Perceived Experiences of Discrimination in Health Care: A Barrier for Cancer Screening Among American Indian Women with Type 2 Diabetes

PURPOSE: Breast and cervical cancer-mortality disparities are prominent among American Indian women. These disparities, in part, may result from patients perceived experiences of discrimination in health care. This report evaluates the impact of perceived discrimination on screening for breast and cervical cancer in a sample of 200 American Indian women with type 2 diabetes. METHODS: Data were collected from patient report and medical records. Prevalence of breast and cervical cancer screening were assessed. Unadjusted and adjusted logistic regression analyses were used to assess associations between perceived discrimination, cancer screening status, and patients' health care-seeking behaviors. FINDINGS: Substantial proportions of AI women in our sample were behind the recommended schedules of screening for breast and cervical cancer. Adjusted estimates revealed that perceived discrimination was significantly associated with not being current for clinical breast examination and Pap test, and was close to statistical significance with not being current for mammography. The number of suboptimal health care-seeking behaviors increased with higher mean levels of perceived discrimination. CONCLUSIONS: Among AI women, perceived discrimination in health care may negatively influence use of breast and cancer screening services, and health care-seeking behaviors. More research is needed among AIs to examine features of health care systems related to the phenomenon patients perceived experience of discrimination

A Frontier Approach to Testing the Averch–Johnson Hypothesis

Abstract The mathematical programming technique Data Envelopment Analysis is used to test the famous hypothesis of Averch and Johnson that utility regulation leads to overuse of capital because the regulated firm earns a return s greater than its cost of capital r, an implicit capital subsidy resulting in allocative inefficiency. Technical and allocative inefficiency are based on cost and production frontiers from 337 electric generating plants using 1970 data, and r is based on the Capital Asset Pricing Model. Significant capital overuse and general failure to minimize costs is detected, but a second‐step regression analysis finds no relationship between the overuse and the s–r subsidy. A small updated data set covering the period 1980–2004 suggests that overuse of capital is no longer a problem, a result that may be owing to recente deregulation and restructuring.Electric Utilities, Economics of Regulation, Programming Models, L94, L51, C61,