Getting management accounting off the ground: post-colonial neoliberalism in healthcare budgets

Taking Sven Modell’s (2014, pp. 83–103) “societal relevance of management accounting” agenda forward, and based on a cost accounting initiative in a Sri Lankan hospital, this paper examines how management accounting is implicated in societal relevance. It reports on a postcolonial neoliberal state’s use of cost-saving experiments and the resultant emancipation of the individuals involved. It runs a bottom-up analysis, from micro events in the hospital to policymaking at the level of the Provincial Council. This analysis suggests that cost accounting acts as a mediating instrument: it begins to loosen the old Keynesian postcolonial bureaucratic budget confinements, creates a social space for individuals to consider cost-saving experiments, and addresses wider policy concerns about hospital resource management. The story is illuminated by Gilles Deleuze’s and Zigmund Bauman’s ideas on post-panoptic societies: old confinements are being problematized and new flexible, “liquid” spaces created, in which individuals are emancipated in terms of their ability to influence resource management within and beyond the organizational constituency

Beyond economic sustainability: embedding social and environmental values in the governance of responsible investment

The transition of global financial markets towards investment models that incorporate environmental and social dimensions is now well underway. This paper discusses the evolution of contemporary responsible investment (RI) and its relationship to sustainable development and environmental social governance(ESG). In the conception of ESG presented here, various well-known institutional arrangements, most notably interest representation, accountability and transparency, decision-making, and implementation are linked to the structures and processes of governance. Using a hierarchical framework of principles, criteria and indicators (PC&I), the paper presents a means for evaluating RI by way of an analysis of stakeholder perceptions regarding the sector’s governance quality. It concludes with some observations on the challenges confronting RI, notably the need for universally consistent quality of governance standards

QuantUM: Quantitative Safety Analysis of UML Models

When developing a safety-critical system it is essential to obtain an assessment of different design alternatives. In particular, an early safety assessment of the architectural design of a system is desirable. In spite of the plethora of available formal quantitative analysis methods it is still difficult for software and system architects to integrate these techniques into their every day work. This is mainly due to the lack of methods that can be directly applied to architecture level models, for instance given as UML diagrams. Also, it is necessary that the description methods used do not require a profound knowledge of formal methods. Our approach bridges this gap and improves the integration of quantitative safety analysis methods into the development process. All inputs of the analysis are specified at the level of a UML model. This model is then automatically translated into the analysis model, and the results of the analysis are consequently represented on the level of the UML model. Thus the analysis model and the formal methods used during the analysis are hidden from the user. We illustrate the usefulness of our approach using an industrial strength case study.Comment: In Proceedings QAPL 2011, arXiv:1107.074

Factors influencing palliative care in advanced dementia : A systematic review

© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.Background: Dementia is a progressive neurodegenerative life-limiting disease. The international literature indicates that patients with advanced dementia can benefit from palliative care (PC) provided during the end-of-life phase. However, evidence indicates that currently many fail to access such provision despite the increased recognition of their palliative needs. Aim: To investigate the factors influencing provision of PC services for people with advanced dementia. Methods: A systematic review of mixed method studies written in English was undertaken. 11 electronic databases including Embase, Medline, PubMed, CINAHL and Scopus from 2008 to 2018 were searched. Narrative synthesis and content analysis were used to analyse and synthesise the data. Key findings: In total, 34 studies were included. 25 studies providing qualitative data, 6 providing quantitative data and 3 mixed methods studies. The findings identified organisational, healthcare professionals and patients-related barriers and facilitators in provision of PC for people with advanced dementia from perspective of stakeholders across different care settings. The most commonly reported barriers are lack of skills and training opportunities of the staff specific to PC in dementia, lack of awareness that dementia is a terminal illness and a palliative condition, pain and symptoms assessment/management difficulties, discontinuity of care for patients with dementia and lack of coordination across care settings, difficulty communicating with the patient and the lack of advance care planning. Conclusions: Even though the provision of PC was empirically recognised as a care step in the management of dementia, there are barriers that hinder access of patients with dementia to appropriate facilities. With dementia prevalence rising and no cure on the horizon, it is crucial that health and social care regulatory bodies integrate a palliative approach into their care using the identified facilitators to achieve optimal and effective PC in this population.Peer reviewe

Deep Reinforcement Learning for Resource Allocation in V2V Communications

In this article, we develop a decentralized resource allocation mechanism for vehicle-to-vehicle (V2V) communication systems based on deep reinforcement learning. Each V2V link is considered as an agent, making its own decisions to find optimal sub-band and power level for transmission. Since the proposed method is decentralized, the global information is not required for each agent to make its decisions, hence the transmission overhead is small. From the simulation results, each agent can learn how to satisfy the V2V constraints while minimizing the interference to vehicle-to-infrastructure (V2I) communications

Adaptive feedback analysis and control of programmable stimuli for assessment of cerebrovascular function

The assessment of cerebrovascular regulatory mechanisms often requires flexibly controlled and precisely timed changes in arterial blood pressure (ABP) and/or inspired CO2. In this study, a new system for inducing variations in mean ABP was designed, implemented and tested using programmable sequences and programmable controls to induce pressure changes through bilateral thigh cuffs. The system is also integrated with a computer-controlled switch to select air or a CO2/air mixture to be provided via a face mask. Adaptive feedback control of a pressure generator was required to meet stringent specifications for fast changes, and accuracy in timing and pressure levels applied by the thigh cuffs. The implemented system consists of a PC-based signal analysis/control unit, a pressure control unit and a CO2/air control unit. Initial evaluations were carried out to compare the cuff pressure control performances between adaptive and non-adaptive control configurations. Results show that the adaptive control method can reduce the mean error in sustaining target pressure by 99.57 % and reduce the transient time in pressure increases by 45.21 %. The system has proven a highly effective tool in ongoing research on brain blood flow control

A New Decision Support Framework for Managing Foot-and-mouth Disease Epidemics

Animal disease epidemics such as the foot-and-mouth disease (FMD) pose recurrent threat to countries with intensive livestock production. Efficient FMD control is crucial in limiting the damage of FMD epidemics and securing food production. Decision making in FMD control involves a hierarchy of decisions made at strategic, tactical, and operational levels. These decisions are interdependent and have to be made under uncertainty about future development of the epidemic. Addressing this decision problem, this paper presents a new decision-support framework based on multi-level hierarchic Markov processes (MLHMP). The MLHMP model simultaneously optimizes decisions at strategic, tactical, and operational levels, using Bayesian forecasting methods to model uncertainty and learning about the epidemic. As illustrated by the example, the framework is especially useful in contingency planning for future FMD epidemic