Search

Purpose: The purpose of this study was to determine the impact on resource use of providing case managers with information on the potential for patients to benefit from home care services. Design and Methods: Twenty-four case managers working in the Arizona Long Term Care System (ALTCS) were randomized into treatment and control groups. Members of the treatment group were given patient assessments for 25 ALTCS clients, estimates of the patients' risks for various adverse outcomes, and estimates of the aggregate potential benefit for each patient. Members of the control group were given only patient assessments (as is usual practice) for the same sample of 25 clients. Both groups were asked to independently write nonbinding care plans for each patient. The cost of each case manager's care plans was computed by multiplying standard costs per service times the mix and volume of services prescribed for each patient. Results: Treatment group care plan costs were, on average, lower than control group costs and closely tracked variation in estimated patient risks. Comparison group care plan costs were unrelated to risks. Implications: Information about risk and potential benefit can improve targeting of services to long-term-care clients. A prospective study using such an approach is warranted to see if provision of risk and potential benefit information would produce better clinical and economic outcomes.

State-to-state differences in generosity of assistance programs targeted toward poor seniors and people with disabilities have always been the 'price of federalism.' Typically, these differences are vitiated when federal law enters a field. Not so with the Medicare Prescription Drug, Improvement, and Modernization Act of 2003. States' choices of how much of the uncovered burden of prescription drug costs is left to near-poor elderly and disabled residents continues to vary widely even though Medicare began to provide pharmaceutical coverage beginning January 2006. The purpose of this article is to address the role that state policies play in promoting continued variation in access to prescription drugs, doi: 10.1300/J031v19n01_05 KEYWORDS. Prescription drugs, Medicaid, Medicare, elderly, disabled

Objectives. Although reliable direct state and local estimates of the activity-limited population are frequently unavailable, regression-adjusted synthetic estimates can be made. Such estimates use multivariate methods to model activity limitation at the national level and then apply model-predicted probabilities to corresponding community-specific demographic data. Methods. Using the 1989 National Health Interview Survey and the 1991 Area Resource File System, this study produced log-linear regression models that included person-level demographic and county-level contextual variables as predictors of activity limitation. Model-predicted rates were then multiplied by corresponding intercensal population data to generate state and local synthetic estimates of activity limitation. Results. Rates of activity limitation generally were found to increase with age and as the socioeconomic conditions of the county in which an individual resided worsened. Race and sex also tended to be statistically significant predictors of activity limitation. Conclusions. Activity limitation can be effectively modeled by age, sex, race, and community socioeconomic status. Synthetic estimates such as these are relatively simple to generate and can be useful for small-area planning in the absence of direct local estimates. (Am J Public Health. 1994;84:1813-1817), Estimates of local need for social and health services may be calculated effectively from national-level data. Typically estimates of the need for social services, the number of physically and mentally disabled and those with restrictions on performing daily activities are all developed at the national level. Small-area analyses are needed. Population data developed in 1989, the 1991 Area Resource Files and the 1989 National Health Interview Survey (NHIS) were used to develop statistical pictures of counties in the US. These can be matched to the individuals who respond to the NHIS, with emphasis on their answers to questions about performing major daily activities. Models then can be created to explore the likelihood of limits on activity and the services that a community might need to provide.

Health planning efforts for the population age 65 and over have been hampered continually by the lack of reliable estimates of the noninstitutionalized long-term care population. Until recently national estimates were virtually nonexistent, and reliable small area estimates remain unavailable. However, with the recent publication of several national surveys and the 1990 Census, synthetic estimates can be made for states and counties by using multivariate methods to model functional dependency at the national level, and then applying the predicted probabilities to corresponding state and county data. Using the 1984 National Health Interview Survey's Supplement on Aging and the 1986 Area Health Resources File System, we have produced log-linear regression models that include demographic and contextual variables as predictors of functional dependency among the noninstitutionalized population age 65 and over. Age, sex, race, and the percent of the 65 and over population who reside in poverty were found to be significant predictors of functional dependency. Applying these models to 1986 Medicare Enrollment Statistics, regression-adjusted synthetic estimates of two levels of functional dependency were produced for all states and--as examples of how the rates can be used to produce additional synthetic estimates--the largest County in each state. We also Produced point estimates and standard errors for the national prevalence of functional dependency among the noninstitutionalized population age 65 and over. (Am J Public Health 1990;81:335-343), Accurate estimation of the proportion of the population over age 65 that consists of functionally dependent people is necessary for health care planning, yet no clearly superior way of arriving at such an estimate has been developed. A method that uses log-linear regression models to estimate the numbers of noninstitutionalized dependent people over 65 is presented and applied to data drawn from several national and local surveys. This model allows for adjustments in the estimates due to several ''real-life'' factors, such as the effect of poverty on other factors that influence dependence (age, sex, race), and the fact that a small proportion (5 percent) of people older than 65 are not enrolled in Medicare. The results showed that age, sex, race, and poverty were the most important predictors of functional dependency. Using these variables, estimates of two levels of dependency were calculated for the individual states and selected counties. The two levels were ADL-dependent (people who have difficulty with the activities of daily life, such as dressing or eating), and those who could perform the activities of daily life but could not, for reasons of mobility, prepare meals, shop, or perform housework. The estimates are likely to prove useful for predicting the number of older people within a region who are likely to require long-term care. (Consumer Summary produced by Reliance Medical Information, Inc.)

Examined nationally representative sample of 60 adult day care centers to describe state of adult day care. Results indicated that day care centers could be categorized into 3 models of care, each serving distinctive subpopulation. Tested model appropriateness with analysis of variance of differences in participant characteristics. Contrasted services, staffing, costs, and other program features among 3 models. (Author/NB)

The article, originally published in the journal in 1988 and currently available in online-only format, provides strategies for providing effective and economical home- and community-based long-term medical care. These include prestratifying patients based on expected benefits, the use of prospective budgeting, and joining home and community care interventions with housing interventions.

Case management programs often designate a nurse or social worker to take responsibility for guiding care when patients are expected to be expensive or risk a major decline. We hypothesized that though an intuitively appealing idea, careful program design and faithful implementation are essential if case management programs are to succeed. We employed two theory perspectives, principal-agent framework and street-level bureaucratic theory to describe the relationship between program designers (principals) and case managers (agents/street-level bureaucrats) to review 65 case management studies. Most programs were successful in limited program-specific process and outcome goals. But there was much less success in cost-saving or cost-effectiveness-the original and overarching goal of case management. Cost results might be improved if additional ideas of agency and street-level theory were adopted, specifically, incentives, as well as "green tape," clear rules, guidelines, and algorithms relating to resource allocation among patients. [ABSTRACT FROM AUTHOR]