moral hazard"). The first method uses the comparison between inpatient and outpatient expenditures to identify both effects and we conclude that both selection and incentive effects are significantly present in our data. The second method is based on a structural model of joint demand of health care and health insurance and makes the most of the change in the marginal cost of health care to identify selection and incentive effects. We conclude that the correlation between insurance coverage and health care expenditures may be decomposed into the two effects: 75% may be attributed to selection, and 25 % to incentive effects. Moreover, we estimate that a decrease in the coinsurance rate from 100% to 10% increases the marginal demand for health care by about 90% and from 100% to 0% by about 150%. Secondly, having shown that selection and incentive effects exist in the Swiss health insurance market, we present the consequence of this result in the context of risk adjustment. We show that if individuals choose their insurance coverage in function of their health status (selection effect), the optimal compensations should be function of the se- lection and incentive effects. Therefore, a risk adjustment mechanism which ignores these effects, as it is the case presently in Switzerland, will miss his main goal to eliminate incentives for sickness funds to select risks. Using a simplified model, we show that the optimal compensations have to take into account the distribution of risks through the insurance plans in case of self-selection in order to avoid incentives to select risks.Then, we apply our propositions to Swiss data and propose a simple econometric procedure to control for self-selection in the estimation of the risk adjustment formula in order to compute the optimal compensations.

Traumatic Brain Injury in Iowa: An Analysis of Core Surveillance Data 2006-2008, July 15, 2011

Termed the “silent epidemic”, traumatic brain injury is the most debilitating outcome of injury characterized by the irreversibility of its damages, long-term effects on quality of life, and healthcare costs. The latest data available from the Centers for Disease Control and Prevention (CDC) estimate that nationally 50,000 people with traumatic brain injury (TBI) die each year; three times as many are hospitalized and more than twenty times as many are released from emergency room departments (ED) (CDC, 2008)1. The purpose of this report is to describe the epidemiology of TBI in Iowa to help guide policy and programming. TBI is a result of an external force which transfers energy to the brain. Stroke is caused by a disruption of blood flow in the brain that leads to brain injury. Though stroke is recognized as the 3rd leading cause of death nationally2, and is an injury that affects the brain it does not meet the definition a traumatic brain injury and is not included in this report.

Traumatic Brain Injury in Iowa Inpatient Hospital Data, 2003-2005

According to the Centers for Disease Control and Prevention, unintentional injury is the fifth leading cause of death for all age groups and the first leading cause of death for people from 1 to 44 years of age in the United States, while homicide remains the 2nd leading cause of death for 15 to 24 years old (CDC, 2006). In 2004, there were approximately 144,000 deaths due to unintentional injuries in the US; 53% of which represent people over 45 years of age (CDC, 2004). With 20,322 suicidal deaths and 13,170 homicidal deaths, intentional injury deaths affect mostly people under 45 years old. On average, there are 1,150 unintentional deaths per year in Iowa. In 2004, 37% of unintentional deaths were due to motor vehicle accidents (MTVCC) occurring across all age ranges and 30% were due to falls involving persons over 65 years of age 82% of the time (IDPH Health Stat Div., 2004). The most debilitating outcome of injury is traumatic brain injury, which is characterized by the irreversibility of its damages, long-term effects on quality of life, and healthcare costs. The latest data available from the CDC estimated that, nationally, 50,000 traumatic brain injured (TBI) people die each year; three times as many are hospitalized and more than twenty times as many are released from emergency room (ER) departments (CDC, 2006). Besides the TBI registry, brain injury data is also captured through three other data sources: 1) death certificates; 2) hospital inpatient data; and, 3) hospital outpatient data. The inpatient and outpatient hospital data are managed by the Iowa Hospital Association, which provides to Iowa Department of Public Health the hospital data without personal identifiers. (The hospitals send reports to the Agency of Health Care Research and Quality, which developed the Health Care Utilization Project and its product, the National Inpatient Sample).

Rethinking Health Insurance, Iowa State Planning Guide, September 30, 2005

Iowa has been a HRSA State Planning Grant participant since October 2000. Iowa’s purpose in participating in the program has remained constant: to identify, through research, policies that will help expand access to affordable health insurance coverage for all Iowans. The Iowa State Planning Grant project (Iowa-SPG) has been able to serve as a significant state data resource on the uninsured in Iowa throughout its tenure. Through the use of State Planning Grant resources, policymakers, the media, and interested citizens have been able to access, from one convenient and trusted source, a variety of information on Iowa’s uninsured population. Section 1 of this report presents an update of state-level data on the uninsured with a focus on the data that has been of greatest interest to various Iowa constituencies during the State Planning Grant years, 2001-2005.

A Data Mining Approach for the Identification of Adverse Drug Events (ADE) resulting from Drug-Drug Interactions (DDI) to improve pharmacovigilance

In the current study, epidemiology study is done by means of literature survey in groups identified to be at higher potential for DDIs as well as in other cases to explore patterns of DDIs and the factors affecting them. The structure of the FDA Adverse Event Reporting System (FAERS) database is studied and analyzed in detail to identify issues and challenges in data mining the drug-drug interactions. The necessary pre-processing algorithms are developed based on the analysis and the Apriori algorithm is modified to suit the process. Finally, the modules are integrated into a tool to identify DDIs. The results are compared using standard drug interaction database for validation. 31% of the associations obtained were identified to be new and the match with existing interactions was 69%. This match clearly indicates the validity of the methodology and its applicability to similar databases. Formulation of the results using the generic names expanded the relevance of the results to a global scale. The global applicability helps the health care professionals worldwide to observe caution during various stages of drug administration thus considerably enhancing pharmacovigilance

Health insurance as a strategy for access : Streamlined facts of the Colombian Health Care Reform

La reforma colombiana al sistema de salud (Ley 100 de 1993) estableció, como estrategia para facilitar el acceso, la universalidad de un seguro de salud que se adquiere mediante la cotización en el régimen contributivo o mediante la afiliación gratuita al régimen subsidiado, con la meta de cubrir a toda la población con un plan de beneficios único que comprende servicios de todos los niveles de atención. En el documento se analizan los principales hechos estilizados de la reforma en cuanto a cobertura del seguro y acceso y, mediante modelos logit, se estiman los determinantes de la afiliación y del acceso, con datos de las encuestas de calidad de vida de 1997 y 2003. Se destaca que la cobertura pasó del 20% de la población en 1993 al 60% en 2004, aunque parece imposible alcanzar la universalidad; la estructura y evolución de la cobertura muestran que los dos regímenes son complementarios, de modo que mientras el contributivo tiene mayor presencia en las ciudades y entre la población con empleo formal, el subsidiado tiene mayor peso entre la población rural y con bajos niveles de ingresos; por otra parte, el seguro tiene ventajas para la población subsidiada, con una mayor probabilidad de utilización de servicios, aunque el plan es inferior al del contributivo y existen barreras para el acceso.

Aplicação de Data Mining à Segurança do Trabalho Ferroviário

Embora o objectivo de redução de acidentes laborais seja frequentemente invocado para justificar uma aplicação preventiva de testes de álcool e drogas no trabalho, há poucas evidências estatisticamente relevantes das pressupostas causalidade e correlação negativa entre a sujeição aos testes e os posteriores acidentes. Os dados de testes e dos acidentes ocorridos com os colaboradores de uma transportadora ferroviária portuguesa de âmbito nacional, durante anos recentes, começam agora a ser explorados, em busca de relações entre estas e outras variáveis biográficas. - Although the aim of reducing occupational accidents is frequently cited to justify preventive drug and alcohol testing at work, there is little statistically significant evidence of the assumed causality and negative correlation between exposure to testing and subsequent accidents. Data mining of tests and accidents involving employees of a Portuguese national wide railway transportation company, during recent years, is now beginning in search of relations between these and other biographical variables.

Distributed classification for pocket data mining

Distributed and collaborative data stream mining in a mobile computing environment is referred to as Pocket Data Mining PDM. Large amounts of available data streams to which smart phones can subscribe to or sense, coupled with the increasing computational power of handheld devices motivates the development of PDM as a decision making system. This emerging area of study has shown to be feasible in an earlier study using technological enablers of mobile software agents and stream mining techniques [1]. A typical PDM process would start by having mobile agents roam the network to discover relevant data streams and resources. Then other (mobile) agents encapsulating stream mining techniques visit the relevant nodes in the network in order to build evolving data mining models. Finally, a third type of mobile agents roam the network consulting the mining agents for a final collaborative decision, when required by one or more users. In this paper, we propose the use of distributed Hoeffding trees and Naive Bayes classifers in the PDM framework over vertically partitioned data streams. Mobile policing, health monitoring and stock market analysis are among the possible applications of PDM. An extensive experimental study is reported showing the effectiveness of the collaborative data mining with the two classifers.

Dynamic group communication for large-scale parallel data mining

Exascale systems are the next frontier in high-performance computing and are expected to deliver a performance of the order of 10^18 operations per second using massive multicore processors. Very large- and extreme-scale parallel systems pose critical algorithmic challenges, especially related to concurrency, locality and the need to avoid global communication patterns. This work investigates a novel protocol for dynamic group communication that can be used to remove the global communication requirement and to reduce the communication cost in parallel formulations of iterative data mining algorithms. The protocol is used to provide a communication-efficient parallel formulation of the k-means algorithm for cluster analysis. The approach is based on a collective communication operation for dynamic groups of processes and exploits non-uniform data distributions. Non-uniform data distributions can be either found in real-world distributed applications or induced by means of multidimensional binary search trees. The analysis of the proposed dynamic group communication protocol has shown that it does not introduce significant communication overhead. The parallel clustering algorithm has also been extended to accommodate an approximation error, which allows a further reduction of the communication costs. The effectiveness of the exact and approximate methods has been tested in a parallel computing system with 64 processors and in simulations with 1024 processing elements.

The determinants of physician and pharmacist utilization and equity of access under Korean universal health insurance

This study examines the social and behavioral determinants of two types of primary care, seeing a physician or a pharmacist, for Koreans and evaluates the equity of the Korean national health insurance system. The study applies the Aday and Andersen access framework to cross-sectional data from the 1992 Korean National Health Interview Survey (N = 21,841).^ The study found that in Korea, the elderly were most likely, and children least likely, to have used physician services. Women, household heads, those in small families, and the less educated were more likely than their counterparts to use physician and pharmacist services. Health status and need were important determinants of Koreans seeing a doctor or a pharmacist. Differences in need substantially accounted for the original differences observed between subgroups. Resources associated with having insurance coverage, a regular source of care, and place of residence (rural/urban) ameliorated to some extent the subgroup differences in the use of physicians' and pharmacists' services among Koreans. They were also major independent predictors of access. Having insurance remains a particularly important predictor of who uses physician services. Among the insured, trade-offs in the use of physician and pharmacist services were found in the current system, i.e., uninsured and poor Koreans were more likely to use pharmacist services, while insured and rural Koreans were more likely to use doctor services. Among the insured, cost sharing rates are lower for physician than for pharmacist services. Self-employed persons were less likely than government and industrial workers to use physician services. An underlying expectation under universal health insurance was that the Korean health care system would be equitable. The research results, however, did not fully support this expectation.^ The policy implications of these findings are that measures are required to extend insurance coverage to the uninsured, to equalize differences in benefit packages between health plans, and to expand the availability of physicians in rural areas. Further research is also needed to understand those who do not currently have a regular source of care and why and the access barriers that may exist for selected demographic subgroups (those in large families and unmarried or divorced/widowed persons). ^

The Aggregate Demand for Private Health Insurance Coverage in the U.S.

This paper estimates the aggregate demand for private health insurance coverage in the U.S. using an error-correction model and by recognizing that people are without private health insurance for voluntary, structural, frictional, and cyclical reasons and because of public alternatives. Insurance coverage is measured both by the percentage of the population enrolled in private health insurance plans and the completeness of the insurance coverage. Annual data for the period 1966-1999 are used and both short and long run price and income elasticities of demand are estimated. The empirical findings indicate that both private insurance enrollment and completeness are relatively inelastic with respect to changes in price and income in the short and long run. Moreover, private health insurance enrollment is found to be inversely related to the poverty rate, particularly in the short-run. Finally, our results suggest that an increase in the number cyclically uninsured generates less of a welfare loss than an increase in the structurally uninsured.