Provision of pharmaceutical care by community pharmacists:a comparison across Europe

Objective To investigate the provision of pharmaceutical care by community pharmacists across Europe and to examine the various factors that could affect its implementation. Methods A questionnaire-based survey of community pharmacies was conducted within 13 European countries. The questionnaire consisted of two sections. The first section focussed on demographic data and services provided in the pharmacy. The second section was a slightly adapted version of the Behavioral Pharmaceutical Care Scale (BPCS) which consists of three main dimensions (direct patient care activities, referral and consultation activities and instrumental activities). Results Response rates ranged from 10–71% between countries. The mean total score achieved by community pharmacists, expressed as a percentage of the total score achievable, ranged from 31.6 (Denmark) to 52.2% (Ireland). Even though different aspects of pharmaceutical care were implemented to different extents across Europe, it was noted that the lowest scores were consistently achieved in the direct patient care dimension (particularly those related to documentation, patient assessment and implementation of therapeutic objectives and monitoring plans) followed by performance evaluation and evaluation of patient satisfaction. Pharmacists who dispensed higher daily numbers of prescriptions in Ireland, Germany and Switzerland had significantly higher total BPCS scores. In addition, pharmacists in England and Ireland who were supported in their place of work by other pharmacists scored significantly higher on referral and consultation and had a higher overall provision of pharmaceutical care. Conclusion The present findings suggest that the provision of pharmaceutical care in community pharmacy is still limited within Europe. Pharmacists were routinely engaged in general activities such as patient record screening but were infrequently involved in patient centred professional activities such as the implementation of therapeutic objectives and monitoring plans, or in self-evaluation of performance.

Handling and communicating uncertainty in chained geospatial web services

Recent developments in service-oriented and distributed computing have created exciting opportunities for the integration of models in service chains to create the Model Web. This offers the potential for orchestrating web data and processing services, in complex chains; a flexible approach which exploits the increased access to products and tools, and the scalability offered by the Web. However, the uncertainty inherent in data and models must be quantified and communicated in an interoperable way, in order for its effects to be effectively assessed as errors propagate through complex automated model chains. We describe a proposed set of tools for handling, characterizing and communicating uncertainty in this context, and show how they can be used to 'uncertainty- enable' Web Services in a model chain. An example implementation is presented, which combines environmental and publicly-contributed data to produce estimates of sea-level air pressure, with estimates of uncertainty which incorporate the effects of model approximation as well as the uncertainty inherent in the observational and derived data.

General and multiplicative non-parametric corporate performance models with interval ratio data

The increasing intensity of global competition has led organizations to utilize various types of performance measurement tools for improving the quality of their products and services. Data envelopment analysis (DEA) is a methodology for evaluating and measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. All the data in the conventional DEA with input and/or output ratios assumes the form of crisp numbers. However, the observed values of data in real-world problems are sometimes expressed as interval ratios. In this paper, we propose two new models: general and multiplicative non-parametric ratio models for DEA problems with interval data. The contributions of this paper are fourfold: (1) we consider input and output data expressed as interval ratios in DEA; (2) we address the gap in DEA literature for problems not suitable or difficult to model with crisp values; (3) we propose two new DEA models for evaluating the relative efficiencies of DMUs with interval ratios, and (4) we present a case study involving 20 banks with three interval ratios to demonstrate the applicability and efficacy of the proposed models where the traditional indicators are mostly financial ratios. © 2011 Elsevier Inc.