We examine the effects of two important types of medical innovation—diagnostic imaging innovation and pharmaceutical innovation—and cancer incidence rates on U.S. cancer mortality rates during the period 1996–2006. The outcome measure we use is not subject to lead-time bias, and our measures of medical innovation are based on extensive data on treatments given to large numbers of patients with different types of cancer.
A previous study used aggregate (region-level) data to investigate whether home health care serves as a substitute for inpatient hospital care, and concluded that “there is no evidence that services provided at home replace hospital services.” However, that study was based on a cross-section of regions observed at a single point of time, and did not control for unobserved regional heterogeneity.
Previous investigators argued that increasing 5-year survival for cancer patients should not be taken as evidence of improved prevention, screening, or therapy, because they found little correlation between the change in 5-year survival for a specific tumor and the change in tumor-related mortality. However, they did not control for the change in incidence, which influences mortality and is correlated with 5-year survival. The purpose of this study was to reexamine the question of whether increasing 5-year survival rates constitute evidence of success against cancer.
Although there is a good deal of speculation surrounding the role of pharmaceutical innovation in late 20th century mortality improvements in the United States, there is little empirical evidence on the topic and there remains a good deal of doubt regarding whether pharmaceuticals matter at all for mortality.
Timely access to care is a key component of high quality health care. Yet, patient delays are prevalent throughout the health-care system resulting in dissatisfaction and adverse clinical consequences for patients as well as potentially higher costs and wasted capacity for providers. For this reason, the Institute of Medicine has identified "timeliness" as one of the six keys in "aims for improvement" in its health-care quality initiative.
We study scheduling of multimedia traffic on the downlink of a wireless communication system. We examine a scenario where multimedia packets are associated with strict deadlines and are equivalent to lost packets if they arrive after their associated deadlines. Lost packets result in degradation of playout quality at the receiver, which is quantified in terms of the "distortion cost" associated with each packet. Our goal is to design a scheduler which minimizes the aggregate distortion cost over all receivers. We study the scheduling problem in a dynamic programming (DP) framework.
This work examines the impact of discharge decisions under uncertainty in a capacity-constrained high risk setting: the intensive care unit (ICU). New arrivals to an ICU are typically very high priority patients and, should the ICU be full upon their arrival, discharging a patient currently residing in the ICU may be required to accommodate a newly admitted patient. Patients so discharged risk physiologic deterioration which might ultimately require readmission; models of these risks are currently unavailable to providers.
Price discrimination is an extremely common type of pricing strategy engaged in by virtually every business with some discretionary pricing power. The issue of whether price discrimination reduces or increases social welfare has been considered by economists since at least 1920. At that time, it was demonstrated that, under certain (restrictive) conditions, price discrimination will reduce social welfare.