This study examined the association of mental and medical illnesses with the odds for leaving against medical advice (AMA) in a national sample of adult patients who left general hospitals between 1988 and 2006. Leaving AMA was first examined as a function of year and mental illness. Multiple logistic regression analysis was then used to adjust for patient and hospital characteristics when associating mental and major medical diagnoses with AMA discharges. The results indicated that leaving AMA was most strongly associated with mental health problems. However, the impact of mental illness was attenuated after adjusting for medical illnesses, patient and hospital characteristics. The strongest predictors of AMA discharge included being self-pay, having Medicaid insurance, being young and male, and the regional location of the hospital (Northeast). When substance abuse conditions were excluded from the mental illness discharge diagnoses, mental illness had lower odds for leaving AMA. The results may be of value to clinicians, and hospital administrators in helping to profile and target patients at risk for treatment-compliance problems. Prospective primary data collection that would include patient, physician, and hospital variables is recommended.

The inequitable geographic distribution of health care resources has long been recognized as a problem in the United States. Traditional measures, such as a simple ratio of supply to demand in an area or distance to the closest provider, are easy measures for spatial accessibility. However the former one does not consider interactions between patients and providers across administrative borders and the latter does not account for the demand side, that is, the competition for the supply. With advancements in GIS, however, better measures of geographic accessibility, variants of a gravity model, have been applied. Among them are (1) a two-step floating catchment area (2SFCA) method and (2) a kernel density (KD) method. This microscopic study compared these two GIS-based measures of accessibility in our case study of dialysis service centers in Chicago. Our comparison study found a significant mismatch of the accessibility ratios between the two methods. Overall, the 2SFCA method produced better accessibility ratios. There is room for further improvement of the 2SFCA method--varying the radius of service area according to the type of provider or the type of neighborhood and determining the appropriate weight equation form--still warrant further study.

The Internet is increasingly being recognized as an invaluable component of education. At the college and university level, online databases and statistical tools for Web-based analysis and data subset extraction have become important instructional resources. These Internet resources enable students to formulate specific research hypotheses, identify relevant variables, and analyze large existing databases. This article describes three of these resources: the Federal Electronic Research and Review Extraction Tool (FERRET) of the U.S. Bureau of the Census, the Survey Documentation and Analysis (SDA) unit at the University of California, Berkley, and the Inter-University Consortium for Political and Social Research (ICPSR), which is housed at the University of Michigan.

In 1980, while most hospitals were in reasonably good financial health, hospitals heavily involved in serving the poor ran a considerable risk of financial trouble. Fewer than 9 percent of the nation's hospitals accounted for 40 percent of the nation's total care to the poor. These hospitals, almost half of which were in the 100 largest cities, not only devoted more of their care to the poor than other hospitals, they also served substantially smaller proportions of privately-insured patients. The result was that one-third of these hospitals--by themselves accounting for over 15 percent of all care to the poor--ran deficits in 1980. Using data from a 1980 survey of nonfederal, nonprofit hospitals, this paper examines the fiscal situation of hospitals heavily involved in serving the poor. The analysis shows that it is insufficient revenues, not inefficiency or underuse, that creates these hospitals' financial problems. The article concludes with an assessment of several policies that could be adopted to alleviate this financial pressure and sustain care to the poor.

The relationship between an organization's staff structure, particularly the relative proportions of its administrators and line staff, and the organization's size, ownership status, financial condition, and scope of services is a subject that has attracted a good deal of attention from organizational theorists. At the present time, the subject is especially important to the hospital industry because of widespread concern about hospital costs and interest in how personnel expenses contribute to these costs.

This article starts out with the premise that a "uniform occupancy rate" for hospitals is not a meaningful concept because the ability of individual hospitals to maintain a certain occupancy rate consistent with a specified "protection level" depends upon several factors. These factors include hospital size, the number of nonsubstitutable patient facilities, the percent of nonurgent (elective) beds, the number of hospitals serving an area, and the relative variation (fluctuation) in the demand for services faced by the hospital. A regression analysis with observed, overall occupancy rate as the dependent variable, and measures that attempt to represent the factors just mentioned as independent variables, tends to substantiate this line of reasoning. However, inasmuch as the status of the independent variables (that is, whether or not they can be regarded as justifiable or uncontrollable) depends largely on the circumstances of each case, the regression model cannot be used as a standard-setting tool. Nonetheless, it offers valuable guidelines for hospital management, planners, and regulators in such areas of decisionmaking as the location and size of hospitals, and acceptable occupancy standards.

Proprietary hospital chains are now the predominant, and the fastest growing, segment of the for-profit sector of the hospital industry. This paper examines the relationships between the growth patterns of proprietary hospital chains and state-level variations in a number of demographic and economic factors related to health care. Results indicate that increases in the market share of proprietary chains are greatest in states that have the greatest increases in population, per capita income, and insurance coverage and that already have large proprietary market shares of beds. The growth behavior of proprietary chains thus appears to be highly consistent with standard market behavior.

About one-third of the nation's poor lack insurance--public or private--against the costs of illness. Data from 1980 and 1982 show that a patchwork of state and local government charitable grants, and the disparate efforts of hospitals to provide free care, cannot mend the national "safety net." A prudent short-run approach to modifying charity care is advanced, although the long-run necessity for insuring the uninsured is inevitable.

Health Data Sources is an ongoing series talking about data sources useful to health services researchers. Contributors have included Ross Mullner, Peter Kralovec, Edward Kobrinski and Jack Hadley. Each piece begins with a description of the data base and is followed by evaluative comments from a recent user.

This paper is an overview of hospital closure in the United States for the five-year period 1976-1980. We describe the distributional patterns of closings among noncommunity and community hospitals classified according to institutional characteristics such as bed size, control, and location. We also examine the ten percent of community hospitals operating at the beginning of the period which were shown to have combined institutional characteristics strongly associated with closure via a method of regression analysis.

The second of a three-part series of articles analyzing the results of the American Hospital Association's Nursing Personnel Survey, this article examines data about RN vacancies and turnover among community hospitals in general and community hospitals classified by bed size, control, and geographic region. It discusses the implications of the findings for nursing administrators.

Vacancy rates for RNs and for LPNs reported in a universe survey of U.S. community hospitals were examined for relationships to a number of characteristics of the institutional makeup, environment and setting, staff organization and composition of these hospitals. RN vacancy rates were found to have a statistically significant positive relationship to the number of beds in the hospitals, the number of hospital beds in the states in which the hospitals were located, and government control. Significant negative relationships were found with the number of RN graduates from nursing programs in the state, occupancy rate, and the ratio of RNs to total inpatient days. LPN vacancy rates showed a significant positive relationship to government control, southern locations, restriction of admissions to children and the ratio of RNs to LPNs. LPN vacancy rates showed a significant negative relationship to the number of hospital beds, occupancy rate, the ratio of LPNs to total inpatient days and the ratio of other nursing service personnel to LPNs.

This paper analyzed the results of the American Hospital Association's (AHA) 1981 survey of inpatient medical rehabilitation hospitals and units, which obtained information for 1980, and notes important differences from the patterns revealed by the survey when it was first conducted in 1979. The survey sample consisted of 554 hospitals, 334 of which responded to the questionnaire. Three categories of these hospitals (independent rehabilitation hospitals, self-contained rehabilitation hospitals within larger medical centers, and defined rehabilitation units of institutions) are examined in terms of utilization, referral sources of their admissions, places to which their patients were discharged, composition of their full-time equivalent professional medical staff, and sources of payment for inpatient claims.

1Associate director of health information and data services, Chicago, Ill 2Project director of the department of survey research, Chicago, Ill 3The director of the division of nursing at the American Hospital Association, Chicago, Ill