Design for Improving Hospital Stroke Unit Processes: Reducing Complex Systems Failures Leading to Adverse Patient Outcomes

This paper describes recent research involving a user-focused design analysis of in-hospital residential treatment for stroke patients. The focus of the research was to identify positive and negative design heuristics associated with addressing poor performance, errors and failures of patient care associated with current designs of hospital systems processes being inadequate to address actual levels of system complexity. The research findings are based on an in–depth case study following a single patient through a stroke unit in a medium scale hospital of (approximately 280 acute beds overall) with 26 stroke unit beds. The case study involved over 200 hours of observations over nine weeks and liaison with hospital and family over the four months of the patient’s stay in hospital. The findings suggest an explanation for the lack of effective advantage so far shown for integrated care as compared to conventional multidisciplinary care. In essence, they suggest that integrated stroke care and multidisciplinary care are both subject to similar serious systemic organisational failures that in effect reduce outcomes of both to a similar compromised position. The paper concludes with three design heuristics for improving stroke unit outcomes via improving the design of stroke unit organisational systems. These proposed heuristics may be of benefit more widely in hospital system design for improved outcomes. Keywords: Hospital System Design, Design Strategies, User-Based Assessment, Case Study, Viable System Model</p

On testing global optimization algorithms for space trajectory design

In this paper we discuss the procedures to test a global search algorithm applied to a space trajectory design problem. Then, we present some performance indexes that can be used to evaluate the effectiveness of global optimization algorithms. The performance indexes are then compared highlighting the actual significance of each one of them. A number of global optimization algorithms are tested on four typical space trajectory design problems. From the results of the proposed testing procedure we infer for each pair algorithm-problem the relation between the heuristics implemented in the solution algorithm and the main characteristics of the problem under investigation. From this analysis we derive a novel interpretation of some evolutionary heuristics, based on dynamical system theory and we significantly improve the performance of one of the tested algorithms

The Stochastics of Threshold Accepting: Analysis of an Application to the Uniform Design Problem

Threshold Accepting (TA) is a powerful optimization heuristic from the class of stochastic local search algorithms. It has been applied successfully to different optimization problems in statistics and econometrics, including the uniform design problem. Using the latter application as example, the stochastic properties of a TA implementation are analyzed. We provide a formal framework for the analysis of optimization heuristics like TA, which can be used to estimate lower bounds and to derive convergence results. It is also helpful for tuning real applications. Based on this framework, empirical results are presented for the uniform design problem. In particular, for two problem instances, the rate of convergence of the algorithm is estimated to be of the order of a power of -0.3 to -0.7 of the number of iterations. --Heuristic optimization,Threshold Accepting,Stochastic analysis of heuristics

The order and priority of research and design method application within an assistive technology new product development process: A summative content analysis of 20 case studies

Summative content analysis was used to define methods and heuristics from each case study. The review process was in two parts: 1) A literature review to identify conventional research methods; and, 2) a summative content analysis of published case studies, based on the identified methods and heuristics to suggest an order and priority of where and when were used. Over 200 research and design methods and design heuristics were identified. From the review of the 20 case studies 42 were identified as being applied. The majority of methods and heuristics were applied in phase two, market choice. There appeared a disparity between the limited numbers of methods frequently used, under ten within the 20 case studies, when hundreds were available

On Optimizing Distributed Tucker Decomposition for Dense Tensors

The Tucker decomposition expresses a given tensor as the product of a small core tensor and a set of factor matrices. Apart from providing data compression, the construction is useful in performing analysis such as principal component analysis (PCA)and finds applications in diverse domains such as signal processing, computer vision and text analytics. Our objective is to develop an efficient distributed implementation for the case of dense tensors. The implementation is based on the HOOI (Higher Order Orthogonal Iterator) procedure, wherein the tensor-times-matrix product forms the core routine. Prior work have proposed heuristics for reducing the computational load and communication volume incurred by the routine. We study the two metrics in a formal and systematic manner, and design strategies that are optimal under the two fundamental metrics. Our experimental evaluation on a large benchmark of tensors shows that the optimal strategies provide significant reduction in load and volume compared to prior heuristics, and provide up to 7x speed-up in the overall running time.Comment: Preliminary version of the paper appears in the proceedings of IPDPS'1

Useful shortcuts: Using design heuristics for consent and permission in smart home devices

Prior research in smart home privacy highlights significant issues with how users understand, permit, and consent to data use. Some of the underlying issues point to unclear data protection regulations, lack of design principles, and dark patterns. In this paper, we explore heuristics (also called “mental shortcuts” or “rules of thumb”) as a means to address security and privacy design challenges in smart homes. First, we systematically analyze an existing body of data on smart homes to derive a set of heuristics for the design of consent and permission. Second, we apply these heuristics in four participatory co-design workshops (n = 14) and report on their use. Third, we analyze the use of the heuristics through thematic analysis highlighting heuristic application, purpose, and effectiveness in successful and unsuccessful design outcomes. We conclude with a discussion of the wider challenges, opportunities, and future work for improving design practices for consent in smart homes