How one hospital broke its inflation fever

The Johns Hopkins Hospital has demonstrated that hospital costs can be decreased without governmental intervention (controls). From 1975 to 1978, the hospital inflation rate was cut by half. One key factor, according to Solomon, was a move to decentralize management which was accompanied by a detailed system for monitoring costs. Also instrumental were administration's consistent reminders to physicians and managers about keeping costs down. The hospital was reorganized from a system of clinical departments that behaved, says Solomon, like "fiefdoms" into 14 autonomous departments that function under their own budgets. Each department controls about 85% of its costs (up from 30%), and is set up to function "like a small business." A breakdown of where cost reductions took place shows a savings of $5 million in overhead and $1.5 million in malpractice claims (Hopkins self-insured). Individual departments have also achieved some dramatic reductions: the Department of Medicine decreased the number of laboratory tests ordered; and the Department of Gynecology and Obstetrics built a new facility with fewer beds than the old one.     

Utilization and productivity of the Duke physician's associate

The objectives of this study were as follows: (1) Formulate a theoretical model of the typical medical practice as a system for producing medical care, with particular attention to the role of middle-level health workers such as graduates of Duke University's Physician's Associate Program. (2) Develop a methodology for collecting data necessary to estimate the relevant parameters in the model, and to describe current patterns of utilization of Duke PA's. (3) Draw substantive conclusions, insofar as the model and data collection methodology permit, about the actual and potential productivity of Duke PA's.As of October 1971 Duke University had graduated 68 PA's from its Physician's Associate Program. Of these, 34 are employed as assistants in family practice or general medicine in a variety of private and institutional settings. Data were collected on eleven of these 34 PA's. No attempt was made to study the other 34 graduates engaged in clinical specialties, administration, or other functions. Neither was any attempt made to collect data on or draw inferences about the utilization and productivity of graduates of any other program such as the MEDEX Program.⁴     

Investment planning for irrigation development projects

This paper considers the problem of choosing among the technologies available for irrigation by tubewells to obtain an investment plan which maximizes the net agricultural benefits from a proposed project in a developing country. Cost and benefit relationships are derived and incorporated into a mathematical model which is solved using a modification of the dynamic programming procedure for solving the knapsack problem. The optimal schedule is seen to favor small capacity wells, drilled by indigenous methods, with supplementary water distribution systems.     

Portfolio choice and equilibrium in capital markets with safety-first investors

This paper develops optimal portfolio choice and market equilibrium when investors behave according to a generalized lexicographic safety-first rule. We show that the mutual fund separation property holds for the optimal portfolio choice of a risk-averse safety-first investor. We also derive an explicit valuation formula for the equilibrium value of assets. The valuation formula reduces to the well-known two-parameter capital asset pricing model (CAPM) when investors approximate the tail of the portfolio distribution using Tchebychev's inequality or when the assets have normal or stable Paretian distributions. This shows the robustness of the CAPM to safety-first investors under traditional distributional assumptions. In addition, we indicate how additional information about the portfolio distribution can be incorporated to the safety-first valuation formula to obtain alternative empirically testable models.     

Hypothesis testing based on goodness-of-fit in the moving average time series model

Small sample properties of t-tests are compared with those of tests based on relative goodness- of-fit in the context of the first order moving average time series model. Monte Carlo experiments reported in the paper suggest that the actual size of these t-tests greatly exceeds theoretical large sample significance levels, while conformity of goodness-of-fit statistics to the appropriate chi-square or F-distributions is much closer. The evidence presented suggests that practitioners are well advised to employ goodness-of-fit tests as a check on results of t-tests particularly when the latter indicate ‘significance’.