Navid Jamali

Bio: Navid Jamali is an academic researcher from University of Toronto. The author has an hindex of 1, co-authored 1 publications receiving 6 citations.

A review of computerized hospital layout modelling techniques and their ethical implications

Abstract: Purpose This paper reviews an area of interdisciplinary collaboration in the design of healthcare facilities that attempts to optimize hospital space-planning using automated statistical techniques from the discipline of Operations Research (OR). This review articulates Facility Layout Problems (FLPs) as a general class of OR problems. Furthermore, the review highlights limitations of these techniques, which necessitate an ethical and participatory engagement with computerized processes of healthcare architecture. Design/methodology/approach An in-depth critical review was carried out, which revealed a number of common themes, collectively theorized as metamodeling processes, or models of models, through which various FLP modelling techniques can be challenged and debated in terms of their architectural viability, and ethical ramifications. Findings This review provides a methodological basis for the further evaluation of computational models. It was found that most of the reviewed studies are functionally focused on flow efficiency and, in general, do not consider broader contextual, relational, social, or salutogenic design values. Originality/value This review is the first on the subject written from an architectural perspective. It can be used by a broad range of readers as its critical review of past and present hospital layout modelling techniques discusses their capabilities and limitations. As such, it also enables them to consider ethical values while critiquing the epistemology of computational processes hidden beneath algorithmic outputs.

Mathematical optimization approaches for facility layout problems: The state-of-the-art and future research directions

Abstract: Facility layout problems are an important class of operations research problems that has been studied for several decades. Most variants of facility layout are NP-hard, therefore global optimal solutions are difficult or impossible to compute in reasonable time. Mathematical optimization approaches that guarantee global optimality of solutions or tight bounds on the global optimal value have nevertheless been successfully applied to several variants of facility layout. This review covers three classes of layout problems, namely row layout, unequal-areas layout, and multifloor layout. We summarize the main contributions to the area made using mathematical optimization, mostly mixed integer linear optimization and conic optimization. For each class of problems, we also briefly discuss directions that remain open for future research.

Optimizing Hospital Room Layout to Reduce the Risk of Patient Falls.

Abstract: Despite years of research into patient falls in hospital rooms, falls and related injuries remain a serious concern to patient safety. In this work, we formulate a gradient-free constrained optimization problem to generate and reconfigure the hospital room interior layout to minimize the risk of falls. We define a cost function built on a hospital room fall model that takes into account the supportive or hazardous effect of the patient's surrounding objects, as well as simulated patient trajectories inside the room. We define a constraint set that ensures the functionality of the generated room layouts in addition to conforming to architectural guidelines. We solve this problem efficiently using a variant of simulated annealing. We present results for two real-world hospital room types and demonstrate a significant improvement of 18% on average in patient fall risk when compared with a traditional hospital room layout and 41% when compared with randomly generated layouts.

A mixed integer programming formulation for solving operating theatre layout problem: A multi-goal approach

Abstract: Facility Layout Problem (FLP) has been widely used in industrial systems to manage the space and the facilities within the floor space. The layout has a great impact on the productivity and the efficiency of running an organization. In health care systems, FLP is applied to hospital layout in a way to improve the health process, but the Operating Theater layout has received less attention instead of its importance. Existing research dealing with the OT Layout were based on graph theoretic methods, which ignore the size, the orientation and the shape of rooms and just focused on the desirable adjacency objective. This paper proposes a Mixed Integer Linear Programming (MILP) formulation for the Operating Theater Layout problem. The formulation uses a multi-goal approach to optimize two objectives: the first quantitative objective minimizes the interdepartmental traveling costs, whereas the second qualitative objective maximizes the closeness of the facilities. The presented model determines the position and orientation of each activity according to the OT international standards. The applicability of the model is demonstrated on four illustrative examples using commercial optimization software.

A multi-objective mixed-integer programming model for a multi-section operating theatre facility layout

Abstract: The focus of this paper is on facilities with multiple sections where the material transport between sections occurs through corridors. A Mixed Integer Linear Programming (MILP) formulation for the Operating Theater Layout problem is proposed. The formulation uses a multi-goal approach to optimize two objectives: the first quantitative objective minimizes the interdepartmental traveling costs, whereas the second qualitative objective maximizes the closeness of the facilities. The presented model determines the position and orientation of each activity according to the OT international standards. The applicability of the model is demonstrated on four illustrative examples using commercial optimization software.