Getting Past Denial - The High Cost of Health Care in the United States

Dartmouth Institute for Health Policy and Clinical , Lebanon, NH, USA.
New England Journal of Medicine (Impact Factor: 55.87). 10/2009; 361(13):1227-30. DOI: 10.1056/NEJMp0907172
Source: PubMed
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    • "It is less well tested in respect of diagnostic procedures, and the area requires further discussion, reflection, and ethical/legal consideration. Each person is entitled to a reasonable expectation of health and equal access to health care (Durand-Zaleski, 2009; Sutherland, Fisher, & Skinner, 2009; Wennberg et al., 2008). There are many factors that complicate availability and access to radiological procedures that result in favor of one region, one individual, or one group over others. "
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    ABSTRACT: Chapter Outline 7.1 Introduction 107 7.2 Ethics in Medical Radiology 109 7.2.1 Core Principles in Medical Ethics 109 7.2.2 A Basic Analysis 111 7.3 Medical, Social, and Legal Context for Radiology 114 7.3.1 Overutilization and Health Economics 116 7.4 Risk, Uncertainty,Communication, and Skeptical Doctors 116 7.5 Justification Issues 118 7.5.1 Awareness 119 7.5.2 Appropriateness and Referral Guidelines 120 7.5.3 Audit (Clinical) 121 7.5.4 Some Reasons for Failure of Justification 121 7.6 Some Special Concerns 121 7.6.1 Nonmedical Exposures 121 7.6.2 Regulatory Framework 122 7.6.3 Some Pregnancy Issues 123 7.7 Conclusions 124
    Social and Ethical Aspects of Radiation Risk Management, First edited by D. Oughton & S. Ove Hansson, 09/2013: chapter 7: pages 105-130; Elsevier Science., ISBN: 9780080450155
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    • "Our findings also potentially have implications for health policy debates about whether to try to equalize health spending across areas. Previous studies have shown, for example, that a family's own income helps explain some – but only some – of the variation across areas in health expenditures (Sutherland, Fisher, and Skinner, 2009). Our results suggest that the geographic concentration of poverty within an area may also matter for health beyond each family's own individual poverty status. "
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    ABSTRACT: In this paper we estimate the causal effects on child mortality from moving into less distressed neighborhood environments. We match mortality data covering the period from 1997 to 2009 with information on every child in public housing that applied for a housing voucher in Chicago in 1997 (N=11,680). Families were randomly assigned to the voucher wait list, and only some families were offered vouchers. The odds ratio for the effects of being offered a housing voucher on overall mortality rates is equal to 1.13 for all children (95% CI 0.73-1.70), 1.34 for boys (95% CI 0.85-2.05) and 0.21 for girls (95% CI 0.01-1.04).
    Journal of Health Economics 10/2012; 32(1):195-206. DOI:10.1016/j.jhealeco.2012.10.008 · 2.58 Impact Factor
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    • "Fewer studies have examined the association between lower income and greater health care utilization, but some exist. These have shown relationships between low income and higher health care expenditures,14,63–65 more hospital admissions,2,66 more preventable hospitalizations,36–39,42,67 and more out-patient visits.68,69 Low income has also been linked to lower educational attainment, which has separately been shown to correlate with increased disease prevalence, shorter life expectancy, and higher Medicare expenditures.16,49,50,70,71 "
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    ABSTRACT: Geographic variation has been of interest to both health planners and social epidemiologists. However, while the major focus of interest of planners has been on variation in health care spending, social epidemiologists have focused on health; and while social epidemiologists have observed strong associations between poor health and poverty, planners have concluded that income is not an important determinant of variation in spending. These different conclusions stem, at least in part, from differences in approach. Health planners have generally studied variation among large regions, such as states, counties, or hospital referral regions (HRRs), while epidemiologists have tended to study local areas, such as ZIP codes and census tracts. To better understand the basis for geographic variation in hospital utilization, we drew upon both approaches. Counties and HRRs were disaggregated into their constituent ZIP codes and census tracts and examined the interrelationships between income, disability, and hospital utilization that were examined at both the regional and local levels, using statistical and geomapping tools. Our studies centered on the Milwaukee and Los Angeles HRRs, where per capita health care utilization has been greater than elsewhere in their states. We compared Milwaukee to other HRRs in Wisconsin and Los Angeles to the other populous counties of California and to a region in California of comparable size and diversity, stretching from San Francisco to Sacramento (termed "San-Framento"). When studied at the ZIP code level, we found steep, curvilinear relationships between lower income and both increased hospital utilization and increasing percentages of individuals reporting disabilities. These associations were also evident on geomaps. They were strongest among populations of working-age adults but weaker among seniors, for whom income proved to be a poor proxy for poverty and whose residential locations deviated from the major underlying income patterns. Among working-age adults, virtually all of the excess utilization in Milwaukee was attributable to very high utilization in Milwaukee's segregated "poverty corridor." Similarly, the greater rate of hospital use in Los Angeles than in San-Framento could be explained by proportionately more low-income ZIP codes in Los Angeles and fewer in San-Framento. Indeed, when only high-income ZIP codes were assessed, there was little variation in hospital utilization among California's 18 most populous counties. We estimated that had utilization within each region been at the rate of its high-income ZIP codes, overall utilization would have been 35 % less among working-age adults and 20 % less among seniors. These studies reveal the importance of disaggregating large geographic units into their constituent ZIP codes in order to understand variation in health care utilization among them. They demonstrate the strong association between low ZIP code income and both higher percentages of disability and greater hospital utilization. And they suggest that, given the large contribution of the poorest neighborhoods to aggregate utilization, it will be difficult to curb the growth of health care spending without addressing the underlying social determinants of health.
    Journal of Urban Health 05/2012; 89(5):828-47. DOI:10.1007/s11524-012-9689-3 · 1.90 Impact Factor
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