Participation in Universal Prevention Programs

We analyze the decision to participate in community-based universal prevention programs through the framework of prospect theory, with family functionality, and related risk status, providing the reference point. We find that participation probability depends on the relative ratios of the weighting and valuation functions. Using data from the Strengthening Families Program and the Washington Healthy Youth Survey, we empirically test the implications of our model. We find that family functionality affects the participation decision in complex and, in some cases, non-linear ways. We discuss the implication of these findings for cost-effectiveness analysis, and suggest directions for further research.Prospect Theory, Treatment Outcomes, Risk Status

Detecting Selection Bias in Community Disseminations of Universal Family-Based Prevention Programs

The goals of the present study were to demonstrate a method for examining selection bias in large-scale implementations of community-based family skills programs, and to explore the nature of selection bias in one such implementation. We used evaluation data from a statewide dissemination of a popular substance abuse prevention program (N programs = 42; N youth = 294). The program’s evaluation measures were designed to match publicly available data on risk and protective factor scales collected in the state’s schools, which enabled us to construct a comparison sample of non-participants (N = 20,608). We then examined the risk status of adolescents in both groups to determine whether risk and protective factor scores were related to the probability of program participation. Participation was predicted by both demographics and risk and protective factor scores. Among families with younger adolescents, program attendance was associated with lower risk; among families with older adolescents, participation was associated with both higher risk (on parental management skills) and lower risk (on substance use). Selection effects must be identified and corrected for in order to calculate valid estimates of program benefits, but in community-based disseminations, the necessary supplemental comparison sample is difficult to obtain. The evaluation design and analytic approach described here can be used in program evaluations of real-world, “bottom-up” dissemination efforts to identify who attends a program, which in turn can help to inform recruitment strategies, to pinpoint possible selection influences on measured program outcomes, and to refine estimates of program costs and benefits.repeated auction; selectivity; prevention program; community-based implementation; program evaluation

Cost-effectiveness of a specialized oral nutritional supplementation for malnourished older adult patients in Spain

Malnutrition has been related to prolonged hospital stays, and to increases in readmission and mortality rates. In the NOURISH (Nutrition effect On Unplanned Readmissions and Survival in Hospitalized patients) study, administering a high protein oral nutritional supplement (ONS) containing beta-hydroxy-beta-methylbutyrate (HP-HMB) to hospitalised older adult patients led to a significant improvement in survival compared with a placebo treatment. The aim of this study was to determine whether HP-HMB would be cost-effective in Spain. We performed a cost-effectiveness analysis from the perspective of the Spanish National Health System using time horizons of 90 days, 180 days, 1 year, 2 years, 5 years and lifetime. The difference in cost between patients treated with HP-HMB and placebo was €332.75. With the 90 days time horizon, the difference in life years gained (LYG) between both groups was 0.0096, resulting in an incremental cost-effectiveness ratio (ICER) of €34, 700.62/LYG.With time horizons of 180 days, 1 year, 2 years, 5 years and lifetime, the respective ICERs were €13, 711.68, €3377.96, €2253.32, €1127.34 and €563.84/LYG. This analysis suggests that administering HP-HMB to older adult patients admitted to Spanish hospitals during hospitalisation and after discharge could be a cost-effective intervention that would improve survival with a reduced marginal cost

第964回千葉医学会例会・第31回麻酔科例会

BACKGROUND:Disease-associated malnutrition has been identified as a prevalent condition, particularly for the elderly, which has often been overlooked in the U.S. healthcare system. The state-level burden of community-based disease-associated malnutrition is unknown and there have been limited efforts by state policy makers to identify, quantify, and address malnutrition. The objective of this study was to examine and quantify the state-level economic burden of disease-associated malnutrition. METHODS:Direct medical costs of disease-associated malnutrition were calculated for 8 diseases: Stroke, Chronic Obstructive Pulmonary Disease, Coronary Heart Failure, Breast Cancer, Dementia, Musculoskeletal Disorders, Depression, and Colorectal Cancer. National disease and malnutrition prevalence rates were estimated for subgroups defined by age, race, and sex using the National Health and Nutrition Examination Survey and the National Health Interview Survey. State prevalence of disease-associated malnutrition was estimated by combining national prevalence estimates with states' demographic data from the U.S. Census. Direct medical cost for each state was estimated as the increased expenditures incurred as a result of malnutrition. PRINCIPAL FINDINGS:Direct medical costs attributable to disease-associated malnutrition vary among states from an annual cost of $36 per capita in Utah to$65 per capita in Washington, D.C. Nationally the annual cost of disease-associated malnutrition is over $15.5 billion. The elderly bear a disproportionate share of this cost on both the state and national level. CONCLUSIONS:Additional action is needed to reduce the economic impact of disease-associated malnutrition, particularly at the state level. Nutrition may be a cost-effective way to help address high health care costs

Topics in health economics prevention, addiction and fraud

These three articles use empirical data to examine important questions regarding public health policy. The first article, Detecting Selection Effects in Community Implementations of Family-Based Substance Abuse Prevention Programs discusses the implications of self-selection in to universal prevention programs and implements an innovative statistical procedure to identify such selection in Washington State for the Strengthening Families Program for Parents and Youth. The second article, Unintended Consequences: Medicare s Impact on the Diagnosis of Non-Enrollees models the incentive for fraudulent diagnosis when provider reimbursement is based on diagnosis for a portion of the population. Importantly, I find evidence that providers which treat a large portion of Medicare patients are more likely to over diagnose (upcode) both Medicare and non-Medicare patients. The third article examines the role of peer perceptions in young people s desire to smoke. Using data from the Washington State Healthy Youth Survey, I show that the youth s expectation of social rewards is a significant predictor of smoking behavior, and interacts with tobacco control policies

Participation in universal prevention programmes

We analyse family decisions to participate in community-based universal substance-abuse prevention programmes through the framework of expected utility theory. Family functioning, which has been shown to be a good indicator of child risk for substance abuse, provides a useful reference point for family decision making. Our results show that well-functioning families (with children at low risk for substance use) should have the lowest incentive to participate, but that high-risk families may also opt out of prevention programmes. For programmes that are most effective for high-risk youth, this could be a problem. Using data from the Strengthening Families Programme (SFP) and the Washington Healthy Youth Survey (HYS), we empirically test the implications of our model and find that at least for one measure of family functioning those families with children most likely to be at risk for substance use are opting out of the programme

Detecting Selection Effects in Community Implementations of Family-Based Substance Abuse Prevention Programs

To calculate valid estimates of the costs and benefits of substance abuse prevention programs, selection effects must be identified and corrected. A supplemental comparison sample is typically used for this purpose, but in community-based program implementations, such a sample is often not available. We present an evaluation design and analytic approach that can be used in program evaluations of real-world implementations to identify selection effects, which in turn can help inform recruitment strategies, pinpoint possible selection influences on measured program outcomes, and refine estimates of program costs and benefits. We illustrate our approach with data from a multisite implementation of a popular substance abuse prevention program. Our results indicate that the program's participants differed significantly from the population at large

Burden of Direct Medical Expenditures related to Malnutrition by Disease (Million Dollars).

<p>Monte Carlo Simulation Confidence Intervals (90%) in brackets.<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0161833#t002fn001" target="_blank">¹</a></p