Health Service Modelling Associates Programme
PenCHORD (the Peninsula Collaboration for Health Operational Research and Data Science) is one of the teams of PenARC.
PenCHORD began in 2010, and has worked with hundreds of local and national partners to use modelling and data science approaches to improve the operational delivery of health and social care services.
Our work is
Using simulation, machine learning and geographic modelling techniques to improve clinical pathways
The SAMueL project is using ML to predict which stroke patients should receive clot-busting treatment
Supporting modellers and data scientists to make their work more open and reproducible
The STARS project is developing guidelines for how to share models to allow them to be used and reused effectively
And…
The Health Service Modelling Associates is a 15 month data science and operational research training and mentoring programme.
Supported by the NIHR PenARC and the NHS Digital Academy, the full programme is provided free of charge to people working in health, social care and policing and is accredited by AphA.
Visit Our Website hsma-programme.github.io/hsma_site
Subscribe to our YouTube Channel youtube.com/@hsma
Follow us on GitHub github.com/hsma-programme
The full HSMA experience is a live, 15-month programme with two distinct phases.
PHASE 1 - 6 month training phase
Participants learn the Python programming language, before progressing through simulation modelling, mapping, machine learning, natural language processing, website development, reproducible reporting, forecasting, and more.
Participants are released from their usual role for one day a week, joining the HSMA trainers online for live lectures and group work.
PHASE 2 - 9 month project phase
Participants are supported to produce a project using the new skills they have learned, applying operational research and data science techniques to a real problem within their organisation.
Participants are expected to spend at least one day a week working on their project during this phase.
Our HSMA Community has now grown to several hundred people across 6 cohorts.
You probably have HSMA alumni in your organisation who can do amazing things if asked the right questions!
Find out more about the HSMA Programme and our projects on the HSMA website
In today’s workshop, we’re running an interactive taster session of HSMA training content drawn from the Discrete Event Simulation (DES) module of our training programme.
You can view the interactive version of these slides at bit.ly/rke-des-slides
Before we start, let’s find out a little bit about you…
Raise your hand if you’ve heard of discrete event simulation before
Raise your hand if you are in an analyst, data scientist or data engineer-type role
Raise your hand if you know some Python or R
Your emergency department is struggling.
You could try a range of different things…
Which of these is the right answer?
Healthcare tends to be full of queueing problems like this one.
Healthcare systems are full of resources
These resources experience demand from entities.
These entities might be
As these entities move through a pathway - a series of steps where these resources are used - queues can build up where there isn’t enough resource.
And these pathways are often very complicated!
There are lots of moving parts, and lots of variation.
Variation in when, and how frequently, people arrive
Variation in how long an activity in the pathway takes
Variation in the pathways people take within a single system
Making changes to pathways can be
And even if you do fix the original problem you were trying to solve, there’s a risk of knock-on effects elsewhere in the pathway that you didn’t foresee.
And even if you avoid that….
A system that is coping now might not cope
On HSMA, we teach a couple of different computer simulation techniques.
High-level technique that’s often suited to uncovering fundamental issues with pathway or wider healthcare system design
Individual-level modelling that is particularly interested in the impact of individuals’ decisions and interactions
Modelling focussing on the flow of entities through a pathway and use of resources, allowing detailed investigation of capacity, queues and waits
What we generally want to tackle our pathway problems in healthcare is Discrete Event Simulation (DES)
In a DES…
DES is so powerful because it gives us an in-silico (computer-based) reproduction of our pathway to play around with.
We can make any change we want
(e.g. more resources, higher demand, new pathway design)
safely and for free and see what impact it has on any metric we care to measure:
And so on!
We’ll explore this more in the interactive part of the workshop, but for now it’s just worth mentioning that DES is also really good at dealing with variation.
Instead of just planning on averages - like the average length of stay, or the average number of people who are referred each month, we can take into account the real-world variation seen, and play out many different possible futures…
Your DES won’t be a perfect one-to-one reproduction of the pathway you are modelling.
We have to make certain assumptions and simplifications, and we can’t capture every complexity.
However…
All models are wrong, but some are useful
• George E. P. Box
In this PenCHORD project, a DES model of the bladder cancer pathway at Royal Cornwall Hospitals Trust (RCHT) exposed two key system bottlenecks.
The model was used to support an on-the-spot rewrite of the pathway, resulting in multi-week reductions to waiting times.
Find Out More
This HSMA project looked at the design of a COVID-19 vaccination clinic in North Devon, exploring
The model identified potential issues with the original proposed plans, and was used to refine the plans to enable a safe but efficient delivery of the vaccination programme.
Find Out More
This HSMA project looked at ways to improve Urgent Treatment Care (UTC) performance. The team wanted to know
The model identified a need for additional rooms and the ED was redesigned as a result.
Find Out More
This HSMA project created a model of a paediatric neurodevelopmental (ADHD + autism) pathway. Waits had increased to a 2 years on average.
The team wanted to understand
The model showed that recruiting an extra lead clinician would not address the bottleneck - but an additional second assessor would.
You can find details about all of our previous and current Discrete Event Simulation projects on the HSMA website