Healthcare

We develop a simple theoretical model of the allocation of public biomedical research expenditure, and present some empirical evidence about the determinants of this allocation. The structure of expenditure should depend on the relative costs as well as the relative benefits of different kinds of research. Analysts of technical change typically have data on neither of these, but the measures of disease burden we use are indicative of the benefit of achieving advances against different diseases.

Case studies of a number of specific drugs have shown that these drugs reduced the demand for hospital care and, in some cases, led to decreases in mortality. For example, according to the Boston Consulting Group Inc., operations for peptic ulcers decreased from 97,000 in 1977, when H2 antagonists were introduced, to 19,000 in 1987; this is estimated to have saved $224 million in annual medical costs. The recent Scandinavian Simvastatin Survival Study indicated that giving the drug simvastatin to heart patients reduced their hospital admissions by a third during five years of treatment.

This paper presents an econometric analysis of the effect of changes in the quantity and type of pharmaceuticals prescribed by physicians in outpatient visits on rates of hospitalization, surgical procedure, mortality, and related variables. It examines the statistical relationship across diseases between changes in outpatient pharmaceutical utilization and changes in inpatient care utilization and mortality during the period 1980-92.

We consider single-server loss systems with exponential service times and non-stationary Poisson input. We prove that if the arrival rate is given by a periodic function, the proportion of lost customers is convex increasing in the amplitude.

Many queueing situations such as computer, communications and emergency systems have the feature that customers may require service from several servers at the same time. They may thus be delayed until the required number of servers is avialable and servers may be idle when customers are waiting. We consider general server-completion-time distributions and derive approximation methods for the computation of the steady-state distribution of the number of customers in queue as well as the moments of the waiting-time distribution. Extensive computational results are reported.

Service systems’ behavior can be affected by multiple factors. In the case of intensive care units (ICUs), which admit patients from four primary loci (the emergency department (ED), scheduled patients, planned transfers from other ICUs, and unplanned transfers), it is known that admission rates of some patients decrease as occupancy increases. It is also known that, for at least some conditions, ICU admission is not just a function of patients’ illness, and that a significant proportion of the variation in ICU admission rates is due to hospital, not patient, factors.

Problem definition: In many service systems, individual server’s workload can have a substantial impact on service time and quality. Such effects are particularly important in healthcare systems which often operate under resource and time constraints. In much of the literature, this has been primarily considered at the system level rather than the individual level. In this study, we investigate this relationship in the context of cardiac surgery, i.e., how surgery duration and patient outcomes are affected by individual surgeon’s daily workload.