Algorithms for Resource Allocation of Substance Abuse Prevention Funds Based on the Estimated Need: A Case Study on State of Florida—Part 1
| Autor: | Leslie Wurster, Sehwan Kim, Nancy Hepler, Charles Williams |
|---|---|
| Rok vydání: | 1998 |
| Předmět: |
medicine.medical_specialty
Health (social science) Index (economics) Substance-Related Disorders State Health Plans Medicine (miscellaneous) Substance abuse prevention medicine Humans Set (psychology) Health Services Needs and Demand Health Care Rationing business.industry Public health Public Health Environmental and Occupational Health General Medicine medicine.disease Mental health United States Weighting Substance abuse Alcoholism Psychiatry and Mental health Models Economic Florida Resource allocation business Algorithm Algorithms |
| Zdroj: | Journal of Drug Education. 28:87-106 |
| ISSN: | 1541-4159 0047-2379 |
| DOI: | 10.2190/wble-26al-v9xt-75te |
| Popis: | The purposes of Parts 1–3 of this article is to develop a framework for county-based prevention resource allocation algorithms based on the aggregated need for substance abuse prevention services estimated at the county level. The development of these algorithms is founded upon two databases: statewide student drug survey and a set of social indicators routinely collected and published by various agencies of the state of Florida. The resource allocation models are devised by developing several indices of prevention needs that are conceptualized in terms of: 1) county-based composite drug use index (COMDRUG), 2) the definitions of prevention target populations as envisioned by the Institute of Medicine (IOM), 3) composite risk-factor index score, and 4) a set of social indicators that are empirically related to COMDRUG observed at the county level. The first three models are based on the prevention needs estimated from the statewide student survey on substance abuse. The social indicator model, however, is presented as an alternative resource allocation model which may be used in lieu of or in the absence of statewide survey. The resource allocation algorithms found on these four conceptualizations are thought to be more equitable and appropriate to the prevention needs of various communities than may be contrived otherwise. Due to a significant amount of information leading to the development of these models, Part 1 of this series is devoted to the following three topics: 1) sampling method used, 2) poststratification weighting methods used to estimate county-based COMDRUG, and 3) the development of resource allocation models based on COMDRUG and the IOM definitions of prevention target populations. |
| Databáze: | OpenAIRE |
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