2. Introduction of 111 to Wales
a. Background
The second one is more of a national program. It relates to 111 call center service coming to Wales. At the time of the study, Wales did not have 111 like England. It was a little bit wary about rolling out the program so decided to do it step by step, health board by health board. This project was actually right at the start with the first health [10.00] board – actually, just ahead of the first health board going live – and analyzing all of their data and producing some simulation models for it.
The first health board that conducted the pathfinder project was Abertawe Bro Morgannwg University (ABMU) Health Board, which is the health board around Swansea. We were asked to look at the call volume data for GP Out of Hours and NHS Direct Wales. The idea was that the [10.00] call volumes from each of those two services would combine when they come through to 111.
The two current systems were run quite differently. NHS Direct Wales runs 24 hours a day, whereas the GP Out of Hours only runs in the evenings and at weekends, and we have different types of staff looking after each service. We wanted to look at the call volumes and look at the staffing rotas as well when we combined the two services. [11.00]
b. Execution
In order to do that we had the data from both NHS Wales for the whole of Wales and the Out of Hours call volumes for each of the seven health Boards. In total, for a year’s worth of data, we were looking at about 800,000 call volume. We initially divided it into the two systems so we could produce simulation models for each. We then developed a combined model, which [11.00] we ran as a baseline, and then we could alter different sections of it to see what staff did what, and what effect it would have.
c. Output
This is a screenshot of the initial simulation model that we had for NHS Direct Wales. Each of the icons relates to the staff that handled the call at that time and the icons along the bottom are the outcomes, so it may be a call to a GP was needed afterwards or [12.00] the patient was referred to A&E or they could look after themselves at home. Quite a lot of options with NHS Direct.
We had a similar model that we built for the GP Out of Hours Service. Each of those was separate for each health board. We were then lucky enough to have an MSc student over the summer who combined the NHS Direct Model and GP out of Hours into one easy to use [12.30] model.
This side are all the different call volume types that come in from NHS Direct and GP Out of Hours. These are the processes that the calls go through depending on what type of call they are. This is a checking mechanism to make sure we had not lost any calls, and then we have the staffing resources along the bottom, so we could see how utilized each of those staffing resources were under the scenarios.
What [13.00] was really nice about being able to do this is it allowed the 111 team the option of trying out different workforce options and costing them ahead of actually putting the figures into Welsh Government and getting the agreement to go ahead on the pathfinder project and then the actual 111 service in ABMU and now in subsequent health boards.
Just being able to develop a model and visualize it was really, really useful to them.
3. Demand and Capacity
a. Background
[13.30] The final case study is quite a new one and relates to two of the modeling fellows that we have trained in our silver modeling course, and they are looking at demand and capacity.
In particular, the Health Board have struggled, really, to understand demand on outpatient clinics; particularly as they have tended to focus on activity rather than the referral demand that comes in. By building this [14.00] simulation model, the modeling fellows have been able to look at referral patterns and they are using it to look at new and follow up appointments and the staff needed and capture the variation from week to week.
b. Methodology
The model came off the back of one that has been developed in the Health Board for ophthalmology. The modeling fellows are still in the pilot stages. They are focusing on one specialty. They have [14.30] developed the discrete model and it is using daily or weekly data depending on what the service wants to find out. In terms of the weekly model, they have also incorporated a forecasting model so that they can then forecast as well as using the simulation to show what is going to happen to demand in the future.
c. Output
This is just a screenshot of one of the subspecialties they have been working on. Essentially a booking will come in and that will generate [15.00] a new appointment for this subspecialty, arthroplasty, and then, depending on whether the patient attends their appointment or cancels it or does not attend or is discharged, it may go up into a follow up pool, and there are different outcomes for that, as well.
Quite often in outpatients, a patient may cycle through the follow up loop several times. This is why it is a useful to have simulation, [15.30] because one thing that has not been captured in the past is how many follow up appointments a patient might need off the back of a new appointment, and this is allowing the service to do that as well.
d. Findings
The modeling fellows have found it is allowing them to understand the referral demand from each subspecialty. They can see the variation, and in the plot below you can actually see the forecasting model that they have produced. [16.00] At the moment, over a three year period, it is out by about six referrals on about 36,000 datapoints, so although it does not look as though it is matching exactly here, it is actually doing really, really well, so they are pleased.
V. Observations
1. Usefulness of SIMUL8
Just to pull some thoughts together, I think we have found that SIMUL8 has been really useful for looking at very large datasets and building [16.30] models off the back of those. We have also found it very useful for when we have conducted small shadowing exercises, and then we can build a model that reflects what we are seeing there. The visualization for clinicians and managers has been really useful, because they can see what is happening in their clinics in a model and then are more likely to believe the results.
We have done quite a mixture of projects: high level models and ones that are looking at patient flow.
2. Future Plans
In the next few months we are looking at a new hospital build, and we are hoping to use SIMUL8 for part of that. We are also looking at a full cancer pathway for lung cancer. That is essentially what we have got planned and are using SIMUL8 for, so it has been an incredibly useful tool for us in the Health Board.
Questions and Answers
Tom Stephenson
It seems like you are lucky enough to work in a very talented team [18.00] with a combination of lots of different analytical skillsets. What goes into the decision criteria for you to decide to use SIMUL8 over other potential tools? What kinds of things do you look for in a project that would lead you towards SIMUL8?
Dr Tracey England
Sometimes it is a case of data quality. Sometimes it is the user specification in that they want the visual side of [18.30] things so they can present to other people; they what the ‘what if’ scenarios. Occasionally it may be just how complicated something is and whether you can break it down into smaller parts. It varies, really. The piece of work we are thinking about doing for the new hospital build is an area where we were really trying to work out which is going to be the best option on the modeling techniques, and we came up with quite a few. [19.00] We still have not decided which one we are going to go for yet.
Tom Stephenson
Okay, great. One other question: I can see that you use simulation well to answer the main questions that you have in a lot of your projects, but you also touched upon some additional benefits that came out of running a project with simulation. For example, the need to maybe shadow clinicians and things like that [19.30]. How would you always run a project to make sure that you are getting those kind of additional benefits? Would you recommend something like shadowing all the time when it is appropriate, even when you have data, for example?
Dr Tracey England
I think it is very useful to try and get at least one or two clinicians on board right at the start, and quite often they will say, ‘Come and have a look at the clinic,’ so even if [20.00] you are not formally shadowing, it is good to go and have those discussions, because quite often the data might tell you one thing, or you think it is telling you one thing, but when you actually see it in action it is very different.
It is always worth doing that shadowing side of things, because things come up that might explain where there is a blip in the data or why something just seems unusual. For instance, when we were doing the patient flow [20.30] model for the trauma clinic they actually had a nasty road traffic accident on that day, and that department would have been closed for outpatients and then would have accepted patients from the road traffic accident. That would have been a very different set of data than usual. If we had not been shadowing, we would not have known that.
Tom Stephenson
I think that would be I have seen as well. [21.00] It is always good to be able to capture information that is going to help you feed all the inputs into the model, and all the variation that we know can happen in real life to get that valid representation.
Excellent. Thanks again to you, Tracey, for presenting. Thanks, everybody, for listening.
