Simulating Movement Devices Used in Hospital Evacuation

Planning for the evacuation of hospitals and healthcare facilities from a fire incident presents a number of unique challenges. It is common for hospitals to have large and complex building structures, while wards have different uses and different staffing structures. There is high staff turnover; therefore, frequent training is required [1]. However, staff training can be problematic as live hands-on drills are often impractical [2]. Areas in healthcare facilities have highly variable occupancy levels and, importantly, patients may require assistance and continuing care dependent on their clinical needs. It can be expected that there will be large numbers of vulnerable occupants and people with reduced mobility (PRM)—a far greater proportion than would be expected in other buildings.

In comparison to other building types, patients in hospitals are more likely to await personal staff instruction on hearing an alarm given their vulnerability and lack of familiarity with the procedure in place; therefore, staff are vital to the evacuation strategy employed [3]. To evacuate PRM staff might have to make many trips, assisting individual patients in turn. This is physically demanding and requires triage procedures to organise, enhance and monitor the process. Evacuating patients is particularly challenging when many require assistance: when the staff to patient ratio is low (e.g. on a night shift), when the structural configuration is complex, and when vertical movement is required. In addition, the size of movement assist devices (alone and in conjunction with the number and identity of handlers) and hospital beds can create moving obstacles while transferring patients, potentially delaying the evacuation of others.

While fire and rescue services are crucial in any hospital fire event, the emphasis for evacuation planning is on in-house procedures. For example, to meet legal requirements in the UK, the emergency response must be designed under the assumption that there will be no evacuation assistance from the fire and rescue services [4]. Typical procedures avoid full building evacuations as this can place highly dependent patients (e.g. those with severe medical conditions) at risk and compromise the functionality of the hospital. The most common strategy is progressive horizontal evacuation, which is conducted in stages to limit the number of people impacted and reduce the distress that might be caused to vulnerable patients. Premises are divided into compartments and sub-compartments, constructed to provide required levels of fire safety. In the event of a fire, occupants are progressively moved into adjacent compartments away from the fire. The concept of horizontal evacuation reduces the number of patients to be moved, as long as fire compartmentation is effective. This approach is based on a three-stage procedure [5]. Those in the fire sub-compartment are initially moved to an adjoining compartment or sub-compartment, using beds or wheelchairs for PRM. If a second stage is deemed to be necessary, patients are then moved from the entire fire compartment to an adjoining compartment. Additional horizontal evacuation may be required before the third stage: vertical evacuation to a lower floor, or to the outside. In adopting this approach, those most exposed to the fire incident are given priority, while attempting to minimize the distress caused to the patients involved.

When assessing risk, it is typically expected that horizontal evacuation will be sufficient and that full hospital evacuation is unlikely to be required. However, incidents have revealed that it can be also necessary to fully evacuate an entire hospital [6‐8] and while elevators may be used, guidance has highlighted that it is essential that provision be made for vertical (stairway) evacuation of patients without the use of lifts [5]. This requires the use of movement assist devices to transport PRM down stairs; for example, hospital rescue sheets, carry chairs, evacuation chair, stretcher, etc. The perception that horizontal evacuation is likely to be sufficient has led to a lack of focus in risk assessments on the vertical component [9]. This leaves gaps in planning for large-scale assisted evacuation and in the provision of training and equipment such as movement assist devices for evacuation down stairs.

To address the complexities of planning for evacuation, many countries are now incorporating performance-based alternatives to increase design flexibility over previous prescriptive building codes, enabling safety performance levels to be established [1, 10, 11]. This represents an evidence-based approach of evaluating evacuation performance, with fire modelling used to estimate the Available Safe Egress Time (ASET) and evacuation modelling used to estimate the Required Safe Egress Time (RSET). This approach allows comparison of the performance of different designs in certain scenarios. The goal is to ensure that ASET > RSET including a safety factor to incorporate a margin of error [12]. Performance-based design requires fire safety engineering: a method of design that assesses performance to demonstrate that it meets regulatory objectives, without necessarily adhering to detailed prescriptive codes.

Simulation can support this fire safety engineering approach by quantifying performance using stochastic (dynamic) modelling. Commercially-available software has been developed to simulate the fire development [13] and/or the evacuation process [14], and are employed internationally as part of performance-based design efforts. Agent-based models (e.g. STEPS [15] and MassMotion [16]), simulate the circulation and evacuation of individuals to gauge a building’s expected performance during egress. However, the application of these and other models to the hospital environment has proved challenging [17‐22]. Many models represent ambulatory differences between people and have incorporated mobility distributions; however, the models that represent PRM have done so by simply modifying their walking speeds or the size of the ambulant individuals (as opposed to devices), not by explicitly representing the devices required to transport them. This only represents one facet of the dynamics of assisted evacuation (i.e. the reduced travel speed) rather than the many others that might exist for the PRM and to those around them (e.g. inability to use certain routes, occupying more space, etc.). For instance, not modelling the movement device might misrepresent the impact on the space occupied, the navigational impact on other pedestrians, and the impact on route availability. Some models represent wheelchair users [15, 16, 23‐25], but are not able to reflect the shape and increased footprint of these devices, particularly in vertical movement and the impact they might have on navigation, manoeuvrability, speed, and on the movement of the adjacent population. Understanding this impact has been shown to be key in assessing the effectiveness of a procedure (or a device) in moving vulnerable populations to safety [26]. The Pathfinder model has recently been developed to now include functionality to physically represent the device and its associated impact on performance. The Pathfinder model is a continuous model, where location and movement are coordinate-based rather than the nodal system described here. As such, the implementation of the functionality described herein is different—requiring different geometrical considerations. The work described here is significantly different from that applied in the Pathfinder model and (as far as the authors are aware) represents the first peer-reviewed description of an attempt to embed such functionality within a simulation tool.¹

Several movement assist devices are available to transport PRM during an evacuation. However, there are only a few data-sets that can be used to quantify the performance of these devices. In conjunction with the mathematical challenges involved in simulating the effect of movement devices, the absence of supporting data also represents an important hurdle to their representation.

The previous discussion highlights several points. The combination of structural, procedural and occupant issues make planning safety strategies for healthcare facilities particularly challenging. The array of interacting factors means that analytically (or intuitively) identifying the effectiveness of procedural strategies becomes highly problematic. Recent international legislation requires equivalent safety practices for all occupants [27, 28]. When coupled with expected demographic changes, this means that a growing population of movement-impaired people need to be supported in evacuation strategies. Historical safety procedures may not be sufficient given the evidence provided by recent incidents. Recent regulatory practices have spawned a generation of engineering tools designed to quantify evacuation performance. These are typically generic in nature. Engineering/simulation tools that can quantify performance are particularly valuable in a healthcare environment. However, such tools require dedicated functionality to represent the peculiarities of the hospital environment (e.g. PRM movement) and require data on which to build these functionalities. There is a paucity of such developments and such data.

The work presented here uses experimental data to inform the development of dedicated functionality within an existing evacuation simulation tool to quantify PRM evacuation performance. This represents a significant advance on many fronts: in the understanding of PRM movement in evacuation devices, the quantification of this movement, and the representation of this movement within a simulated environment. This advance allows fire protection engineers and healthcare providers to assess the effectiveness of their building designs and procedural strategies to ensure a hospital population reaches a place of safety in the time available.

Table 1 provides an overview of the simulation functionality that is required within modelling software to represent the key components of hospital evacuation. As identified by a systematic review of the literature [22], the crucial development needed in simulating hospital evacuation is the explicit representation of the devices used to evacuate PRM. It requires a geometrical representation that reflects its movement and the space it occupies, as well as the human factors associated with its use. The theoretical model developed to address this also advances the ability to represent other human-manoeuvred objects, such as prams, trolleys and luggage in evacuation scenarios. While this work focuses on the development of simulation tools for movement devices in hospitals, its widely applicable functionality is developed in general and versatile terms in order to be useful in other applications. As such, this paper describes functionality that can be generalised as “objects”, and functionality that is specific to movement devices as “devices” throughout this paper.

This section presents a synoptic outline of the Object Model (OM) developed to represent human-operated objects within evacuation software. The model developments presented here were implemented within buildingEXODUS V6.0 (bEX) [44], and forms part of a PhD project undertaken by the lead author while at the Fire Safety Engineering Group of the University of Greenwich [22]. bEX allows agents to move around a nodal grid (that represents occupiable space), with the nature and connectivity of the nodes affecting their movement and performance

To fully integrate within the software, it is important that the objects specified here can interact with the other sub-models within bEX. Therefore, in addition to the OM, the full range of existing capability is required, including the group and leadership behaviours, the wayfinding and signage features, the interaction and conflict resolution with other occupants, and the potential for pairing with the fire simulation software SMARTFIRE [45], in order to ensure that the additional developments represented are able to interact as expected with the existing model functionality. The methodologies presented here are designed to preserve these established interactions by integrating with this existing bEX functionality where possible.

There are currently no definitive standards for the testing of building evacuation simulations. We now adopt the most comprehensive tests available (i.e. ISO/TR 16730-5:2013 [52] and NIST [53]) and a battery of new tests to quantify the movement of beds and movement devices, in both horizontal and vertical evacuations.

The full testing process employed to examine the implementation and impact of the developments described in this article is available in the author’s thesis [22], including: Component Testing, where individual components of the implemented model are tested to ensure they function as intended; and Functional Verification, where the model’s ability to perform simulations of hospital evacuation is analysed; i.e. to verify the collective performance of the different model components. This test compares the predictive capability of the new functionality with results produced by manually configuring the simulation tool (that act as a proxy for real-world expectation). For each test, qualitative and/or quantitative verification was conducted to compare the simulation model against experimental data presented in this paper, as briefly outlined here.

It should be noted that genuine validation data are not available. There is no extant data-set that sufficiently documents a full-scale case, including the individual devices used, the scenario, the procedure and the overall evacuation performance for an instructive validation test to be performed. The approach adopted here is designed to test the new modelling functionality, to ensure that the theoretical model functions as designed, and replicates the benchmark data from the Ghent trials individually and in a hypothetical test case employing user-driven model results derived from the experimental observations as a proxy for a real-world benchmark. This last test is particularly important as it shows that the model might operate equivalently to an expert user manually approximating the experimental data.

This work represents an attempt to simulate the movement of PRM during an evacuation given the use of movement devices. It does this by representing the presence and movement of the device itself (given the building geometry), the procedural requirements of the devices (i.e. the number and identity of staff), the vertical and horizontal movement rates achievable by the device when being moved, and the interruptions of this movement due to staff stopping through fatigue. The combination of these elements was previously not satisfactorily represented in evacuation simulation tools, which had previously only represented the reduction in travel speed and/or the physical presence of a device independent of geometrical or procedural elements. The capacity to simulate this process in a more representative manner is more likely to capture the movement of PRM (and associated staff) during an emergency evacuation procedure and also the impact of this movement on other evacuees. This should help ensure that the simulation process (although still a simplification) excludes fewer factors that inhibit evacuation performance and is less likely to produce unduly optimistic predictions.

It is acknowledged that, although this effort represents an important step in the simulation of PRM movement, more work is required. The process of development has also highlighted other model developments that may be considered to further enhance the functionality: the representation of patient preparation from varying initial positions (e.g. lying down) and the attachment of medical equipment; the adjustment of speeds in light of new performance factors such as levels of training, device weight, handler fatigue, and the different physical capabilities within a handling team; and the behaviours of evacuees travelling alongside and overtaking devices in a dense flow. Better information about device acceleration, momentum and braking would also support an improved model of device movement.

A worthwhile development would be adaptable agent itineraries to enable the simulation of agents who are not staff (e.g. visitors and other hospital staff) to aid in the assistance of PRM. Furthermore, itineraries that are conditional on a developing situation, or based on communication between agents would greater represent the reality of hospital procedures, particularly the communication and interaction between hospital staff and emergency responders.

As noted previously, the advances made during this work can also be extended to non-healthcare environments to address the presence of luggage, prams, mobility scooters, etc. This work is ongoing.

Hospitals are complex spatial environments, and evacuations require moving vulnerable occupants to a place of safety. It is critical to understand the performance of vertical evacuation strategies, particularly the means by which people with reduced mobility can be assisted in stair descent. This paper outlined the algorithms implemented to explicitly represent the dynamics of evacuation devices within evacuation software.

The model developed in this work specified movement devices in terms of the parameters identified in the experimental data. Devices are specified using rectangular vertices, sufficient for approximating wheelchairs, beds, stair movement devices, and other medical equipment. Experimental data were also associated with the object to indicate the speed at which it travels, associated preparation times, as well as the size and space it occupies and the number of handlers required. Algorithms were presented that enable devices to move within a fine-node system, to navigate alongside other agents on a flat surface and on stairs, and to manoeuvre corners and doorways during the simulation in accordance with the data collected. The gender of the handlers informed the speeds applied. A stopping model is also presented, to represent the devices stopping periodically within the stairwell, as indicated by the experimental results. Numerous quantitative and qualitative testing was conducted. This demonstrated that the model developed as part of this work is effective in reproducing the hospital evacuation behaviour observed in the data collected during this work (e.g. during the Ghent trials) and that it is suitable for application within broader hospital scenarios.

Prior to the data collected during the Ghent trials, there were insufficient data to understand and quantify the performance of evacuation devices. Although further work is still required, the data collected has significantly enhanced understanding and capacity to quantify the performance of a number of different devices. Importantly, it also enabled the explicit simulation of this performance within an evacuation model. This is a significant and novel development, given the functionality that had to be introduced to cope with the procedural, navigational and geometric aspects of the use of the device. This has now been achieved and demonstrated to adequately represent the real-world behaviour being simulated.

This enhancement now allows practitioners and interested parties to test the use of evacuation devices as part of different hospital evacuation procedures and their impact (positive or negative) on overall performance—and to quantify the factors that influence this performance. This significantly enhances planning and diagnostic capabilities of the model within hospital and other healthcare facilities. This forecasting capacity enables insight to be gained prior to the implementation of a new procedure, a new building design or the use of new devices. As such, it should help ensure that the adoption of new designs is better informed and that risk assessments and evidence-based analyses are better supported in the future.