Poverty reduction on a large scale depends on empowering those who are most motivated to move out of poverty - poor people themselves. But if empowerment cannot be measured, it will not be taken seriously in development policy making and programming.

Building on the award-winning Empowerment and Poverty Reduction sourcebook, this volume outlines a conceptual framework that can be used to monitor and evaluate programs centered on empowerment approaches. It presents the perspectives of 27 distinguished researchers and practitioners in economics, political science, sociology, psychology, anthropology, and demography, all of whom are grappling in different ways with the challenge of measuring empowerment. The authors draw from their research and experiences at different levels, from households to communities to nations, in various regions of the world.

Measuring Empowerment is an invaluable resource for planners, practitioners, evaluators, and students?indeed for all who are interested in approaches to poverty reduction that address issues of inequitable power relations.

Background: Low rates of technology utilization in hospitals with high proportions of black inpatients may be a remediable cause of healthcare disparities.

Objectives: Our objective was to determine how differences in technology utilization among hospitals contributed to racial disparity and if temporal reduction in hospital procedure rate variation resulted in decreased racial disparity for these technologies.

Methods: We identified 2,348,952 elderly Medicare beneficiaries potentially eligible for 1 of 5 emerging medical technologies from 1989-2000 and determined if these patients had received the indicated procedure within 90 days of their qualifying hospital admission. Initial multivariate regression models adjusted for age, race, sex, admission year, clinical comorbidity, community levels of education and income, and academic/urban hospital admission. The inpatient racial composition of each patient's admitting hospital and time-race interactions were added as covariates to subsequent models.

Results: Blacks had significantly lower adjusted rates (P 0.001) compared with whites for tissue replacement of the aortic valve, internal mammary artery coronary bypass grafting, dual-chambered pacemaker implantation, and lumbar spinal fusion. Hospitals with > 20% black inpatients were less likely to perform these procedures on both white and black patients than hospitals with 9% black inpatients, and racial disparity was greater in hospitals with larger black populations. There were no temporal reductions in racial disparities.

Conclusions: Blacks may be disadvantaged in access to new procedures by receiving care at hospitals that have both lower procedure rates and greater racial disparity. Policies designed to ameliorate racial disparities in health care must address hospital variation in the provision of care.

Mortality rates in the United States fell more rapidly during the late nineteenth and early twentieth centuries than in any other period in American history. This decline coincided with an epidemiological transition and the disappearance of a mortality "penalty" associated with living in urban areas. There is little empirical evidence and much unresolved debate about what caused these improvements, however. In this article, we report the causal influence of clean water technologies -- filtration and chlorination -- on mortality in major cities during the early twentieth century. Plausibly exogenous variation in the timing and location of technology adoption was used to identify these effects, and the validity of this identifying assumption is examined in detail. We found that clean water was responsible for nearly half the total mortality reduction in major cities, three quarters of the infant mortality reduction, and nearly two thirds of the child mortality reduction. Rough calculations suggest that the social rate of return to these technologies was greater than 23 to 1, with a cost per person-year saved by clean water of about $500 in 2003 dollars. Implications for developing countries are briefly considered.

Objectives

The study was designed to determine whether racial disparity in utilization of the implantable cardioverter-defibrillator (ICD) has improved over time, and whether small-area geographic variation in ICD utilization contributed to national levels of racial disparity.

Background

Although racial disparities in cardiac procedures have been well-documented, it is unknown whether there has been improvement over time. Low ICD utilization rates in predominantly black geographic areas may have exacerbated national levels of disparity.

Methods

Discharge abstracts from elderly black and white Medicare beneficiaries hospitalized with ventricular arrhythmias from 1990 to 2000 were analyzed to determine if ICD implantation occurred within 90 days of initial hospitalization. Multivariate logistic regression models were constructed to assess the relationship between ICD implantation, year of admission, and the percentage of black inhabitants in each patient's county of hospitalization while controlling for clinical, hospital, and demographic characteristics.

Results

There was improvement in ICD implantation racial disparity: In the period 1990 to 1992, black patients had an odds ratio of 0.52 (95% confidence interval [CI] 0.42 to 0.64) for receiving an ICD compared with whites. However, by 1999 to 2000, the odds ratio for blacks had risen to 0.69 (95% CI 0.61 to 0.78) (test-for-trend p = 0.01). Approximately 20% of this trend could be explained by reduction in geographic variation in ICD use between areas with larger black and predominantly white populations.

Conclusions

Rates of ICD implants became more equal among whites and blacks during the 1990s, although persistent disparity remained at the decade's end. Geographic equalization in cardiovascular procedure rates may be an essential mechanism in rectifying disparities in health care.

This issue of CHP/PCOR's quarterly newsletter covers news and developments from the fall 2004 quarter. It features articles about:

• the newly created Center on Advancing Decision Making for Aging (CADMA), a multidisciplinary research collaboration administered by CHP/PCOR that will explore how older Americans make decisions about their health and well-being;
• a roundtable discussion with healthcare and biotech industry leaders, sponsored by CHP/PCOR and led by Sean Tunis, MD, chief medical officer at the Centers for Medicare and Medicaid Services;
• groundbreaking research on the health needs and health status of China's elderly, conducted by trainees in CHP/PCOR's China-U.S. Health and Aging Research Fellowship;
• research by CHP/PCOR faculty and affiliates on racial disparities in the use of implantable cardioverter-defibrillators (ICDs), the drug industry's marketing of low-dose forms of hormone replacement therapy, and the long-term risks of surgery and anesthesia; and
• renewed funding and seed projects for CHP/PCOR's Center on the Demography and Economics of Health and Aging.

The traditional focus of disability research has been on the elderly, with good reason. Chronic disability is much more prevalent among the elderly, and it has a more direct impact on the demand for medical care. It is also important to understand trends in disability among the young, however, particularly if these trends diverge from those among the elderly. These trends could have serious implications for future health care spending because more disability at younger ages almost certainly translates into more disability among tomorrow's elderly, and disability is a key predictor of health care spending. Using data from the Medicare Current Beneficiary Survey (MCBS) and the National Health Interview Study (NHIS), we forecast that per-capita Medicare costs will decline for the next fifteen to twenty years, in accordance with recent projections of declining disability among the elderly. By 2020, however, the trend reverses. Per-capita costs begin to rise due to growth in disability among the younger elderly. Total costs may well remain relatively flat until 2010 and then begin to rise because per-capita costs will cease to decline rapidly enough to offset the influx of new elderly people. Overall, cost forecasts for the elderly that incorporate information about disability among today's younger generations yield more pessimistic scenarios than those based solely on elderly data sets, and this information should be incorporated into official Medicare forecasts.

Objective: To quantify the effects of informal caregiver availability and public funding on formal long-term care (LTC) expenditures in developed countries.

Data Source/Study Setting: Secondary data were acquired for 15 Organization for Economic Cooperation and Development (OECD) countries from 1970 to 2000. Study Design. Secondary data analysis, applying fixed- and random-effects models to time-series cross-sectional data. Outcome variables are inpatient or home heath LTC expenditures. Key explanatory variables are measures of the availability of informal caregivers, generosity in public funding for formal LTC, and the proportion of the elderly population in the total population.

Data Collection/Extraction Method: Aggregated macro data were obtained from OECD Health Data, United Nations Demographic Yearbooks, and U.S. Census Bureau International Data Base.

Principal Findings: Most of the 15 OECD countries experienced growth in LTC expenditures over the study period. The availability of a spouse caregiver, measured by male-to-female ratio among the elderly, is associated with a $28,840 (1995 U.S. dollars) annual reduction in formal LTC expenditure per additional elderly male. Availability of an adult child caregiver, measured by female labor force participation and full-time/part-time status shift, is associated with a reduction of $310 to $3,830 in LTC expenditures. These impacts on LTC expenditure vary across countries and across time within a country.

Conclusions: The availability of an informal caregiver, particularly a spouse caregiver, is among the most important factors explaining variation in LTC expenditure growth. Long-term care policies should take into account behavioral responses: decreased public funding in LTC may lead working women to leave the labor force to provide more informal care.

Objective: To determine whether health maintenance organizations (HMOs) attract enrollees who use relatively few medical resources and whether a simple risk-adjustment system could mitigate or eliminate the inefficiency associated with risk selection.

Data Sources: The first and second rounds of the Community Tracking Study Household Survey (CTSHS), a national panel data set of households in 60 different markets in the United States.

Study Design: We use regression analysis to examine medical expenditures in the first round of the survey between enrollees who switched plan types (i.e., from a non-HMO plan to an HMO plan, or vice versa) between the first and second rounds of the survey versus enrollees who remained in their original plan. The dependent variable is an enrollee's medical resource use, measured in dollars, and the independent variables include gender, age, self-reported health status, and other demographic variables.

Data Collection Methods: We restrict our analysis to the 6,235 non-elderly persons who were surveyed in both rounds of the CTSHS, received health insurance from their employer or the employer of a household member in both years of the survey, and were offered a choice of an HMO and a non-HMO plan in both years.

Principal Findings: We find that people who switched from a non-HMO to an HMO plan used 11 percent fewer medical services in the period prior to switching than people who remained in a non-HMO plan, and that this relatively low use persisted once they enrolled in an HMO. Furthermore, people who switched from an HMO to a non-HMO plan used 18 percent more medical services in the period prior to switching than those who remained in an HMO plan.

Conclusions: HMOs are experiencing favorable risk selection and would most likely continue to do so even if employers adjusted health plan payments based on enrollees' gender and age because the selection is based on enrollee characteristics that are difficult to observe, such as preferences for medical care and health status.

We all have a stake in the size of the physician workforce. With too few physicians, access to care will be compromised; with too many, there will be strong pressures to overconsume health services. Increasing the production of U.S.-trained physicians by expanding physical resources of medical schools and creating new residency and fellowship positions will be costly and will have delayed, long-lasting effects on the supply of physicians' services. According to those who believe that physicians increase the demand for their own services, every additional physician would generate added health care costs for the length of a career, which now averages about 30 years. These increased expenditures would dwarf the short-term costs of expanding our capacity to train physicians.

Because new graduates are a small fraction of the total physician workforce, the supply of physicians would change little in the short run, even if it were possible to expand the number of training positions instantly. In an article in this issue (1), Richard Cooper forcefully argues that this delay is an important reason to take immediate action to increase the production of physicians. He projects that the United States will have 200 000 fewer physicians than we need in 2020. We agree that demographic and economic trends could increase the demand for physician services in the coming years, but we also believe that his forecast contains far too many uncertainties to serve as the basis for taking immediate action. We think that Cooper's analysis does not take account of important factors that could change the need for large increases in physician supply. In this commentary, we discuss the potential roles of a healthier aging population, changes in government policy, new technology, physician-induced demand for health care, and changes in the price of health care.

Some years ago, I spent a sabbatical year as a fellow at Stanford’s Center for Advanced Study in the Behavioral Sciences, doing research and finishing a book. A group of psychologists met each week at the center to discuss and (mostly) argue about stigmas and stereotypes, seeking to understand how the social responses to people with disabilities influenced their self-images.