Physician Incentive Management in University Hospitals: Inducing Efficient Behavior Through the Allocation of Research Facilities

The imperative to improve healthcare efficiency is now stronger than ever. Rapidly increasing healthcare demand and the prospect of healthcare cost exploding require that measures be taken to make healthcare organizations become more efficiency-aware. Alignment of organizational interests is therefore important. One of the main hurdles to overcome is the provision of the right incentives to healthcare workers, in particular physicians. In this research we investigate the incentive system for physicians in university hospitals. We present an inquiry held in a large university hospital in the Netherlands and show that non-financial incentives receive significantly more support among physicians than financial incentives. Over 95 percent of the physicians indicated they derive more work stimulus from research possibilities or scientific status than from wage. Over 80 percent of the physicians also indicated they prefer to be able to do more research. We therefore identified a broad class of non-financial incentives aimed at physicians in university hospitals: research facilities. The main tradeoff in using research facilities within an incentive system is between efficient resource utilization and inducement effects. This thesis constructs a principal-multi-agent model where agents engage in both care and research and which includes heterogeneity and private information. We study how research facilities incentives can be used to improve hospital performance if the current wage system is left intact. We show that research facilities are optimally used as incentives for both care and research activities, and that the hospital offers different contracts depending on physician ability and valuation. Moreover, if physicians need to reveal their valuations for research facilities, the hospital finds it optimal to allow physicians to make a rent. We discuss some implications of extending the theoretical results to practice

Entanglement, Mixedness, and Spin-Flip Symmetry in Multiple-Qubit Systems

A relationship between a recently introduced multipartite entanglement measure, state mixedness, and spin-flip symmetry is established for any finite number of qubits. It is also shown that, within those classes of states invariant under the spin-flip transformation, there is a complementarity relation between multipartite entanglement and mixedness. A number of example classes of multiple-qubit systems are studied in light of this relationship.Comment: To appear in Physical Review A; submitted 14 May 200

Hamiltonian BRST-anti-BRST Theory

The hamiltonian BRST-anti-BRST theory is developed in the general case of arbitrary reducible first class systems. This is done by extending the methods of homological perturbation theory, originally based on the use of a single resolution, to the case of a biresolution. The BRST and the anti-BRST generators are shown to exist. The respective links with the ordinary BRST formulation and with the $sp(2)$-covariant formalism are also established.Comment: 34 pages, Latex fil

Entanglement study of the 1D Ising model with Added Dzyaloshinsky-Moriya interaction

We have studied occurrence of quantum phase transition in the one-dimensional spin-1/2 Ising model with added Dzyaloshinsky-Moriya (DM) interaction from bi- partite and multi-partite entanglement point of view. Using exact numerical solutions, we are able to study such systems up to 24 qubits. The minimum of the entanglement ratio R $\equiv$ \tau 2/\tau 1 < 1, as a novel estimator of QPT, has been used to detect QPT and our calculations have shown that its minimum took place at the critical point. We have also shown both the global-entanglement (GE) and multipartite entanglement (ME) are maximal at the critical point for the Ising chain with added DM interaction. Using matrix product state approach, we have calculated the tangle and concurrence of the model and it is able to capture and confirm our numerical experiment result. Lack of inversion symmetry in the presence of DM interaction stimulated us to study entanglement of three qubits in symmetric and antisymmetric way which brings some surprising results.Comment: 18 pages, 9 figures, submitte

Entanglement Sharing in the Two-Atom Tavis-Cummings Model

Individual members of an ensemble of identical systems coupled to a common probe can become entangled with one another, even when they do not interact directly. We investigate how this type of multipartite entanglement is generated in the context of a system consisting of two two-level atoms resonantly coupled to a single mode of the electromagnetic field. The dynamical evolution is studied in terms of the entanglements in the different bipartite partitions of the system, as quantified by the I-tangle. We also propose a generalization of the so-called residual tangle that quantifies the inherent three-body correlations in our tripartite system. This enables us to completely characterize the phenomenon of entanglement sharing in the case of the two-atom Tavis-Cummings model, a system of both theoretical and experimental interest.Comment: 11 pages, 4 figures, submitted to PRA, v3 contains corrections to small error

Impact of extreme weather events frequency and intensity in shaping phytoplankton communities

Lake habitats and communities can often be correlated with general morphometric and geographic characteristics such as depth, latitude, altitude, or watershed area. Further, communities are typically correlated with average environmental conditions such as seasonal temperature and nutrient levels. The frequency and intensity of extreme weather events (rain and wind) are typically not encompassed by average environmental descriptors, yet, can modify the physical habitats of lakes, significantly influencing phytoplankton growth and survival. We tested the hypothesis that lakes with a higher frequency and intensity of extreme weather events have a functionally different phytoplankton assemblage from lakes with a lower frequency of extreme weather events. We compiled long-term (mean = 20±13 years, range 0.6-44 years) phytoplankton datasets for 22 lakes across a wide gradient of altitude, latitude, depth, and trophic state. We classified the phytoplankton genera into morpho-functional groups and C-S-R strategists, and compared among lake phytoplankton assemblages’ characteristics across the gradient of wind and rain conditions experienced by the lakes. We discuss how the frequency of extreme weather events can affect phytoplankton functional groups, the dominance of differing life history strategies and ultimately community structure. The frequency and intensity of extreme events is expected to increase with climate change, with the potential to drive shifts in phytoplankton composition

Separability and entanglement in 2x3xN composite quantum systems

The separability and entanglement of quantum mixed states in \Cb^2 \otimes \Cb^3 \otimes \Cb^N composite quantum systems are investigated. It is shown that all quantum states $\rho$ with positive partial transposes and rank $r(\rho)\leq N$ are separable.Comment: Latex, 15 page

A global dataset on weather, lake physics, and phytoplankton dynamics

We compiled data from over 30 lakes across the globe to address how storms influence thermal structure and phytoplankton community dynamics mediated by lake conditions and functional traits. In addition to (generally) fortnightly phytoplankton samples (mean ± SD temporal coverage across all lakes = 20 ± 13 years), the dataset includes limnological variables from standard long-term monitoring programs (24 ± 15 years coverage), daily weather observations (16 ± 10 years coverage) and, when available, high-frequency lake water temperature and water chemistry profiles (12 ± 7 years coverage). All data have been standardized to similar formats and include complete metadata. We used the dataset to develop an R-package (“algaeClassify”), which assigns phytoplankton genus/species information to multiple functional trait groups, and here we provide a summary of ongoing research using the dataset to investigate: 1) the influence of storm events on seasonal phytoplankton succession, 2) the impact of storms on lake thermal structure, and 3) whether lake phytoplankton communities are shaped by long-term patterns in disturbance frequency and intensity. We give an overview on how to access these data, and we further highlight the opportunities the dataset provides for asking both basic and applied questions in limnology, ecology, climate change, and lake management