Heterogeneity of risk in a managed home health care population.

OBJECTIVE: To examine the distribution of risk and the correlation between risks in a home care population with regard to several important adverse outcomes. BACKGROUND: Researchers and policy makers have long recognized the heterogeneity of home care populations. Most research in this area focuses on identifying predictors of adverse outcomes. The degree of the heterogeneity of risks is much more poorly understood. Yet understanding the degree of risk heterogeneity at the population level is important because it has implications for the extent to which the level of care should vary among recipients. STUDY SETTING: Patients enrolled in the Arizona Health Care Cost Containment System (AHCCCS) program, between the December 1992 and April 1998. OUTCOME MEASURES: Estimating the risk for nursing home placement, hospitalization, death, and functional decline. METHODS: Estimating discrete time hazard models. From these models the predicted risk for each outcome is estimated and the distribution and correlation of predicted risks is examined. Model fit is assessed through split sample techniques and by examining the ratio of predicted to actual outcomes for selected sub-groups. RESULTS: The estimates reveal a wide variation in predicted risk. The ratio of predicted risk at the 90th percentile relative to the 10th percentile ranges from 4.99 for nursing home admission to 6.65 for hospitalization. The distributions of predicted risks are all skewed, particularly the distributions for death and nursing home admission. Predicted nursing home risk is highly correlated with the predicted risk for death (rho = 0.71). The predicted risk for hospitalization is not strongly correlated with the predicted risk for either death or nursing home admission. CONCLUSION: The wide variation in risk among home care patients suggests that efficient allocation of resources would require variation in spending and targeting of services based on patient characteristics. Greater research regarding the effectiveness of home care for different sub-populations is called for.

Incidence of four adverse outcomes in the elderly population: implications for home care policy and research.

The cost-effective allocation of home care resources requires knowledge of the incidence of institutionalization, hospitalization, functional impairment, and mortality. We therefore assembled a database containing 176 rates abstracted from 71 longitudinal studies published between 1985 and 1998 that examine one or more of these outcomes in the 65 and over population in the United States. Where possible we calculate median values for the estimated annual rate of each outcome for different types of studies-nationally representative, sub-national probability, and convenience sample-and specific subgroups-community residents, hospital admissions and discharges, and nursing home admissions and discharges. We find comparatively low rates of institutionalization and mortality, relatively high rates of hospitalization and functional impairment, similar rates for national and sub-national probability samples, and rates from convenience samples, which greatly exceed probability-based rates. While the rates for institutionalization, hospitalization and mortality are quite stable, the rates for functional impairment display considerably more variability. We conclude by discussing the implications of our findings for researchers and policymakers.

Predicting elderly people's risk for nursing home placement, hospitalization, functional impairment, and mortality: a synthesis.

Long-term care resources would be allocated more cost-effectively if care planning and medical/functional eligibility decisions were grounded more firmly in extant evidence regarding the risk of nursing home placement, hospitalization, functional impairment, and mortality. This article synthesizes the studies that longitudinally assess the predictors of each of these outcomes for the 65 and older population in the United States. A database was assembled containing 167 multivariate analyses abstracted from 78 journal articles published between 1985 and 1998. Findings show that 22 risk factors consistently predict two or more outcomes, including three that predict all four: worse performance on physical function measures not based on activities of daily living, greater illness severity, and prior hospital use. Findings should help prioritize variable selection choices of those setting eligibility criteria, allocating care resources, and doing descriptive studies. Gaps are shown to exist in the understanding of outcome effects of facility, market, policy, and other system attributes.

Willingness to pay for a quality-adjusted life year: in search of a standard.

Cost-benefit analysis (CBA) provides a clear decision rule: undertake an intervention if the monetary value of its benefits exceed its costs. However, due to a reluctance to characterize health benefits in monetary terms, users of cost-utility and cost-effectiveness analyses must rely on arbitrary standards (e.g., < $50,000 per QALY) to deem a program "cost-effective." Moreover, there is no consensus regarding the appropriate dollar value per QALY gained upon which to base resource allocation decisions. To address this, the authors determined the value of a QALY as implied by the value-of-life literature and compared this value with arbitrary thresholds for cost-effectiveness that have come into common use. A literature search identified 42 estimates of the value of life that were appropriate for inclusion. These estimates were classified by method: human capital (HK), contingent valuation (CV), revealed preference/job risk (RP-JR) and revealed preference/non-occupational safety (RP-S), and by U.S. or non-U.S. origin. After converting these value-of-life estimates to 1997 U.S. dollars, the life expectancy of the study population, age-specific QALY weights, and a 3% real discount rate were used to calculate the implied value of a QALY. An ordinary least-squares regression of the value of a QALY on study type and national origin explained 28.4% of the variance across studies. Most of the explained variance was attributable to study type; national origin did not significantly affect the values. Median values by study type were $24,777 (HK estimates), $93,402 (RP-S estimates), $161,305 (CV estimates), and $428,286 (RP-JR estimates). With the exception of HK, these far exceed the "rules of thumb" that are frequently used to determine whether an intervention produces an acceptable increase in health benefits in exchange for incremental expenditures.

State legislative staff influence in health policy making.

State legislative staff may influence health policy by gathering intelligence, setting the agenda, and shaping the legislative proposals. But they may also be stymied in their roles by such institutional constraints as hiring practices and by turnover in committee leadership in the legislature. The intervening variable of trust between legislators and their support staff is also key to understanding influence and helps explain how staff-legislator relationships play an important role in designing state health policy. This study of legislative fiscal and health policy committee staff uses data from interviews with key actors in five states to model the factors important in explaining variation in the influence of committee staff on health policy.

Balancing resources and risk: selecting home care clients in Florida's CARES program.

Selecting home care patients who would otherwise go into a nursing home always involves error: serving too many or two few. To clarify the choices program and case managers must make, we propose a risk-based alternative to current selection methods that involves scientifically-derived variable weighting and conscious choice of cut-off score for bestowing home care eligibility. We illustrate our proposal with data from Florida's Comprehensive Assessment and Review of Long-term Care Services (CARES) program. Using logistic regression we identify characteristics that distinguish clients recommended for nursing home placement from those referred to the community and use these results to estimate the risk of nursing home recommendation for each client. An approach to using these risk scores to determine eligibility is demonstrated along with assessment of the impact of alternative risk score cut-offs on denying care to as many as half or as few as 5% of clients served.

Managed care for elderly people: a compendium of findings.

Although managed care seems to serve well the interests of non-elderly enrollees and their payers, elderly people face more risks. Chronic conditions, multiple problems, and more limited resources make them more vulnerable, whereas multiple payer sources make them more complicated to cover. This synthesis of managed care delivered in Medicare and Medicaid demonstration projects serving elderly beneficiaries shows that managed care plans either select or attract enrollees who suffer fewer frailties than those served in fee-for-service settings, exhibit reluctance to enter rural markets, provide a broad range of elderly-specific services, offer more comprehensive coverage and services, and result in greater perceived access problems, particularly for vulnerable subgroups. Plans operate more cheaply by using fewer resources, even after adjusting for case mix differences. Managed care enrollees tend to be more satisfied with financial and coverage aspects, whereas fee-for-service enrollees report higher satisfaction on other dimensions. In acute care settings, process of care findings were mixed, whereas clinical and self-reported outcome indicators were no better and in some instances worse in managed care. Long-term care enrollees, in the few studies reported, consistently faired worse in both the processes and outcomes of care. These findings suggest that further research on the effects of managed care in its rapidly changing incarnations is needed, particularly with respect to how to improve the quality of acute and long-term care delivered to elderly people and the proper role of government and other key actors in the health care system.

Cost savings from home and community-based services: Arizona's capitated Medicaid long-term care program.

The Arizona Long-Term Care System is the first capitated, long-term care Medicaid program in the nation to operate statewide. It promotes an extensive home and community-based services program intended to lower long-term care costs by substituting home care for institutional care. Because the program is statewide, finding a suitable control group to evaluate it was a serious problem. A substitute strategy was chosen that compares actual costs incurred to an estimate of what costs would have been in the absence of home and community-based (HCB) services. To estimate the likelihood of institutionalizing clients in the absence of HCB services, coefficients for institutionalization risk factors were estimated in a logistic regression model developed using national data. These were applied to characteristics of Arizona clients. The model assigned approximately 75 percent of the program's clients to a category with traits that were determined to resemble nursing home residents' traits. A similar methodology was used to estimate lengths of nursing home stays. Lengths of stay by the program's nursing home patients were regressed on their characteristics using an event history analysis model. Coefficients for these characteristics from the regression analysis were then applied to HCB services clients to estimate how long their nursing home stays would have lasted, had they been institutionalized. These estimated nursing home stays were generally shorter than these same patients' observed home and community stays. Risk of institutionalization was then multiplied by estimated length of stay and by monthly nursing home costs to estimate what costs would have been without the HCB services option. The expected costs were compared to actual costs to judge cost savings. Home and community-based services appeared to save substantial amounts on costs of nursing home care. Estimates of savings were very robust and did not appear to be declining as the program matured. Savings probably came from several sources: the assessment teams that judged client eligibility were employed by a state agency and thus were independent from the program contractors; clients were required to be in need of at least a three-month nursing home stay; a cap was placed on the number of HCB services clients contractors were allowed to serve each month; the capitated payment methodology forced managed care contractors to hold down average HCB services costs or lose money; and the HCB services and nursing home costs were blended in the capitated rate, so that plans that failed to place clients in HCB services would lose money by using more nursing home days than their monthly capitated rate allowed.

Estimating activity limitation in the noninstitutionalized population: a method for small areas.

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.

ADL dependent people may also be sick: neglect of the "home health" population in the home care debate.

Fear of large new public outlays have muted debate over recent proposals to expand subsidized supportive (non-medical) home care services for the elderly. Data from the billing portion of the 1984 National Long Term Care Survey demonstrate that of the approximately one million community-dwelling elderly persons whose chronic functional impairments would make them eligible for many proposed home care programs, nearly one third (31%) received services from a home health agency over a 12-month period. Since home health agencies provide substantial amounts of supportive services to enrollees, it is estimated that between three and six million non-medical visits are provided annually to chronically functionally impaired persons through home health agencies. These existent services should be taken into account in predicting the incremental public service burden and costs of proposed supportive home care programs.

Case mix adjusted nursing-home reimbursement: a critical review of the evidence.

Nursing-home case mix adjusted payment systems typically base payments on estimates of patients' care needs, but to date the data on their effectiveness are ambiguous. Studies mainly show that access for patients most in need of care appears to improve under these systems. Case mix based payment systems have both positive and negative effects on quality of care and require compensating mechanisms for the potentially harmful incentives they can generate. On the positive side, nursing homes are paid more equitably; the negative aspect is reflected in higher costs, particularly for administration. A Health Care Financing Administration (HCFA) demonstration project may provide insights, but its limited number of predominantly small, rural, participating states, its tandem quality assurance system, and potentially confounding market variables may restrict the value of this project. We do not yet have the data to assess the impact of instituting case mix adjustment systems.

Regression-adjusted small area estimates of functional dependency in the noninstitutionalized American population age 65 and over.

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.

Adult day care regulation: "Déjà vu all over again"?

We investigate what aspects of adult day care are regulated by licensure and certification requirements, whether differences exist among centers according to their regulatory status, and the relationship between regulatory status and satisfaction. The data come from a national survey of adult day care center. We find that adult day care regulations are primarily structural in nature and that differences do exist among centers by regulatory status. Participants are very satisfied with the centers and their staff overall, especially at centers that are regulated; their satisfaction with milieu is less at regulated centers and with amenities is unaffected. Day care regulations have not been extended to the processes and outcomes of care as nursing home regulations recently have been. The choice that now faces policymakers is between increasing these regulations or relying on market mechanisms to protect day care participants.

Financial aspects of adult day care: national survey results.

Using data from a national survey of adult day care centers, it was found that a typical center had revenues of approximately $140,000 and expenses that were slightly higher. Most of the revenue was from Federal sources, with Medicaid being the largest single source. The median cost per participant day was $29.50, over one-half of which was attributable to labor expenses. To the extent that adult day care programs can better utilize their capacity, considerable savings could be made in cost per participant day.

A model for reducing the cost of care in VA medical centers that offer adult day health care.

One approach to providing cost-effective adult day health care (ADHC) services is to guide both the inputs to ADHC services and the provision of other services so that substitution for institutional services can realistically take place. This approach has been used in a randomized clinical trial to evaluate the medical efficacy and cost of ADHC in the Department of Veterans Affairs (DVA). This article describes the strategies that were used to improve the cost effectiveness of ADHC during the evaluation. Cost and use estimates were developed based on the best data available from the DVA and previous research on the cost for patients' use of ADHC, nursing home, hospital, and ambulatory care. A cost workshop was attended by the ADHC managers to develop plans for controlling costs. Plans were identified that increase the likelihood that ADHC can be shown to be less costly than customary care.