Investigating and learning lessons from early experiences of implementing ePrescribing systems into NHS hospitals:a questionnaire study

Background: ePrescribing systems have significant potential to improve the safety and efficiency of healthcare, but they need to be carefully selected and implemented to maximise benefits. Implementations in English hospitals are in the early stages and there is a lack of standards guiding the procurement, functional specifications, and expected benefits. We sought to provide an updated overview of the current picture in relation to implementation of ePrescribing systems, explore existing strategies, and identify early lessons learned.Methods: a descriptive questionnaire-based study, which included closed and free text questions and involved both quantitative and qualitative analysis of the data generated.Results: we obtained responses from 85 of 108 NHS staff (78.7% response rate). At least 6% (n = 10) of the 168 English NHS Trusts have already implemented ePrescribing systems, 2% (n = 4) have no plans of implementing, and 34% (n = 55) are planning to implement with intended rapid implementation timelines driven by high expectations surrounding improved safety and efficiency of care. The majority are unclear as to which system to choose, but integration with existing systems and sophisticated decision support functionality are important decisive factors. Participants highlighted the need for increased guidance in relation to implementation strategy, system choice and standards, as well as the need for top-level management support to adequately resource the project. Although some early benefits were reported by hospitals that had already implemented, the hoped for benefits relating to improved efficiency and cost-savings remain elusive due to a lack of system maturity.Conclusions: whilst few have begun implementation, there is considerable interest in ePrescribing systems with ambitious timelines amongst those hospitals that are planning implementations. In order to ensure maximum chances of realising benefits, there is a need for increased guidance in relation to implementation strategy, system choice and standards, as well as increased financial resources to fund local activitie

Results of Environmental Scanning Applied to the Design of a Deer Management Decision Support System (DSS) For The United States and California

Using freely available internet search tools for environmental scanning, information related to deer management was collected, categorized, and evaluated with the goal of providing public decision support. Key issues raised in the public debate discovered by the search are addressed with relevant information formatted as output for a decision support system – dashboard elements. A graph addresses contradictory reports about the current direction of the deer population; the trend since 2006 appears to be down. Another graph illustrates the approximate longterm population trend; the current U.S. white-tailed deer population is about the same as in 1500. A table summarizes profiles of state deer issues and strategies. Only eleven states are trying to reduce their deer population. A graph illustrates the rise and fall of the California population, the most dramatic population decline in the U.S. over the past 100 years. Hunting pressure and herd demographic management are found to be related to the decline, making these candidate variables for attention in the decision support system. This case application is designed to illustrate methods the author has learned in creating a variety of decision support applications for technology companies

Predicting Risk for Deer-Vehicle Collisions Using a Social Media Based Geographic Information System

As an experiment investigating social media as a data source for making management decisions, photo sharing websites were searched for data on deer sightings. Data about deer density and location are important factors in decisions related to herd management and transportation safety, but such data are often limited or not available. Results indicate that when combined with simple rules, data from photo sharing websites reliably predicted the location of road segments with high risk for deer-vehicle collisions as reported by volunteers to an internet site tracking roadkill. Use of Google Maps as the GIS platform was helpful in plotting and sharing data, measuring road segments and other distances, and overlaying geographical data. The ability to view satellite images and panoramic street views proved to be a particularly useful. As a general conclusion, the two independently collected sets of data from social media provided consistent information, suggesting investigative value to this data source. Overlaying two independently collected data sets can be a useful step in evaluating or mitigating reporting bias and human error in data taken from social media

On fuzzy reasoning schemes

In this work we provide a short survey of the most frequently used fuzzy reasoning schemes. The paper is organized as follows: in the first section we introduce the basic notations and definitions needed for fuzzy inference systems; in the second section we explain how the GMP works under Mamdani, Larsen and G¨odel implications, furthermore we discuss the properties of compositional rule of inference with several fuzzy implications; and in the third section we describe Tsukamoto’s, Sugeno’s and the simplified fuzzy inference mechanisms in multi-input-single-output fuzzy systems

An institutional approach to the role of cost accounting in regulated markets: the case of the royal soap factory of Seville (1515-1692)

Regulated markets and state-owned monopolies characterized the economies of many Southern European and Latin American territories around the end of the Middle Ages and the Renaissance. Strikingly, however, investigation into the functioning of cost accounting in such contexts has been widely neglected in accounting research. In this paper, we examine the role of early cost systems in regulated markets by focusing on the case of the soap production and distribution monopoly in the City of Seville (Spain). In 1423, the King of Castille granted the soap monopoly to the Duke of Alcalá as a reward for his war achievements, but the decision on the price of soap rested in the hands of the local government. Disputes between the Duke of Alcalá and the local government (the parties) about the fair price of a pound of soap were resolved through tests that replicated the soap production process and determined its cost through complex calculations. Drawing on the insights of institutional sociology, we found that the test and its accompanying cost calculations constituted an institution that legitimized the parties both in the public opinion and before the King. Further, our data revealed that the parties engaged in active agency before the King of Spain to shape in their favor the constitutive elements of the institution, such as the use of purpose-purchased or stored materials in the soap test; incorporation into the total cost the rents that would have been earned if the factory buildings were leased; and the salaries of some employees (i.e., slaves, factory administrator and priest)

When decision support systems fail: insights for strategic information systems from Formula

Decision support systems (DSS) are sophisticated tools that increasingly take advantage of big data and are used to design and implement individual - and organization - level strategic decisions . Yet, when organizations excessively rely on their potential the outcome may be decision - making failure, particularly when such tools are applied under high pressure and turbulent conditions. Partial understanding and unidimensional interpretation can prevent learning from failure. Building on a practice perspective, we study an iconic case of strategic failure in Formula 1 racing. Our approach, which integrates the decision maker as well as the organizational and material context , identifies three interrelated sources of strategic failure that are worth investigation for decision - makers using DSS and big data: (1) t he situated nature and affordances of decision - making ; (2) t he distributed nature of cognition in decision - making; and (3) the performativity of the DSS. We outline specific research questions and their implications for firm performance and competitive advantage. Finally, we advance an agenda that can help close timely gaps in strategic IS research