title: S.P.I.C.E.--a model for reducing the incidence and costs of occupationally entitled claims.
abstract: A review of national statistics and recent studies strongly suggests that current administrative and medical systems, when applied to managing workers' compensation claims and other disability-related benefit programs, are often ineffective and costly, and can even promote disability. With numerous medical and occupational health articles published daily, it is difficult to develop practical strategies for daily management of disability claims that make use of current information. It is the authors' view that a comprehensive, dynamic model for management exists within the military's "Forward Treatment" methodology. This model, originally published in The Journal of Occupational Rehabilitation, has been expanded to include those methods demonstrated in literature to both reduce claims and deal with them in an efficient, fair, and timely manner. Because military personnel and employed individuals are similarly entitled, the military's proven model can be effective in reducing claim rates and costs associated with workers' compensation as well as short- and long-term disability programs. The model, given the acronym S.P. I.C.E., includes five components: Simplicity, Proximity, Immediacy, Centrality, and Expectancy.
authors.affiliation: Labor Commission, State of Utah, Salt Lake City, 84114-6610, USA.
authors.forename: A L
authors.initials: AL
authors.lastname: Colledge
authors.forename: H I
authors.initials: HI
authors.lastname: Johnson
mesh_terms: D004185:Disability Evaluation; D005260:Female; D017048:Health Care Costs; D006801:Humans; D015994:Incidence; D008297:Male; D018803:Models, Economic; D009784:Occupational Diseases / Q000191:economics* / Q000453:epidemiology / Q000517:prevention & control* / Q000534:rehabilitation; D016272:Occupational Health; D010810:Physical and Rehabilitation Medicine / Q000191:economics* / Q000379:methods; D018570:Risk Assessment; D014481:United States; D014942:Workers' Compensation / Q000191:economics* / Q000706:statistics & numerical data*