Omar M. Ashour

A simulation analysis of the impact of FAHP-MAUT triage algorithm on the Emergency Department performance measures

Emergency Department (ED) crowding is a major problem in the U.S. like in many other countries world-wide. This problem is adversely affecting the safety of the patients who rely on receiving a timely treatment in EDs. As a part of solving this problem, a triage process is utilized. Triage is a pre-hospital process by which patients are sorted according to the severity of their illnesses or injuries. Improvements to this process would affect the patient flow positively, and in turn would enhance patient satisfaction and quality of care. In a previous study, we developed a triage algorithm that uses Fuzzy Analytic Hierarchy Process (FAHP) and Multi-Attribute Utility Theory (MAUT) to rank the patients according to their characteristics: chief complaint, age, gender, pain level, and vital signs. The main purpose of this study is to compare two triage systems using Discrete Event Simulation (DES); one system uses the typical Emergency Severity Index (ESI), and the other uses the FAHP and MAUT algorithm. Overall, there was no strong statistical evidence that either system would do better than the other for all the performance measures when the average is taken across all ESI levels. On the other hand, the collected simulated data by each ESI level showed that the FAHP-MAUT algorithm tends to balance the time-to-bed (TTB) and length of stay (LOS) for ESI levels 2-5. In terms of the percentage of tardy patients, FAHP-MAUT system significantly outperforms the ESI system for ESI levels 4 and 5; 34% vs. 61% and 25% vs. 70%, respectively. Both systems were performing about equally for ESI level 1 and level 3 patients; 25% vs. 26% and 64% vs. 67%, respectively. While ESI system slightly outperforms FAHP-MAUT system for ESI level 2 patients, 56% vs. 66%. Based on these results, we recommend using FAHP-MAUT not only because it performs better in terms of minimizing the number of patients with longer than the allotted upper limits of wait times, but also it reduces potential bias and errors in decision making in clinical settings; and thus, it can be used as the basis of an expert system to advise triage nurses.

Fuzzy AHP and utility theory based patient sorting in emergency departments

Triage, a classification system used to separate patients based on the acuity of their condition, is considered in this study. Triage process relies on the nurses interaction with the patient (e.g., a conversation on symptoms, visual observation, and vital sign measurements), and the subsequent severity classification. However, potential miscommunication, and thus uncertainty could be present in this process. In order to account for this uncertainty, a triage algorithm that uses fuzzy analytic hierarchy process (FAHP) along with the multi-attribute utility theory (MAUT) to sort the patients is presented. FAHP is used to get an acuity score on the chief complaint, and MAUT integrates this score with age, gender, and pain level to provide a final prioritisation. In the paper, a clinical case study is provided for which we used an expert nurses judgments to build the FAHP and the utility functions.

Dynamic patient grouping and prioritization: a new approach to emergency department flow improvement

The demand on emergency departments (ED) is variable and ever increasing, often leaving them overcrowded. Many hospitals are utilizing triage algorithms to rapidly sort and classify patients based on the severity of their injury or illness, however, most current triage methods are prone to over- or under-triage. In this paper, the group technology (GT) concept is applied to the triage process to develop a dynamic grouping and prioritization (DGP) algorithm. This algorithm identifies most appropriate patient groups and prioritizes them according to patient- and system-related information. Discrete event simulation (DES) has been implemented to investigate the impact of the DGP algorithm on the performance measures of the ED system. The impact was studied in comparison with the currently used triage algorithm, i.e., emergency severity index (ESI). The DGP algorithm outperforms the ESI algorithm by shortening patients’ average length of stay (LOS), average time to bed (TTB), time in emergency room, and lowering the percentage of tardy patients and their associated risk in the system.

Rank aggregation methods comparison: A case for triage prioritization

This paper seeks to test and to determine a suitable aggregation method to represent a set of rankings made by individual decision makers (DMs). A case study for triage prioritization is used to test the aggregation methods. The triage is a decision-making process with which patients are prioritized according to their medical condition and chance of survival on arrival at the emergency department (ED). There is a lot of subjective decision-making in the process which leads to discrepancies among nurses. Four rank aggregation methods are applied to the prioritization data and then an expert evaluates the results and judges them on practicality and acceptability. The proposed recommendation for preference aggregation is the method of the estimation of utility intervals. Expert opinion is highly valued in a decision-making environment such as this, where experience and intuition are key to successful job performance and outcomes.

A Study on Situated Cognition: Product Dissection's Effect on Redesign Activities.

Situated cognition theory describes the context of a learning activity’s effect on learner’s cognition. In this paper, we use situated cognition theory to examine the effect of product dissection on product redesign activities. Two specific research questions are addressed: 1) Does situated cogni tion, in the form of product dissection, improve product functionality during redesign exercise?, and 2) Does situated cognition, again in the form of product dissection, affect the creativity during product redesign? In this study, three sections of first-year students in two different locations – The Pennsylvania State University (Penn State) and Missouri University of Science and Technology (S&T) – performed product redesign using coffee makers. The redesigned products have been analyzed with respect to both depth (detail level) and creativity. Based on our results, we find that situated cognition, in the form of product dissection, improves product functionality during redesign and positively affects creativity. The implications of these results are also discussed.

From product dissection to product archaeology: Exposing students to global, economic, environmental, and societal impact through competitive and collaborative "digs"

Product dissection activities have been very successful used in engineering courses to help anchor the knowledge and practice of engineering in students’ minds. Unfortunately, most product dissection activities tend to stress form, functionality, and fabrication, missing opportunities to explore the broader impacts of engineering design decisions. In this paper, we present initial efforts to transform product dissection activities into product archaeology exercises wherein students “dig” to uncover not only the manufacturing (i.e., economic) issues of a product, but also the global and societal context that influenced its development as well as the environmental impact of the product during its life cycle. We introduce two new classes of exercises—competitive “digs” and collaborative “digs”—to engage students in similar, yet different, ways in product archaeology. Competitive “digs” pit teams of students in a time-based competition to unearth the global, societal, economic, and environmental impact of a product while collaborative “digs” allow students to work together to dig more deeply into these issues over an extended period of time. Results from pilot offerings of both of these types of exercises are summarized and discussed along with a preliminary educational assessment of one of the collaborative “digs”. Improvements to the exercises and future work to formalize this new paradigm of product archaeology are also discussed.Copyright

Redesign the engineering teaching and assessment methods to provide more information to improve students' learning

We present a synopsis of instructor experience on the mastery learning approach as implemented in our school for key fundamental engineering courses. The mastery learning approach revolves around the idea of dividing the course into modules, each module culminates in an exam comprised of 2 or 3 problems where each problem tests one important concept. For each exam, a student can make up to 3 attempts, however the maximum possible score and time allotted on subsequent attempts is reduced. Grading of the problems is based on a scale where no points are awarded unless the solution contains only a small error at most. Thus, mastery learning requires the students to go back and study the material if they get it wrong on the first attempt. We interviewed six instructors who use or have used the mastery learning approach in their classes. In general, instructors have a positive experience with mastery learning approach. However some challenges were noted that are also discussed in the paper. This paper aims to provide a context for the audience who are interested in implementing mastery learning approach in their curriculum.

An approach for rush order acceptance decisions using simulation and multi-attribute utility theory

Rush orders are orders with shorter lead times and higher operating priorities compared to regular orders. A company may accept rush order, regardless of its capacity or raw material constraints, to maintain customer satisfaction and/or increase profit. On the other hand, rush orders can cause problems in managing production systems due to the unbalanced use of system resources. In this paper, discrete event simulation (DES) and multi-attribute utility theory (MAUT) are integrated to study the impact of rush orders on the performance of a hybrid push-pull production system. The proposed approach is used to identify the best acceptance levels of rush orders. Numerical results showed that prioritising customer orders based on their associated utilities can improve the performance of a production system. In addition, the best acceptance levels of rush orders can be determined by maximising the performance of the production system while considering production constraints. [Received 25 May 2015; Revised 1 August 2016; Revised 6 September 2016; Revised 3 March 2017; Accepted 5 June 2017]

The Assessment of Product Archaeology as a Platform for Contextualizing Engineering Design

Many engineering departments struggle to meet “the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context” (Outcome h) that is required for ABET. As a result, engineering students receive meaningful contextual experiences in piecemeal fashion and graduate with a lack of concrete competencies that bridge knowledge and practice in the global world in which they will live and work. By considering products as designed artifacts with a history rooted in their development, our product archaeology framework combines concepts from archaeology with advances in cyber-enhanced product dissection to implement pedagogical innovations that address the significant educational gap. In this paper, we focus on assessing elements of a sustainable and scalable foundation that can support novel approaches aimed at educating engineering students to understand the global, economic, environmental, and societal context and impact of engineering solutions. This foundation is being developed across a network of partner institutions. We present recent results from freshman, sophomore, and senior courses at two of the partners in the national network of institutions.Copyright