Objective: To provide a model for prospective budgeting for home care that is plausible, coherent, flexible, and sufficiently tractable that it can serve as a template for practical decision making and to clarify what would be the data requirements and statistical framework to calibrate the model.Methods: Methods used are standard risk-neutral expected value theory, cost benefit analysis, and the conditional logistic probability model.Results: A simple but effective prospective budgeting model that provides analytic scaffolding for a practical decision support system for home care case managers, consultants, and program evaluators that can improve program equity, efficiency, and effectiveness.Discussion: The author criticizes the well-known Titration Budgeting Model of Weissert, Chernew, and Hirth in terms of its logical and operational problems but then goes on to develop a framework within which the goals of the titration model can be met and home care resources can be more efficiently allocated.
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