See, for example, Weissman, J. and Epstein, A., Falling Through the Safety Net: Insurance and Status and Access to Care (Baltimore: Johns Hopkins University Press, 1994); Kinney, E. Steinmetz, S., “Notes from the Insurance Underground: How the Chronically Ill Cope,” Journal of Health Politics, Policy and Law, 19 (1994): 633–42; Beauregard, K., Agency for Health Care Policy and Research, Persons Denied Private Health Insurance Due to Poor Health. National Medical Expenditure Survey Data Summary 4 (Rockville: Department of Health and Human Services, 1991); and Brown, L., “The Medically Uninsured: Problems, Policies, and Politics,” Journal of Health Politics, Policy and Law, 15 (1990): 413–26.Google Scholar

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This sample was drawn from a stratified random sample of households in St. Joseph County, Indiana (the greater South Bend Metropolitan Area), obtained for another study conducted by the Indiana State Department of Health (DOH). See Murphy, M., Final Report: Consumer Survey of Chronic Disease Prevention Project, St. Joseph County, Indiana (Nov. 1993). Two methods were used to obtain the DOH study sample: (1) a county-wide, random-digit dialing of households, and (2) a house-to-house survey of households in thirteen census tracts with high proportions of minorities and low-income people. Each nonelderly adult resident (age 19 to 64) in the DOH study was asked to join our study. Of the 1,225 random contacts, 329 were too old (age 65+) for our study. Of the remaining 896 individuals, 508 (56.7 percent) agreed to participate. DOH interviewers forwarded the names, addresses, and telephone numbers to the authors. We conducted a subsequent telephone survey to collect data. We attempted to contact all consenting DOH study contacts. Not all consenting contacts could be reached again. Many had moved, changed telephone numbers, or were otherwise unreachable after multiple attempts. After many follow-up calls, 242 respondents participated successfully in our study.Google Scholar

To measure morbidity, we identified twenty-three separate categories of serious conditions that could affect all major organ systems. (These included heart disease, diseases of the nervous system, lung diseases, diseases of the glandular system, kidney diseases, liver diseases, intestinal diseases, skeletal diseases, muscle diseases, diseases of the immune system, drug or alcohol addiction, serious mental illness, treatment for high cholesterol, and cancer.) Respondents were asked to self-report whether they had any of these conditions. For analysis, data were grouped into the following categories: (1) no conditions, (2) one or two morbid conditions, and (3) more than two morbid conditions. In the South Bend Sample, respondents with one or more morbid conditions were placed in the Seriously Ill Subsample. All respondents in the Breast Cancer Sample had at least one morbid condition—cancer.Google Scholar

The Breast Cancer Sample was drawn from the tumor registries of the seven hospitals that treat over 90 percent of the women with breast cancer in Marion County, Indiana, the greater Indianapolis Metropolitan Area. The Breast Cancer Sample is comprised of women with breast cancer who: (1) resided in Marion County; (2) had been diagnosed or treated in the study hospitals; (3) were diagnosed and/or treated for Breast Cancer between January 1987 and December 1990; and (4) were between nineteen and sixty-four years of age at the time of the survey. Because of confidentiality concerns, the tumor registries contacted patients and forwarded names of willing study participants to the investigators. Tumor registries contacted 821 patients whom the hospitals recorded as having breast cancer in the relevant time period. Many letters requesting participation in the study were returned to the hospitals as undeliverable. Many other contacted respondents did not meet the study's age or residency criteria or, in a few cases, did not even have breast cancer. Because of the unreliable way in which hospitals handled returned mail for this study, inaccuracies in the demographic data in the tumor registries, and hospitals’ confidentiality concerns regarding nonparticipating patients, we could not conduct an analysis of the nonrespondents. Of the 208 women who agreed to participate in the study, 34 (16.5 percent) had died, moved, were too ill, or were otherwise unreachable for a telephone interview. In all, there were 174 women in the Breast Cancer Sample.Google Scholar

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We analyzed whether respondents were insured with a dichotomous dependent variable (uninsured [0] or insured [1]) using logistic regression. The independent variables used in all regression analyses included: Age, gender, race, marital status, educational status, employment status, annual household income, number of dependents, comorbidity, and reported health status. Whether respondents delayed seeking or taking treatment (delayed care [1] or not delay care [0]) was analyzed in the same way, except with the additional independent variable of insurance coverage status.Google Scholar

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The results of the regression are available from the authors.Google Scholar

The results of the regression are available from the authors.Google Scholar

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Specifically, 39.4 percent of the insured Seriously Ill Subsample and 31.9 percent of the insured Breast Cancer Sample were underinsured for this reason.Google Scholar

The results of the regression are available from the authors.Google Scholar

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