Healthcare

BACKGROUND: Delays for appointments are prevalent, resulting in patient dissatisfaction, higher costs, and possible adverse clinical consequences. A "just-in-time" approach to patient scheduling, called advanced access, has been effective in reducing delays in multiple clinical settings. Offering most patients appointments on the same day requires achieving an appropriate balance between supply of and demand for appointments, but no methods have been previously proposed to determine what this balance should be.

In this note we present algorithms that compute, exactly or approximately, time-dependent waiting time tail probabilities and the time-dependent expected waiting time in M(t)/M/s(t) queuing systems.

Hospital diagnostic facilities, such as magentic resonance imaging centers, typically provide service to several diverse patient groups: outpatients, who are scheduled in advance; inpatients, whose demands are generated randomly during the day; and emergency patients, who must be served as soon as posssible. Our analysis focuses on two inter-related tasks: designing the outpatient appoitnment schedule, and establishing dynamic priority rules for admitting patients into service.

Objectives: Significant variation in emergency department (ED) patient arrival rates necessitates the adjustment of staffing patterns to optimize the timely care of patients. This study evaluated the effectiveness of a queueing model in identifying provider staffing patterns to reduce the fraction of patients who leave without being seen.

America's health care system is the envy of the world, but it faces serious challenges. The costs of care are rising rapidly, the number of uninsured Americans is at an all-time high, and public dissatisfaction is steadily increasing. How can we preserve the strengths of our current system while correcting its weaknesses? Three of American's leading health-care scholars answer that question in Healthy, Wealthy, and Wise. Poorly conceived federal tax policies, insurance regulations, and barriers to entry have distorted health-care markets and inhibited competition.

Several econometric studies have concluded that technical progress embodied in equipment is a major source of manufacturing productivity growth. Other research has suggested that, over the long run, growth in the U.S. economy's 'health output' has been at least as large as the growth in non-health goods and services. One important input in the production of health pharmaceuticals is even more R&D- intensive than equipment.

A patent only protects an innovator from others producing the same product, but it does not protect him from others producing better products under new patents. Therefore, one may divide up the source of competition facing an innovator into within-patent competition, which results from production of the same product, and betweenpatent competition, which results from production of products on other patents.

There is a large body of work that documents a strong, positive correlation between education and measures of health, but little is known about the mechanisms by which education might affect health. One possibility is that more educated individuals are more likely to adopt new medical technologies. We investigate this theory by asking whether more educated people are more likely to use newer drugs, while controlling for other individual characteristics, such as income and insurance status.

We hypothesize that pharmaceutical-embodied technical progress increases per capita output via its effect on labor supply (the employment rate and hours worked per employed person). We examine the effect of changes in both the average quantity and average vintage (FDA approval year) of drugs consumed on labor supply, using longitudinal, condition-level data. The estimates indicate that conditions for which there were above-average increases in utilization of prescriptions during 1996-1998 tended to have above-average reductions in the probability of missed work days.