Hospitalization for Ambulatory Care Sensitive Conditions (ACSH) is an accepted indicator of access to health care and avoidable morbidity. Accessible care of reasonable quality should reduce ACSH. Little research has examined the indicator's external validity. We calculated standardized ACSH rates for 32 areas of Victoria, Australia (population 4.4 million). A representative survey measured access, disease prevalence, propensity to seek care, disease burden, social determinants of health services use, and behavioral risk factors. Regression analyses compared self-rated access with ACSH rates. Independent of prevalence, propensity to seek care, disease burden, and physician supply, better access was associated with lower ACSH rates. Results provide support for the ACSH indicator. When rural residence was considered, the covariate measuring access was not significant. However, rural residence also may contribute importantly to access. Results suggest both the complexity of the meaning of access and the desirability of further research to validate the ACSH indicator.

Background: Travel burden is a key element in conceptualizing geographic access to health care. Prior research has shown that both rural and minority populations bear disproportionate travel burdens. However, many studies are limited to specific types of patient or specific locales. The purpose of our study was to quantify geographic and race-based differences in distance traveled and time spent in travel for medical/dental care using representative national data.

Physician supply is positively associated with the overall performance of the primary health care system in a large sample of urban counties of the United States.

This study identified perceived physical activity (PA) enablers and barriers among a racially/ethnically and geographically diverse group of older adults. Data were from 42 focus groups conducted with African Americans, American Indians, Latinos, Chinese, Vietnamese, and non-Hispanic Whites (hereafter Whites). Constant-comparison methods were used to analyze the data. Common barriers were health problems, fear of falling, and inconvenience. Common enablers were positive outcome expectations, social support, and PA program access. American Indians mentioned the built environment and lack of knowledge about PA as barriers and health benefits as an enabler more than participants in other groups. Whites and American Indians emphasized the importance of PA programs specifically designed for older adults. Findings suggest several ways to promote PA among older people, including developing exercise programs designed for older adults and health messages promoting existing places and programs older adults can use to engage in PA.

The increment-decrement life-table methods used in several recent analyses of active life expectancy depend on parameters representing rates of movement between functional states such as "active" or "disabled." Available data often pose severe problems for the derivation of these parameters. For example, panel-survey data typically fail to record functional status between interviews. The time intervals between interviews also tend to vary across respondents, often substantially. The Longitudinal Study of Aging, used in this research, exhibits these problems. The authors develop a discrete-time Markov chain model of functional status dynamics that accommodates these features of the data and present maximum-likelihood estimates of the model. Also introduced is a new technique for the calculation of active life expectancy: microsimulation of functional status histories. The microsimulation technique permits the derivation of several new indexes of late life-course outcomes.