Reena Valand

Health Education East Midlands

This work has been made possible thanks to the collaborative effort of the following:

http://emhiec.co.uk/projects-2012-2013/em24-night-shift/

In response to this, simulations have become increasingly more common, with virtual simulations particularly appealing as they have the potential to prepare people and improve performance [6].

Recent development in local information technology enables the accurate recording of data on the out-of-hours work junior doctors undertake. [7], building up a picture of a ‘typical’ OOH shift.

Using these data, a task simulation, entitled ‘Night Shift’ has been produced.

This tool can be used to provide additional training for newly qualified doctors and increase their preparedness for out-of-work hours.

Feedback gathered from surveys and focus groups determined the simulation would focus on task prioritisation and route planning. ‘Night Shift’ was developed to provide a time compressed replication of a typical out-of-hours shift that a junior doctor might undertake.

Wireframe CAD map data of Nottingham City Hospital was obtained by the medical contributors. Software developers exported this to the software to provide a top-down view of the hospital layout. (See Fig. 1).

Tasks are assigned to users at random points at the start and throughout the simulation shift. Users are required to navigate to the location of the tasks. The goal of the simulation is to attend to high urgency ‘red’ tasks as quickly as possible to prevent these from deteriorating to high-urgency status.

Fig. 1. Still image from a development version of the simulation showing a top-down view of Nottingham City Hospital corridors

Insert ‘Night Shift’ game here

Participants in the intervention group completed their non-urgent tasks more rapidly than the control group, though there was a broad range of completion times.

There was no difference in the time to complete urgent tasks.

Those in the intervention group undertook fewer tasks per shift than those in the control group (8.5 versus 12) but this was not statistically significant (p=0.290).

Short-comings of the educational tool Users of the simulation reported having difficulty in navigating using a top-down view and a static set of

pictures relating to what the user would see at that location. Users recognised that hospitals have a plethora of signs, but felt the level of visual information provided was too simple.

Users were frustrated by the ‘fatigue’ element of the simulation. This was included to convey the loss of function that occurs if junior doctors do not take breaks. Evidently, slower walking pace and gradual darkening of the screen was not the best way to convey this, and will be addressed in later versions.

The feedback element of the simulation was also limited, and provided users with data rather than a clear context of how this differed from optimal performance and how deficiencies might be practically addressed.

Actual difficulties of working OOH This area of feedback is related to realistic aspects of the night shift.

The simulation involved a great deal of walking around in comparison to the medical activity undertaken. Despite this being realistic, it ultimately reduced engagement in the activity.

Students also reported that it was impossible to attend to multiple urgent tasks that appeared in a short time window. This is representative of actual shifts rather than a game where one can ‘win’.

This highlights a key issue with the representations of real-world tasks within serious games or simulations.

It is possible that engagement with the task simulation increases familiarity of users with the hospital layout, potentially having a positive effect on the user’s ability to prioritise non -urgent tasks on the basis of optimal planning.

Junior doctors are already highly trained to prioritise and complete urgent tasks in real life, and it is therefore hypothesized that this may be the reason for why a significant change in performance completing urgent tasks was not found.

This pilot study has demonstrated the possibility to utilise newer streams of clinical data to produce a task simulation that can be used to train junior doctors in non-technical skills.

A key strength to this piece of work is its innovative use of high-volume task level data and precise mapping to inform the underlying mechanics of a simulation.

Furthermore, the project benefitted greatly from the collaborative effort working with doctors, nurses, hospital managers, IT specialists, engineers and human factors experts with a commercial software developer partner.

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[7] J.D. Blakey, A Fearn, and D. Shaw. What drives the ‘August effect’? A observational study of the effect of junior doctor changeover on out of hours work. J R Soc Med Sh Rep Open, vol. 4(1:7), Aug. 2013.