Shamimi A. Halim

Agent-based modelling and simulation of emergency department re-triage

Triage is a process of accessing patients on their severity based on a triage acuity scale in hospital emergency department (ED). Re-triage is a process where the severity of a patients condition is reassessed when there is a clinical need for it. Re-triage does not feature in the conventional triage, where the patients with non-urgent consideration will have to wait to be treated on a first come first serve basis. In this study, we investigate the effect of re-triage on patients waiting time and on the ED service by means of agent-based modelling and simulation. The simulation is based on historical records of patients presenting to the ED of Hospital USM in the year 2011. The result of the simulation shows that the implementation of re-triage in the conventional three-level triage system can significantly Reduce the waiting time of patients with deteriorating clinical conditions, with slight increase in the demand for ED service due to the re-triage activity.

A Conceptualisation of an Agent-Oriented Triage Decision Support System

Triage is a complex process in ED that necessitates accurate, consistent and timely decision for assessment and management of incoming patients. With triage officers having different levels of expertise and experience, the triage scales are applied inconsistently, as evident from the lack of uniformity in the existing triaging system in Malaysian hospitals. In many hospitals, the triaging largely occurs in an ad hoc basis, placing patients at risk and contributing to inefficient resource utilisation. A computer system can be used to overcome these problems. Consequently, the paper proposes the development of a knowledge-based, agent-oriented decision support system for triage assessment and management. The ability to implement goal-directed behaviour, communicative processes and schedule-oriented, but concurrently executed tasks among others, make the agent technology suitable to be applied. We intend to adopt a modelling view to knowledge engineering, and plan to use the CommonKADS methodology as a basis for knowledge engineering, modelling and knowledge base development.

Flies species recognition for maggot therapy using neural-expert technique

Maggot Debridement Therapy (MDT) has been recognized as one of the effective alternative treatment to enhance healing and to decrease the mortality associated with underlying injury. One of the most important procedures in performing MDT is to use the correct maggot from suitable species. In this case, maggots from the incorrect species would consume the live tissue instead of the dead tissue. Hence, this is highlighted as one of the difficulties in implementing MDT. Currently the process of identifying flies is done manually by experts or by using DNA traits. We explored and developed another procedure to recognize the species using hybrid neuro-expert technique. The percentage of correctness using standard back propagation neural network yields 94.4% accuracy. By adapting the neuro-expert technique, the prototype accuracy is 100%.

Task-Based Modelling of the Triage Domain Knowledge

Triage is a decision-making process that classifies incoming patients for presentational urgency in Emergency Departments (EDs). There are issues with triage reliability in EDs, which we can be resolved through uniform application of a robust triage scale. However, the complex robust triaging knowledge is not easy to understand or recalled for timely decision-making. Therefore, we suggest the development of a knowledge-based triage decision support system to help triage officers to make correct and consistent triage decisions. Consequently, we pursued knowledge engineering to construct the models of the knowledge in order to make explicit the conceptualisation of the assumptions and constraints in triage decision-making. We regard task as a rationale basis for modelling the purposive domain knowledge. Consequently, the paper discusses the modelling of the domain knowledge to support the triage decision-making task. The triage decision-making task model is presented in a complementary paper. Together, the knowledge models can be viewed as meta models that provide the conceptual guiding principles for the consequent design of the triage decision support system.

A Conceptualisation of a Strategy to Shiftwork Scheduling Optimisation in an Emergency Department

Shiftwork schedule is required to provide uninterrupted service for the hospital emergency department. There are many limitations with the manual shiftwork scheduling applied at the University of Malaya Medical Centre Emergency Department (UMMC-ED). We propose an alternative shiftwork scheduling strategy to solve these limitations which consists of three modes; Initialization, Sufficient and Insufficient mode. These modes detect the imbalance between workforce and workload which enable the appropriate distribution according to the demands of individual staff. We developed a tool, Trauma Hospital Online Roster (THOR) that implements the above strategy.

Domain Expert Maintainable Inference Knowledge of Assessment Task

Inference and domain knowledge are the foundation of a Knowledge-based System (KBS). Inference knowledge describes the steps or rules used to perform a task inference; making reference to the domain knowledge that is used. The inference knowledge is typically acquired from the domain experts and communicated to the system developers to be implemented in a KBS. The explicit representation of inference knowledge eases the maintenance of the evolving knowledge. However, the involvements of the knowledge engineers and software developers during the maintenance phase give cause to several problems during the systems life-cycle. In this paper, we provide a possible way of using rule templates to abstract away the inference knowledge to higher conceptual categories that are amenable to domain experts. Backed by a rule editing user-interface that is designed to instantiate the rule templates, the responsibility to maintain the inference knowledge can be assigned to the domain experts, i.e., the originators of the knowledge. The paper demonstrates the feasibility of the idea by making a case of inference knowledge applied to assessment task such as triage decision making. Five rule templates to represent the inference knowledge of assessment tasks are proposed. We validated the rule templates through case studies in several domains and task, as well as through usability testing.

New approach of assessing hypovolemic shock class 1 during acute emergencies: Ultrasonographic inferior vena cava and abdominal aorta diameter ratio

In a patient with hypovolemic shock class 1, the vital signs and biochemical properties are almost normal. The alteration of hemodynamic parameters and biochemical values occurs mainly in advanced hypovolemia state (neuroendocrine response). The availability of ultrasound machine at healthcare centers makes the measurement of vascular calibre feasible and possible. Inspiration and expiration inferior vena cava diameter changes predict hypovolemic shock class 1 but in acute emergencies this method is impractical. The purpose of this study is to develop a new approach in identifying hypovolemic shock at early phase by measuring the inferior vena cava and aorta diameter ratio using bedside ultrasound machine.

Ultrasonographic abdominal aorta diameter changes: A predictor of hypovolemic shock class 1

Hypovolemic shock class 1 and mild to moderate dehydration are associated with normal or minimal changes in vital signs. Biochemical values markedly change only in advanced hypovolemia. Inspiration and expiration inferior vena cava diameter changes predict hypovolemic shock class 1 but in acute emergencies this method is impractical. The purpose of this study is to develop a new approach in identifying hypovolemic shock at early phase (class 1 hypovolemic shock) by measuring the diameter of aorta using ultrasound machine.