Publication Type: Conference Paper/Unpublished Manuscript
Abstract: The paper examines path dependence analysis of the development of public health insurance in the United States and argues that a number of key interpretations are challenged by a comparative perspective examining the historical development of public healht insurance in Canada.

Publication Type: Poster
Abstract: In pre-war Europe, insurance policies were a popular means of saving and investing, and an insurance policy became known as the “poor man’s Swiss bank account.” European citizens purchased policies to insure against injury, loss of life, or destruction of property, among other things. Jewish citizens, a particularly vulnerable ethnic group, perceived insurance policies as a sound and secure means of investing, and Jewish families bought approximately 2.5 billion dollars worth of insurance policies before World War II.
The fate of many Jewish pre-World War II insurance policies is unknown. Countless policies were confiscated by the Nazi regime during the war. After the war, policies were canceled and the money pocketed by the companies because the policyholder or their heirs had fallen victim to the Nazi program of annihilation and did not come forth to claim payment.
In the eyes of European insurers, Nazi racial policy initially had a positive effect on the industry. After Kristallnacht, German insurance companies were saddled with thousands of property damage claims. Through “creative” interpretations of the insurance terms and conditions and through the implementation of anti-Jewish legislation by the Nazi state, the insurance companies were saved from the damaging effects of Kristallnacht.
While collusion with the Axis regimes was, initially, financially beneficial, Nazi anti-Jewish policy became increasingly burdensome. By the early 1940s, confiscation of Jewish assets, including insurance policies, was legalized by decree throughout all of Axis-occupied Europe. Using asset registries that Jews were forced to fill out in all areas under Axis rule, the fascist authorities demanded that insurance companies locate and surrender all Jewish insurance policies. Companies failing to cooperate with the proper governmental authorities were penalized.
However, many companies lessened the effect of the anti-Jewish laws on their operations by using political connections. For example, the general director of Germany’s most powerful re-insurance company was Minister of Finance in Hitler’s cabinet from 1933-1934. In Italy, many Jewish insurance leaders were replaced with loyal Fascists after 1938.
This poster will illustrate the effects of Nazi and Fascist economic and social policies on insurance companies and policyholders. In the first section, entitled “Corporate Complicity and Resistance,” I will feature pictures of European insurance leaders, many of whom appeared publicly in Nazi and Fascist regalia, and will describe their connections to these regimes. In the second section, entitled “The Effect of Racial Policy on Insurance,” I will feature a copy of the property registration form used in Austria and a timeline of confiscation laws implemented in Axis-occupied Europe. In the final section, entitled “The Fate of Holocaust Era Insurance Policies,” I will tell the story of two individuals, Adolf Stern and Jack Weiss, who filed lawsuits in U.S. courts in the last decade regarding unpaid insurance policies. By including images of their pre-World War II insurance contracts and letters they received from the insurers regarding their claims, I will illustrate the fate of many pre-World War II insurance policies held by Jewish individuals.

Publication Type: Abstract
Abstract: Understanding the affordability of coverage is important for evaluating the role of policy in reducing the number of uninsured workers. We study worker health insurance take-up and coverage decisions using data from the Medical Expenditure Panel Survey (MEPS) from 1997 to 2003. Unlike previous studies which control only for current income, we include information on the presence and value of family-level assets such as home ownership, vehicles, savings accounts, stocks, bonds, retirement accounts, as well as liabilities, to estimate the effect of net wealth on insurance purchase decisions. Unlike most studies which focus on “worker” take-up, we also take into account the availability of insurance offers through the spouse’s employer in estimating enrollment decisions of workers and their families.

We estimate worker demand for employer sponsored health insurance as a function of the premium as well as worker, family, employer and plan characteristics. We use two approaches to deal with the lack of premium data for workers who decline coverage. The first approach uses a sub sample in MEPS from 1997-1999 with linked data from the Household Component (HC) and the Insurance Component (IC) which is a survey of employers. Although the HC-IC link sample is not nationally representative, it contains data on the premiums for takers and decliners as well as the availability of choice of health plans, and types of plans offered. The second approach uses simulated premiums from the Insurance Component List Sample. Using the nationally representative sample of employers in the MEPS-IC, we estimate average plan premiums as a function of predictor variables available on both the employer and household surveys, including location (state, MSA), firm size, industry, and plan types offered. We then use this model to predict premiums for workers in the household survey.

Among adults living in families with health insurance offers in 2001 and 2002, 7.6 percent did not take up private insurance. As expected, probability of take up declined with income: 8.6 percent of adults with middle income, 19.9 percent of adults with low income, and 32.4 percent of poor and near poor adults did not take up private insurance. (Bernard and Selden, 2005) Preliminary work based on this sample, suggests that assets and net wealth play a significant role in insurance coverage decisions. Controlling for income, adults who did not take up health insurance were significantly less likely to have assets. For example, among poor and low income adults, the decliners were less likely to own homes (46% vs. 54%), less likely to have cars (78% vs. 86%), less likely to have checking accounts (37% vs. 51%), less likely to have stocks (1% vs. 5%), and less likely to have individual retirement accounts (13% vs. 22%). Research using affordability thresholds based on income has shown that health insurance was affordable to between 25% to 75% of the uninsured in 2000. (Bundorf and Pauly, 2002) Our preliminary results suggest that in explaining health insurance purchase decisions, affordability thresholds based solely on income may be inadequate.

Publication Type: Conference Paper/Unpublished Manuscript
Review Method: Peer Reviewed
Abstract: Why is the insurance industry willing to insure some risks and unwilling to insure others? Behind the insuring of hazards there is a complex and sometimes unpredictable process of identifying those events the industry can deal with and those where an insurance approach is bound to fail. Insurance of risks associated with climatic change is a good example of the vulnerabilities of the state and the insurance industry. The high price of intervention impedes any immediate action, yet the hazards will not just go away. The pressures of dramatically increasing costs and uncertainties about new forms of risk have had a decisive impact on current insurance activities. Ulrich Beck claims in his World Risk Society that these new forms are increasingly difficult to predict and to control; we thus live in a world of more and more dangers, and fewer and fewer insurable risks. This observation assumes, however, no change in the norms and institutional arrangements of risk-assessment in the insurance industry. An alternative claim is equally plausible, that insurance adapts to the new situation, modifying the conditions of insurability and ensuring continuity.
While some may be happy with the state’s shifting of responsibility to the insurance industry, others would argue that the state should take a more active role in the coverage against hazards. This role would involve not only shared financial responsibility, but also negotiations about the fundamental conditions of insurability. In Germany and Austria, for example, the state-run flood management is currently being transformed into a public-private partnership. But even if such partnerships are a promising solution to insurability constraints, they are not without problems. In this paper the institutional conditions of such regimes in five different countries (USA, Netherlands, UK, Germany and France) are compared and evaluated.

Publication Type: Abstract
Abstract: Purpose: This paper analyzes Tennessee hospital discharge records and uses insurance type as a factor to predict the likelihood of hospitalization for an ambulatory care-sensitive (ACS) condition.

Background: ACS conditions are those for which timely and effective outpatient care can potentially prevent the need for hospitalization. High incidence of preventable hospitalizations such as asthma, diabetes, hypertension and congestive heart failure may be indicative of underlying problems with access to primary care or deficiencies in outpatient care management. Analysis of preventable hospitalizations can thus provide information for health system evaluation. TennCare is Tennessee’s experimental Medicaid managed care program that began in 1994. An overarching goal of this reform model was to deliver prevention-centered longitudinal care to reduce inappropriate use of inpatient care. The resulting savings, it was theorized, could then be used to expand insurance coverage. However, the expected outcome of better use of primary care of this $8.4 billion program that covers 1 in every 4 Tennesseans has never been investigated.

Hypotheses: We will test two hypotheses. The first is that patients insured by TennCare are more likely to be admitted for ACS conditions than patients insured by other insurance types after controlling for race, age, gender, and co-morbidities. The second hypothesis is that the likelihood of ACS hospitalization varies among the different TennCare Managed Care Organizations (MCOs), with patients insured by nonprofit, academic-medical-center-affiliated MCOs having a lower likelihood of ACS hospitalization than those insured by other MCOs.

Data Sources: The primary source is the Hospital Inpatient Discharge Data System (HDDS) maintained by the Tennessee Department of Health for 1997-2002. HDDS receives information from UB-92 forms on all inpatient discharges in Tennessee. Each form contains information on patient diagnoses, procedures performed, charges, and selected patient demographics. We will also use county-level Area Resource File data to describe the environments in which patients live.
Methodology: We will use the AHRQ definition of Potentially Avoidable Hospitalizations which include those for 16 specific ACS conditions. There will be two dependent variables for each of the two hypotheses: a dummy variable with 1 signifying an ACS admission and 0 otherwise; the total charges of the admission. The key independent variable for the logistic regressions is a categorical variable representing insurance type (TennCare, Medicare, Private insurance, Self Pay, etc.). Control variables include patient demographics such as age, gender, race, patient risk strata that consist of principal and co-morbidity diagnoses, and county characteristics such as population density, percent poverty, supply of primary care physicians per 100,000 population. In the second regression analysis with the hospital charges as the dependent variable, a dummy variable representing whether the admission is for an ACS condition or not will be added.

Potential Contribution: Little is known about TennCare’s effectiveness in the provision and deployment of primary care. If significance differences in the prevalence and expenditures of primary care-sensitive hospitalizations are found between TennCare and other insurance types after controlling for confounding factors, the results will shed new light on the performance of TennCare as a model of public-sector Medicaid reform.