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The determination of each year's endowment payout, total spending, and transfers to or from reserves Is set up as an optimal smoothing rule problem. Stochastic laws of motion are formulated for total spending, operating income, changes in the balances for endowment and operating reserves, and the acquisition of new gifts to endowment. Parameters of the smoothing rules are obtained by making subjective tradeoffs among objectives such as the means and meansquare deviations of budget quantities and the probabilities that these quantities will exceed certain control limits. The model currently is being used to determine the endowment payout rate for Stanford University. [ABSTRACT FROM AUTHOR]

This paper formulates a demographic flow model that can be used to analyze the effects of university early-retirement policies on faculty appointment rates and rank and age distributions. In addition, it discusses a specific early-retirement plan designed to induce less productive older members of a faculty into voluntary withdrawal while offering significantly less encouragement to their more productive colleagues. The model is then used to examine the extent to which this plan is likely to achieve its intended results, namely an increase in the flow rate of new appointments, a reduction in the number of older faculty members in service, and a reduction in total personnel costs. Both short-run and equilibrium effects are analyzed with specific reference to the situation at Stanford University. [ABSTRACT FROM AUTHOR]

Five-year projections of university expense and income items are incorporated into a model requiring long-run financial equilibrium (LRFE) at the end of the planning period. LRFE means that both budget levels and growth rates are in balance. The "transition to equilibrium" model consists of a set of simultaneous linear equations that are solved for an estimate of the amount of budget base reductions needed to achieve LRFE five years later. The model was applied at Stanford University, the resulting $10.2 million budget adjustment target was accepted, and now (two years later) more than 85 percent of the needed changes have been implemented. [ABSTRACT FROM AUTHOR]

This article focuses on the use of large-scale simulation models for university planning and management. The paper begins with a general description of a cost simulation model (CSM), using a numerical example to show how it operates. In order to lower the costs of implementing and operating a CSM and to increase the stability of its parameters, it has been suggested that all data first be grouped into so-called discipline categories these typically consisting of several academic departments within a school or college.

This paper studies multistage mathematical programs with an arbitrary transient phase followed by an infinite stationary phase with linear constraints and objective. It presents conditions under which a derived linear program will determine an optimal solution to the infinite problem. These conditions are general and may be validated by simple algebraic tests (perhaps solving a finite linear program). No topological restrictions are placed on the model. [ABSTRACT FROM AUTHOR]

This paper develops a simple deterministic model that relates student admissions and enrollments to the final demand for educated students. It includes the, effects of drop-out rates and student-teacher ratios upon student enrollments and faculty staffing levels. Certain technological requirements are assumed known and given. These, as well as the laws of flow conservation and the relations between equilibrium enrollment levels and average flow rates, axe used to predict the effects of specific administrative policies and institutional controls at the campus level. [ABSTRACT FROM AUTHOR]

The problem faced by a single-product firm that must choose among alternative investments in capital equipment to meet a known demand for capacity in each discrete time period is formulated as a linear program. The formulation explicitly includes a transient set of investment opportunities which are available in early periods, as well as a stationary set which will become available in the near future. Also, no finite time horizon is placed upon the planning process. The approach taken to obtain the optimal solution to the infinite-horizon problem is to solve first a finite-horizon problem that includes a valuation of terminal capital stocks. The optimal solution to this problem is then used to construct a solution to the infinite-horizon problem that is identical to the finite-horizon solution in early periods. This construction is shown to be optimal for the infinite-horizon problem. [ABSTRACT FROM AUTHOR]

Purpose Most patients, providers, and payers make decisions about cancer hospitals without any objective data regarding quality or outcomes. We developed two online resources allowing users to search and compare timely data regarding hospital cancer surgery volumes. Methods Hospital cancer surgery volumes for all California hospitals were calculated using ICD-9 coded hospital discharge summary data. Cancer surgeries included (bladder, brain, breast, colon, esophagus, liver, lung, pancreas, prostate, rectum, and stomach) were selected on the basis of a rigorous literature review to confirm sufficient evidence of a positive association between volume and mortality. The literature could not identify threshold numbers of surgeries associated with better or worse outcomes. A multidisciplinary working group oversaw the project and ensured sound methodology. Results In California in 2014, about 60% of surgeries were performed at top-quintile--volume hospitals, but the per-hospital median numbers of surgeries for esophageal, pancreatic, stomach, liver, or bladder cancer surgeries were four or fewer. At least 670 patients received cancer surgery at hospitals that performed only one or two surgeries for a particular cancer type; 72% of those patients lived within 50 miles of a top-quintile--volume hospital. Conclusion There is clear potential for more readily available information about hospital volumes to help patient, providers, and payers choose cancer surgery hospitals. Our successful public reporting of hospital volumes in California represents an important first step toward making publicly available even more provider-specific data regarding cancer care quality, costs, and outcomes, so those data can inform decision-making and encourage quality improvement. [ABSTRACT FROM AUTHOR]

Objective: Some argue that health plans have minimal impacts on quality of care and that quality data collection should focus only on physician organizations. We investigate the relative impact of physician organizations and health plans on quality measures., Design: Statistical analysis of data on 9 Healthcare Effectiveness Data and Information Set (HEDIS) measures from 6 health plans and 159 provider organizations. We use regression analyses to examine the amount of variation in HEDIS measures accounted for by variation across provider organizations, and whether accounting for health plans explains additional variation. We also examine whether accounting for provider organizations explains away variation in HEDIS scores across health plans., Setting: Six health plans and 159 contracted provider groups in California., Main Outcome Measures: Nine HEDIS scores., Results: For all nine measures studied, variation across provider organizations explains much of the HEDIS score variation. But, after accounting for variation across providers, variation across plans statistically significantly explains additional variation. We also find statistically significant differences across health plans in HEDIS rates that are not substantially affected when we control for the provider organization that cared for the patient., Conclusions: On their face, these results suggest that plans can influence quality independent of the selection of physician organizations with which they contract, in contrast to hypotheses that plans are 'too far' from patients to have an influence. Continued attention to collecting plan-level data is warranted. Further work should address other possible sources of variations in HEDIS scores, such as variability in plan administrative databases.