Community Pharmacy: an untapped patient data resource

As community pharmacy services become more patient centred they will be increasingly reliant on access to good quality patient information. This paper describes how the information which is currently available in community pharmacies can be used to enhance service delivery and patient care. With integration of community pharmacy and medical practice records on the horizon the opportunities this will provide are also considered. The community pharmacy held patient medication record, which is the central information repository, has been used to identify non-adherence, to prompt the pharmacist to clinically review prescriptions, identify patients for additional services and to identify those patients at greater risk of adverse drug events. Whilst active recording of patient consultations for treatment over the counter may improve the quality of consultations and information held, the lost benefits of anonymity afforded by community pharmacies needs to be considered. Recording of pharmacy staff activities enables workload to be monitored, remuneration to be justified and critical incidents to be learned from but is not routine practice. Centralisation of records between community pharmacies enables practices to be compared and consistent problems to be identified. By integrating pharmacy and medical practice records, patient behaviour with respect to medicines can be more closely monitored and should prevent duplication of effort. When using patient information stored in a community pharmacy it is however important to consider the reason why information was recorded in the first instance and whether it is appropriate to use it for a different purpose without additional patient consent. Community pharmacies currently have access to large amounts of information which if stored and used appropriately can significantly enhance the quality of provided services and patient care. Integrating records increases opportunities to enhance patient care yet further. Whilst community pharmacies have significant amounts of information available to them this is frequently untapped

Intrinsic Volumes of Random Cubical Complexes

Intrinsic volumes, which generalize both Euler characteristic and Lebesgue volume, are important properties of $d$-dimensional sets. A random cubical complex is a union of unit cubes, each with vertices on a regular cubic lattice, constructed according to some probability model. We analyze and give exact polynomial formulae, dependent on a probability, for the expected value and variance of the intrinsic volumes of several models of random cubical complexes. We then prove a central limit theorem for these intrinsic volumes. For our primary model, we also prove an interleaving theorem for the zeros of the expected-value polynomials. The intrinsic volumes of cubical complexes are useful for understanding the shape of random $d$-dimensional sets and for characterizing noise in applications.Comment: 17 pages with 7 figures; this version includes a central limit theore

School Quality, Educational Attainment and Aggregation Bias

Data from 31 countries participating in the Programme for International Student Assessment (PISA) is used to estimate education production functions for reading literacy.The analysis suggests that the probability of finding statistically significant and correctly signed class size effects increases the higher the level of aggregation used to measure class size.Class size, PISA data, bias

Marijuana use among young people in an era of policy change: what does recent evidence tell us?

R25 DA030310 - National Institute on Drug Abus

Distributed Computing with Adaptive Heuristics

We use ideas from distributed computing to study dynamic environments in which computational nodes, or decision makers, follow adaptive heuristics (Hart 2005), i.e., simple and unsophisticated rules of behavior, e.g., repeatedly "best replying" to others' actions, and minimizing "regret", that have been extensively studied in game theory and economics. We explore when convergence of such simple dynamics to an equilibrium is guaranteed in asynchronous computational environments, where nodes can act at any time. Our research agenda, distributed computing with adaptive heuristics, lies on the borderline of computer science (including distributed computing and learning) and game theory (including game dynamics and adaptive heuristics). We exhibit a general non-termination result for a broad class of heuristics with bounded recall---that is, simple rules of behavior that depend only on recent history of interaction between nodes. We consider implications of our result across a wide variety of interesting and timely applications: game theory, circuit design, social networks, routing and congestion control. We also study the computational and communication complexity of asynchronous dynamics and present some basic observations regarding the effects of asynchrony on no-regret dynamics. We believe that our work opens a new avenue for research in both distributed computing and game theory.Comment: 36 pages, four figures. Expands both technical results and discussion of v1. Revised version will appear in the proceedings of Innovations in Computer Science 201