Journal of Mental Health Policy and Economics最新文献

Background: There is now general agreement that a comprehensive psychiatric service can operate with the minimum use of in-patient facilities. Consequently, the emphasis in most European countries is on reducing the number of inpatient beds and expanding the range of community care facilities, including day hospital services, available to mentally ill patients. Decision-making with respect to placement is now even more important given the changes currently taking place on the supply side.Method: The study examines the factors that influence placement decision-making between inpatient care and day hospital care in one Health Board in Ireland. Placement was examined over a 9 month period for all patients presenting for treatment in one particular area with a population of 39000 people. Patients were not randomized between the two settings due to ethical concerns about the randomization process. The issue of placement is analysed using a logit estimation procedure.Results: The results suggest that two variables have a significant affect on placement for the population under review: whether the patient is accompanied at the time of admission and the domicile of the patient.Conclusions: Greater flexibility with respect to the opening hours of day hospital facilities, linked to improved transport facilities, together with further analysis on the process of admission to hospital, particularly the dynamics of the interaction between providers, patients, and accompanying persons, may improve placement decision-making for mentally ill patients. Copyright © 1999 John Wiley & Sons, Ltd.

Objective: To identify the determinants of level and intensity of psychosocial treatment activity among staff who deliver services to the severely and mentally ill.Methods: The study sample consisted of 769 treatment providers working in 77 units in 29 VA mental health facilities. Level of psychosocial care was measured as the number of patient contacts and total hours spent in psychosocial care over a 1 week period. Intensity of psychosocial care was measured as the average time per patient contact. We used hierarchical linear modeling (HLM) to examine the association between level and intensity of care and three categories of determinants—individual provider attributes, work characteristics and treatment setting characteristics.Results: Providers' occupation is related to both the level and intensity of care. Providers with administrative responsibilities also have fewer patient contacts and lower intensity of such contacts. Providers who perceived their pay and benefits more positively had fewer patient contacts and less intensive patient contacts. Positive relationships with patients and providers were also associated with greater levels and intensity of psychosocial treatment activity among providers. Finally, statistically significant differences in psychosocial treatment activity among units were identified although such differences are not attributable to unit size, patient cohort severity or unit workload.Conclusions: Level and intensity of psychosocial treatment activity vary systematically by individual attributes of providers, characteristics of the work they perform and attributes of the treatment setting. These factors may provide the basis for designing interventions to modify provider behavior in a manner consistent with emerging financial pressures and treatment modalities for the seriously mentally ill. Copyright © 1999 John Wiley & Sons, Ltd.

Background: The costs of substance abuse in the USA are enormous and varied. Seldom are they comprehensively assessed. A new study jointly published by the National Institute on Drug Abuse (NIDA) and the National Institute on Alcoholism and Alcohol Abuse (NIAAA) has done just this. Aims: Researchers for the economic cost of alcohol and drug abuse in the United States, 1992 used systematic cost-of-illness measurement methods to evaluate the burden drug abuse and dependency place on the US economy. This burden includes widespread disability, morbidity, premature death, and diversion of economic resources to drug-related activities. Conceptualizing, identifying, and measuring this burden was a major undertaking; the report describes the methods in detail. Method: Costs are measured as the value of resources used (direct costs) or lost during a one year period. As adopted here, the human capital approach estimates an individual’s value to society in terms of his or her production potential. The value of future lost earnings is discounted to present time. Finally, the study adopts a societal point of view that is consistent with the recommendations of the Panel on Cost-Effectiveness in Health and Medicine that was convened by the U.S. Public Health Service in 1993. Therefore, this study considers all health and non-health outcomes and costs created by drug abuse and dependency for the entire population. Results: For drug abuse, the annual cost in 1992 is estimated at $98 billion. By 1995, this estimate rose to $110 billion after adjusting for inflation and population change. For 1988, a previous and similar study estimated a cost of $58 billion. The distribution of costs is of particular concern.

Background: Algorithms describe clinical choices to treat a specific disorder. To many, algorithms serve as important tools helping practitioners make informed choices about how best to treat patients, achieving better outcomes more quickly and at a lower cost. Appearing as flow charts and decision trees, algorithms are developed during consensus conferences by leading experts who explore the latest scientific evidence to describe optimal treatment for each disorder. Despite a focus on ‘optimal’ care, there has been little discussion in the literature concerning how costs should be defined and measured in the context of algorithm-based practices. Aims of the study: This paper describes the strategy to measure costs for the Texas Medication Algorithm project, or TMAP. Launched by the Texas Department of Mental Health and Mental Retardation and the University of Texas Southwestern Medical Center at Dallas, this multi-site study investigates outcomes and costs of medication algorithms for bipolar disorder, schizophrenia and depression. Methods: To balance costs with outcomes, we turned to cost-effectiveness analyses as a framework to define and measure costs. Alternative strategies (cost–benefit, cost–utility, cost-of-illness) were inappropriate since algorithms are not intended to guide resource allocation across different diseases or between health- and non-health-related commodities. ‘Costs’ are operationalized consistent with the framework presented by the United States Public Health Service Panel on Cost Effectiveness in Medicine.

Patient specific costs are calculated by multiplying patient units of use by a unit cost, and summing over all service categories. Outpatient services are counted by procedures. Inpatient services are counted by days classified into diagnosis groups. Utilization information is derived from patient self-reports, medical charts and administrative file sources. Unit costs are computed by payer source. Finally, hierarchical modeling is used to describe how costs and effectiveness differ between algorithm-based and treatment-as-usual practices. Discussion: Cost estimates of algorithm-based practices should (i) measure opportunity costs, (ii) employ structured data collection methods, (iii) profile patient use of both mental health and general medical providers and (iv) reflect costs by payer status in different economic environments. Implication for health care provision and use: Algorithms may help guide clinicians, their patients and third party payers to rely on the latest scientific evidence to make treatment choices that balance costs with outcomes. Implication for health policies: Planners should consider consumer wants and economic costs when developing and testing new clinical algorithms. Implications for further research: Future studies may wish to consider similar methods to estimate costs in evaluating algorithm-based practices. Copyright © 1999 John Wiley & Sons, Ltd.