Here you can find details of a range of current and previously-completed HSMA projects, split by the key methods used in the project.
Click on the preview for each project to read the full details. For many completed projects, you can watch a short talk from the HSMAs who undertook the project on their plans, successes and challenges.
Discrete Event Simulation
Modelling strategies to reduce the elective backlog in hip surgery
This project used Discrete Event Simulation to model the hip surgery patient pathway in Exeter to understand the potential impact of various strategies to reduce the backlog…
• Royal Devon and Exeter NHS Foundation Trust
Developing a generic vaccination service model for the COVID-19 pandemic and beyond
In winter 2020, vaccinations had recently been approved for use in the UK to protect people against the COVID-19 virus. Consequently, a mass vaccination programme was…
Simulation modelling to test proposed models of pediatric critical care in South West England
This project used a combination of Discrete Event Simulation and Geographic Modelling approaches to determine where Level 2 Pediatric Critical Care Units should be located…
The Effect of Booked Appointments on Waiting Times at Urgent Treatment Centres
The aim of the project was to examine in more detail the question of whether booked appointment times might reduce waiting times in Urgent Treatment Centres (UTC). This was…
Use of Discrete Event Simulation to Tackle Long Waits and a Growing Backlog for Children Requiring Neuro Development Assessment (Autism and ADHD)
The aim of the project was to understand the current pathway to assessment of Autism and ADHD in children, identifying any bottlenecks. We wanted to know what change needed…
Using DES to Improve Flow through an Acute Medicine Assessment Pathway
Nottingham University Hosptials has two major Acute Medicine Assessment areas (WB3 and AMRA), where patients can be reviewed before being sent to the most appropriate…
• Sandwell and Birmingham NHS Trust
Discrete Event Simulation of Cognitive Behavioural Therapy Pathway in an IAPT Service
The aim of the project was to use Discrete Event Simulation (DES) to model the current wait list for High Intensity Cognitive Behavioural Therapy (HI-CBT). The team wanted…
• NHS Dorset
Use Of Discrete Event Simulation (DES) to reduce delays in Cancer Diagnosis & Treatment
The project aim was to develop a Discrete Event Simulation (DES) model based on Colorectal Cancer pathway at Gloucester Royal Hospital to identify the key delays within the…
• University Hospitals of Morecambe Bay NHS Trust
• Dartford and Gravesham NHS Trust
Discrete Event Simulation to Improve Flow and Performance in the Urgent Treatment Centre
The primary aim of the project was to improve Urgent Treatment Care (UTC) performance by developing a model which would help the Emergency Department (ED) team with the…
Meeting the demand of 111 for primary care services
This was an attempt to model the impact of enforcing timely primary care interventions when 111 calls are undertaken.
• Devon CCG
• University of Plymouth
The role of Patient Initiated Follow-up (PIFU) and ‘Digital Outpatients’ in Supporting the Elective Recovery - Can We Better Size Potential for Clearing the Backlog?
The aim of the project is to find out what role Patient Initiated Follow-up (PIFU) can play in the redeployment of capacity to address the backlog. This will be done by…
Using Discrete Event Simulation to model the bottlenecks in the Acute Medical Unit pathway
In this project, a computer simulation of the acute medical pathway in a Devon trust was created, along with an interactive tool allowing parameters such as the staffing levels to be changed. This allowed staff to explore the optimum levels of resourcing, enabling risk-free testing of staffing and resource changes before committing to these changes in the real-world.
Modelling the effect of complex discharge delays on acute performance
Hospitals across the country are struggling to provide patients with the care they need in a timely manner. Increasing waiting times in A&E departments, long waits for…
Discrete Event Simulation to model elective surgery pathways
The aim of the project was to create a Discrete Event Simulation in SimPy to model elective surgery pathways, which could be used to model changes to a pathway and their…
Modelling the location of neonatal critical care units in North West England
In this project, the optimum location for 22 neonatal care sites across North West England was explored.
A Discrete Event Simulation Model to reduce Rheumatology waiting times in Dorset
The current Referral to Treatment waiting list is at its highest level in NHS history. Identifying methods for reducing the waiting list and waiting times would benefit…
• BCP Council
Discrete Event Simulation modelling of Non-elective flow
Poor patient flow is leading to (very) long waits for admission in Emergency Departments. This means there is poor performance against all the key ED wait metrics for the…
Discrete Event Simulation and Artificially Intelligent Forecasting: Modelling the 62 Day Prostate Cancer Pathway
At present we’re missing the 62 day target from referral to treatment of prostate cancer. The pathway involves numerous activities such as triaging, imaging, biopsies as…
Discrete Event Simulation to model othopaedic theatre capacity optimisation
The aim of this project is to use Discrete Event Simulation to optimise theatre capacity for elective procedures and major trauma arrivals in Orthopaedics.
Discrete Event Simulation modelling of childrens ADHD diagnosis and treatment
This project is using Discrete Event Simulation to model the children’s ADHD diagnostic and treatment pathway. The model will be used to identify delays and potential…
Modelling eye injection pathways
This project aims to develop a comprehensive and flexible simulation model to optimise anti-VEGF treatment strategies in ophthalmology. The model will address the complex…
Modelling the impact of 111 and GP access on Emergency Departments
This project will use Discrete Event Simulation to model patients’ navigation of GP vs 111 services and assess the knock-on effect for Emergency Departments.
Forecasting acute bed occupancy, and simulating short term demand and capacity for acute beds
The aim of this project is to develop a tool to perform time series forecasting on bed occupancy based on historical data, incorporating variables like seasonality and…
Modelling Musculoskeletal Physiotherapy services across Exeter, Mid and East Devon
This project aims to explore the demand for and access to Musculoskeletal Physiotherapy services across Exeter, Mid and East Devon.
Referral to treatment waiting times for Neurosurgical patients
This project will aim to model the pathway for Neurosurgical patients, and to explore, based on current waiting times,
Modelling 111 option 2 call centre
We operate 2 separate 111 call centres for mental health patients (for both Norfolk and Suffolk). These are both set up in different ways (one fully staffed with ‘qualified’…
Intelligent Pathway Management
The aim of the project is to use data science techniques to quantify the impact of deviations from the “Best Case Scenario” in a patient pathway, this could be diagnostics…
Modelling delays in breast, head and neck cancer pathways
Breast cancer and head and neck cancer are two common cancer sites, where the main clinical pathway is surgery, followed by adjuvant radiotherapy or chemotherapy. Clinical…
Modelling secondary care psychological therapy flow
Poor patient pathway flow is leading to long waits for patient to receive treatment for severe and enduring mental health problems. The current focus is for Adult mental…
Modelling of theatre recovery flow requirements
Staffing levels within the recovery environment are not well defined or understood. There is minimal to no literature around minimal staffing requirements within the NHS and…
Machine learning to identify possible outpatient DNAs
This project will use Machine Learning approaches to identify possible outpatient DNAs
111 Downstream forecasting
The aim of this project is to develop a model that, based on incoming 111 calls, predicts the likely place, time and volume of downstream activity due to these calls. This…
Forecasting demand in RDUH breast care services and the impact of urban development
Historically there has been a lack of data science or accurate forecasting in developing capacity. Between 2011 and 2021 the growth in the population served by the Royal…
Using Data Science techniques to address delays in the pathway for Neurodiversity Diagnoses in Children and Young People in Devon
Currently, across multiple healthcare providers in Devon, around 6,000 children have been waiting more than 52 weeks for a neurodiversity diagnosis. These diagnoses can…
Discrete Event Simulation model to support the flow of patients through Community Diagnostic Centres
Community Diagnostic Centres (CDCs) are a relatively new implementation in the NHS, with the intention of improving patient flow and reducing waits for diagnostic tests, by…
Geographic modelling of resource utlitisation at Devon Air Ambulance
A geographical modelling project on the utilisation of resources at Devon Air Ambulance, modelling current demand and conducting what if scenarios to optimise service…
SIMPACT: Simulation of Medical Patient Admission and Care Throughput
More information coming soon!
Modelling resourcing scenarios to meet increases in demand on a Devon eye clinic
More information coming soon!
Machine learning
Exploring the use of Machine Learning and Natural Language Processing to teach a machine to predict whether a patient is likely to be imminently admitted to hospital based on GP data and clues in GP notes
This exploratory project explored the use of Natural Language Processing methods to automate the extraction of key information from free-text patient notes in order to…
• Peninsula Dental School
• Royal Devon and Exeter NHS Foundation
Forecasting Demand and Length of Stay in the Emergency Department
The project aimed to use forecasting and machine learning methods to predict the length of stay and arrivals to the Emergency Department (ED) at different times of day, days…
Using Machine Learning to Predict Hospital Admissions and Length of Stay for Respiratory Conditions
The aim of the project was to use available Primary and Secondary Care patient history and demographic information to better predict the chance of admission for respiratory…
Predicting Non-Elective Admissions
The project aim was to develop a predictive model to identify patients at high risk of admission and to provide explanatory feedback as to why the patients were at risk.…
• NHS North East London CSU
Predicting Violent Incidents on Mental Health Inpatient Units
The aim of the project was to see if the occurrence of violent incidents on hospital wards could be reduced, if incidents could be pre-empted and interventions could be…
Developing a Service Planning Decision Support Tool to Tackle Inequalities and Minimise Carbon Output
There are three current significant health agendas to which this project broadly relates.
• Torbay Council
• West Sussex County Council
Using Machine Learning to estimate inequities in access to hospital procedures
The aim of this project was to determine on an ICB, LTLA and UTLA the overall level of disparity in accessing planned appointments in hospital. The team did this for each…
Forecasting Demand – Investigating approaches to forecast clock starts
Within the organisation (NHS England) forecasting for clock starts is currently done using scenario-based modelling in Excel. This limits how much data can be used to make…
• NHS North of England Commissioning Support Unit
Investigating factors impacting NHS workforce retention
This project aimed to work out which factors are the biggest drivers of staff turnover using regression modelling on staff workforce figures as well as other local factors such as employment. This was turned into a dashboard for internal use. However, it was concluded that the currently available data only acccounted for 13% of the variation in turnover seen; more data on other factors is required to explain the patterns seen.
• Yorkshire Ambulance Service
Using Machine Learning and Explainable AI to predict and understand mental health appointment DNAs to reduce inequalities
As a provider of Mental Health Services for SMI, Lancashire & South Cumbria NHS Foundation Trust is committed to helping to deliver the aims of Core20Plus5. Core20PLUS5 is a…
Geographic and Boosted Tree Modelling of Healthcare worker vaccination uptake
There is low uptake of Healthcare Workers for COVID and Flu, which is in many Trusts decreasing with each season.
Improving ambulance care via fast feedback from Quality Care Indicators
Our aim is to improve Ambulance Clinical Quality Indicators (ACQI) data quality and rapidly provide feedback from all ACQI records. There is potential for this tool to be…
Using machine learning models to predict future frailty
This project will use machine learning methods to estimate the size of the Wakefield District population who will likely be frail in 2 / 3 / 4 years time, and to understand…
Understanding drivers of increased length of stay
NCL has observed a consistent increase in long Length of Stay (LoS) over the past 5 years. Increasing length of stay means a higher capacity is needed for the same demand…
Using classification modelling technques to investigate changes in Healthcare Resources Group (HRG) coding over time
The Medium-Term Activity Projections (MTAP) model produces a set of baseline activity and price-weighted contact projections to 2040/41 for NHS England for some types of…
Forecasting acute bed occupancy, and simulating short term demand and capacity for acute beds
The aim of this project is to develop a tool to perform time series forecasting on bed occupancy based on historical data, incorporating variables like seasonality and…
Predicting the risk of injurious falls in older people with atrial fibrillation
Atrial fibrillation (AF) is a common cardiac arrhythmia which increases the risk of stroke.
Predicting Gestational Diabetes and other maternity-related conditions using machine learning
Maternity-related conditions, such as gestational diabetes, can have significant impacts on the health of both the mother and baby if not identified early. Current…
Pharmacy Clinical prioritisation tool
As with many other parts of the NHS we have significant workforce challenges meaning that the clinical team can often not interact with as many patients as they would like.…
Modelling of theatre recovery flow requirements
Staffing levels within the recovery environment are not well defined or understood. There is minimal to no literature around minimal staffing requirements within the NHS and…
Machine learning to identify possible outpatient DNAs
This project will use Machine Learning approaches to identify possible outpatient DNAs
Exploring factors that impact Opiate Cessation using explainable machine learning
Many patients prescribed opiate medication for acute pain relief end up taking the medication for many years, leading to adverse events, dependence and tolerance. There is…
111 Downstream forecasting
The aim of this project is to develop a model that, based on incoming 111 calls, predicts the likely place, time and volume of downstream activity due to these calls. This…
Forecasting blood donation session capacity
Blood donation sessions have limits of how many people will be able to attend a session. Bookings for sessions often don’t convert into actual donations due to…
Evaluating the use of machine learning calssifiers for the identification of the determinants of stage at diagnosis of prostate cancers using registry data
This project will use a selection of ML methods to try to classify whether a given patient is diagnosed at an early or late stage of prostate cancer using a selection of…
Identifying which patients are most at risk for an outcome across integrated neighbourhood teams
Population health management often use population segmentation to categorise the population according to health status, health care needs and priorities. This approach…
Using Data Science techniques to address delays in the pathway for Neurodiversity Diagnoses in Children and Young People in Devon
Currently, across multiple healthcare providers in Devon, around 6,000 children have been waiting more than 52 weeks for a neurodiversity diagnosis. These diagnoses can…
Predictive modelling for smoking cessation success
Smoking is a leading cause of preventable diseases and deaths worldwide. Despite numerous public health campaigns and interventions, smoking cessation remains a significant…
Population segmentation of GP-registered population in Dorset
The aim of this project is to create a machine learning-based population segmentation model for the GP-registered Dorset population using multiple characteristics including…
Proactive Patient Attendance Prediction: Enhancing Healthcare Efficiency through Attendance Forecasting
Every month ~ 12% of outpatient appointments are not attended at Barts Health NHS Trust. This equates to over 10 thousand hours of clinical input, space and equipment that…
RALPulator : Predicting Robotic-assisted laparoscopic prostatectomy (RALP) operative times from patient letters
This project is building an app that reads in patient letters ahead of surgery, uses Natural Language Processing techniques to extract key information from the text, and…
Identifying potential concurrent treatment areas and services that would better support patients with multiple, complex referral to treatment (RTT) pathways.
The aim of this project is to use machine learning approaches to support analysis of patients with multiple concurrent RTT pathways, focusing particularly on healthcare…
Using machine learning to identify factors that increase number of appointments per pathway
The new EPP data set combines data to create the most complete version of elective pathway activity we have ever had. At the moment we don’t know why some people/pathways…
Analysis and prediction of seasonality in pathologies requiring ITU admission
Anecdotally, many intensive care clinicians know that admission causes follow specific patterns, for example we see more cardiac arrests in summer, more pancreatitis in…
Using Machine Learning to predict whether a patient might develop a SSI (Surgical Site Infection)
More information coming soon!
Natural Language Processing
What are they saying about us? An AI tool to determine the sentiment of tweets to police forces across the country, and what people are talking about
This project used AI-based Natural Language Processing methods to develop a dashboard that predicts the sentiment (positive or negative) of every tweet to every police force…
Exploring the use of Machine Learning and Natural Language Processing to teach a machine to predict whether a patient is likely to be imminently admitted to hospital based on GP data and clues in GP notes
This exploratory project explored the use of Natural Language Processing methods to automate the extraction of key information from free-text patient notes in order to…
• Peninsula Dental School
• Royal Devon and Exeter NHS Foundation
Predicting Non-Elective Admissions
The project aim was to develop a predictive model to identify patients at high risk of admission and to provide explanatory feedback as to why the patients were at risk.…
• NHS North East London CSU
Using Natural Language Processing to detect drug related content within free text
Since the amount of data being collected and stored has increased significantly, datasets are often reviewed manually, particularly when free text fields are present. This…
• Derbyshire Police
• Greater Manchester Police
Improving ambulance care via fast feedback from Quality Care Indicators
Our aim is to improve Ambulance Clinical Quality Indicators (ACQI) data quality and rapidly provide feedback from all ACQI records. There is potential for this tool to be…
Clinical coding automation using Natural Language Processing
The aim of this project is to use Natural Language Processing (NLP) to predict ICD-10 or OPCS-4 codes from doctor/patient notes, automating a task currently done manually by…
Applying Natural Language Processing to automate the extraction and classificiation of congenital anomaly diagnoses from free text and genetic data
Congenital anomaly diagnoses can be submitted to the National Congenital Anomaly and Rare Diseases Services (NCARDRS) under an unspecific and uninformative ICD10 code of…
Using Data Science techniques to address delays in the pathway for Neurodiversity Diagnoses in Children and Young People in Devon
Currently, across multiple healthcare providers in Devon, around 6,000 children have been waiting more than 52 weeks for a neurodiversity diagnosis. These diagnoses can…
RALPulator : Predicting Robotic-assisted laparoscopic prostatectomy (RALP) operative times from patient letters
This project is building an app that reads in patient letters ahead of surgery, uses Natural Language Processing techniques to extract key information from the text, and…
Mapping and Location Optimisation
Simulation modelling to test proposed models of pediatric critical care in South West England
This project used a combination of Discrete Event Simulation and Geographic Modelling approaches to determine where Level 2 Pediatric Critical Care Units should be located…
Reducing Travel Times to Treatment for Cardiac Patients in the South East of England
The aim of the project was to employ geographical and statistical analysis of past and present travel times to understand the impact the flow of activity into London has on…
• NHS England and Improvement
• The Strategy Unit
Spatial Modelling of Violent Crime to Support Strategic Analysis
The aim of this project was to use various crime data variables and spatial analysis to turn them into useful insights for inclusion in assessed intelligence reporting.
• Devon and Cornwall Police
• Devon County Council
Modelling the location of neonatal critical care units in North West England
In this project, the optimum location for 22 neonatal care sites across North West England was explored.
Developing a tool to assess inequalities and demographic coverage of service locations
This project hopes to empower NHS service providers with a tool that grants a deeper understanding of the population they serve and allows them to direct future service…
• Wessex AHSN
• Nottingham University Hospitals NHS Trust
Using Machine Learning and Explainable AI to predict and understand mental health appointment DNAs to reduce inequalities
As a provider of Mental Health Services for SMI, Lancashire & South Cumbria NHS Foundation Trust is committed to helping to deliver the aims of Core20Plus5. Core20PLUS5 is a…
Modelling Musculoskeletal Physiotherapy services across Exeter, Mid and East Devon
This project aims to explore the demand for and access to Musculoskeletal Physiotherapy services across Exeter, Mid and East Devon.
Optimising the location of Breast Cancer diagnostic services across Devon
Over 6000 patients a year are referred to RD&E and NDDH for fast-track breast symptom diagnosis. The fast-track clinic requires a clinician, a mammography team and a…
Identifying unpaid carers in Norfolk
There are thousands of unpaid carers. Among many other risks, unpaid carers are likely to experience poor mental health, loneliness and isolation. Supporting the mental and…
Mapping health inequalities, depreviation, ethnicities and crime across the UK
The aim of the project is to use ONS data around ethnicities of population, health index England, Deprivation data from QOF, and overlay the same with crime statistics at a…
Geographical mapping in specialist palliative and end of life care
Using national health and census data, the aim of this project is to use geographic mapping to show if we are caring for a fair representation of our population. The two…
Forecasting
South East Regional Covid 19 Vaccination Demand & Capacity Modelling
The aim of the project was to create an easy to use model for predicting demand and capacity for Covid vaccinations.
• Surrey and Borders Partnership NHS Trust
Forecasting Demand and Length of Stay in the Emergency Department
The project aimed to use forecasting and machine learning methods to predict the length of stay and arrivals to the Emergency Department (ED) at different times of day, days…
Forecasting Demand – Investigating approaches to forecast clock starts
Within the organisation (NHS England) forecasting for clock starts is currently done using scenario-based modelling in Excel. This limits how much data can be used to make…
• NHS North of England Commissioning Support Unit
Understanding Excess Mortality in Dorset
The project was based on the Dorset ICS (Integrated Care Systems) Health Inequalities programme aim to improve access, enhance the experience of services for everyone.…
Forecasting modelling for A&E attendance
The aim of this project is to forecast future A&E attendances 6 weeks in advance, accounting for seasonal patterns.
Forecasting acute bed occupancy, and simulating short term demand and capacity for acute beds
The aim of this project is to develop a tool to perform time series forecasting on bed occupancy based on historical data, incorporating variables like seasonality and…
Forecasting the supply of medical doctors
The problem: Not enough medical doctors by region and we need to establish the gap between what we have and what we need.
Modelling 111 option 2 call centre
We operate 2 separate 111 call centres for mental health patients (for both Norfolk and Suffolk). These are both set up in different ways (one fully staffed with ‘qualified’…
Predicting the future demand for Renal replacement therapy
The problem: Kidney disease is projected to be the fifth leading cause of premature deaths globally by 2040. With people living longer and having more comorbidities, the…
111 Downstream forecasting
The aim of this project is to develop a model that, based on incoming 111 calls, predicts the likely place, time and volume of downstream activity due to these calls. This…
Forecasting demand in RDUH breast care services and the impact of urban development
Historically there has been a lack of data science or accurate forecasting in developing capacity. Between 2011 and 2021 the growth in the population served by the Royal…
Forecasting NHS planning and performance metrics
The ICB leads on development of Operational Planning submissions to NHS England on an annual basis. This involves development trajectories against various activity and…
Discrete Event Simulation model to support the flow of patients through Community Diagnostic Centres
Community Diagnostic Centres (CDCs) are a relatively new implementation in the NHS, with the intention of improving patient flow and reducing waits for diagnostic tests, by…
Analysis and prediction of seasonality in pathologies requiring ITU admission
Anecdotally, many intensive care clinicians know that admission causes follow specific patterns, for example we see more cardiac arrests in summer, more pancreatitis in…
Geographic modelling of resource utlitisation at Devon Air Ambulance
A geographical modelling project on the utilisation of resources at Devon Air Ambulance, modelling current demand and conducting what if scenarios to optimise service…
Reporting Automation Projects
Developing a Service Planning Decision Support Tool to Tackle Inequalities and Minimise Carbon Output
There are three current significant health agendas to which this project broadly relates.
• Torbay Council
• West Sussex County Council
Creating a tool to automatically generate health equity audits for Community Diagnostic Centres
Community diagnostic centres (CDCs) have been launched across England to tackle the diagnostic backlog and address healthcare inequalities. CDCs and commissioners struggle…
• Reading Borough Council
Forecasting modelling for A&E attendance
The aim of this project is to forecast future A&E attendances 6 weeks in advance, accounting for seasonal patterns.
Modelling 111 option 2 call centre
We operate 2 separate 111 call centres for mental health patients (for both Norfolk and Suffolk). These are both set up in different ways (one fully staffed with ‘qualified’…
Analysis and prediction of seasonality in pathologies requiring ITU admission
Anecdotally, many intensive care clinicians know that admission causes follow specific patterns, for example we see more cardiac arrests in summer, more pancreatitis in…
Automating and scaling waiting list equity analysis at a trust level
More information coming soon!
Network Analysis
Generating a richer understanding of relationships in crime data in order to identify opportunities to safeguard individuals and families
This project used Network Analysis methods to identify the social relationships between groups of people who could be causing significant issues within their communities…
Meeting the demand of 111 for primary care services
This was an attempt to model the impact of enforcing timely primary care interventions when 111 calls are undertaken.
• Devon CCG
• University of Plymouth
Network Analysis of diagnostic procedures in A&E setting
In A&E a patient can be given one or more diagnostic procedures. These can be as simple as the various blood test or more complicated procedures like an MRI test. The aim of…
Agent-Based Simulation (ABS)
Modelling eye injection pathways
This project aims to develop a comprehensive and flexible simulation model to optimise anti-VEGF treatment strategies in ophthalmology. The model will address the complex…
Modelling of theatre recovery flow requirements
Staffing levels within the recovery environment are not well defined or understood. There is minimal to no literature around minimal staffing requirements within the NHS and…
Using Agent Based Simulation to understand criminal adoption of new technologies
I work in a field that researches the use of technology by criminals. Often, we want to understand how the use and behaviours for a new technology might develop, or have…
System Dynamics
Understanding drivers of increased length of stay
NCL has observed a consistent increase in long Length of Stay (LoS) over the past 5 years. Increasing length of stay means a higher capacity is needed for the same demand…
Projects with a Streamlit Interface
Forecasting Demand and Length of Stay in the Emergency Department
The project aimed to use forecasting and machine learning methods to predict the length of stay and arrivals to the Emergency Department (ED) at different times of day, days…
Reducing Travel Times to Treatment for Cardiac Patients in the South East of England
The aim of the project was to employ geographical and statistical analysis of past and present travel times to understand the impact the flow of activity into London has on…
• NHS England and Improvement
• The Strategy Unit
Using Discrete Event Simulation to model the bottlenecks in the Acute Medical Unit pathway
In this project, a computer simulation of the acute medical pathway in a Devon trust was created, along with an interactive tool allowing parameters such as the staffing levels to be changed. This allowed staff to explore the optimum levels of resourcing, enabling risk-free testing of staffing and resource changes before committing to these changes in the real-world.
Discrete Event Simulation to model elective surgery pathways
The aim of the project was to create a Discrete Event Simulation in SimPy to model elective surgery pathways, which could be used to model changes to a pathway and their…
Modelling the location of neonatal critical care units in North West England
In this project, the optimum location for 22 neonatal care sites across North West England was explored.
Creating a tool to automatically generate health equity audits for Community Diagnostic Centres
Community diagnostic centres (CDCs) have been launched across England to tackle the diagnostic backlog and address healthcare inequalities. CDCs and commissioners struggle…
• Reading Borough Council
Understanding Excess Mortality in Dorset
The project was based on the Dorset ICS (Integrated Care Systems) Health Inequalities programme aim to improve access, enhance the experience of services for everyone.…
Developing a tool to assess inequalities and demographic coverage of service locations
This project hopes to empower NHS service providers with a tool that grants a deeper understanding of the population they serve and allows them to direct future service…
• Wessex AHSN
• Nottingham University Hospitals NHS Trust
Discrete Event Simulation modelling of Non-elective flow
Poor patient flow is leading to (very) long waits for admission in Emergency Departments. This means there is poor performance against all the key ED wait metrics for the…
Discrete Event Simulation and Artificially Intelligent Forecasting: Modelling the 62 Day Prostate Cancer Pathway
At present we’re missing the 62 day target from referral to treatment of prostate cancer. The pathway involves numerous activities such as triaging, imaging, biopsies as…
Discrete Event Simulation to model othopaedic theatre capacity optimisation
The aim of this project is to use Discrete Event Simulation to optimise theatre capacity for elective procedures and major trauma arrivals in Orthopaedics.
Discrete Event Simulation modelling of childrens ADHD diagnosis and treatment
This project is using Discrete Event Simulation to model the children’s ADHD diagnostic and treatment pathway. The model will be used to identify delays and potential…
Modelling eye injection pathways
This project aims to develop a comprehensive and flexible simulation model to optimise anti-VEGF treatment strategies in ophthalmology. The model will address the complex…
Understanding drivers of increased length of stay
NCL has observed a consistent increase in long Length of Stay (LoS) over the past 5 years. Increasing length of stay means a higher capacity is needed for the same demand…
Forecasting acute bed occupancy, and simulating short term demand and capacity for acute beds
The aim of this project is to develop a tool to perform time series forecasting on bed occupancy based on historical data, incorporating variables like seasonality and…
Modelling Musculoskeletal Physiotherapy services across Exeter, Mid and East Devon
This project aims to explore the demand for and access to Musculoskeletal Physiotherapy services across Exeter, Mid and East Devon.
Referral to treatment waiting times for Neurosurgical patients
This project will aim to model the pathway for Neurosurgical patients, and to explore, based on current waiting times,
Modelling 111 option 2 call centre
We operate 2 separate 111 call centres for mental health patients (for both Norfolk and Suffolk). These are both set up in different ways (one fully staffed with ‘qualified’…
Intelligent Pathway Management
The aim of the project is to use data science techniques to quantify the impact of deviations from the “Best Case Scenario” in a patient pathway, this could be diagnostics…
Predicting Gestational Diabetes and other maternity-related conditions using machine learning
Maternity-related conditions, such as gestational diabetes, can have significant impacts on the health of both the mother and baby if not identified early. Current…
Developing a streamlit app for creating Theographs of patient journeys
The aim of this project is to create an open source application to generate interactive theograph visuals to understand a patients’/clients’ journey through a system.
Pharmacy Clinical prioritisation tool
As with many other parts of the NHS we have significant workforce challenges meaning that the clinical team can often not interact with as many patients as they would like.…
Forecasting blood donation session capacity
Blood donation sessions have limits of how many people will be able to attend a session. Bookings for sessions often don’t convert into actual donations due to…
Developing a web app to recommend appropriate technology enabled care
The growing importance of Technology Enabled Care (TEC) in today’s health and social care environment, especially with the increasing aging population and the need for…
Forecasting demand in RDUH breast care services and the impact of urban development
Historically there has been a lack of data science or accurate forecasting in developing capacity. Between 2011 and 2021 the growth in the population served by the Royal…
Applying Natural Language Processing to automate the extraction and classificiation of congenital anomaly diagnoses from free text and genetic data
Congenital anomaly diagnoses can be submitted to the National Congenital Anomaly and Rare Diseases Services (NCARDRS) under an unspecific and uninformative ICD10 code of…
Modelling the benefit of MECC (Making Every Contact Count) Training using agent based simulation
Making Every Contact Count (MECC) is an e-learning programme in which health and social care staff are encouraged to use various interactions with patients to open…
Identifying which patients are most at risk for an outcome across integrated neighbourhood teams
Population health management often use population segmentation to categorise the population according to health status, health care needs and priorities. This approach…
RALPulator : Predicting Robotic-assisted laparoscopic prostatectomy (RALP) operative times from patient letters
This project is building an app that reads in patient letters ahead of surgery, uses Natural Language Processing techniques to extract key information from the text, and…
Identifying potential concurrent treatment areas and services that would better support patients with multiple, complex referral to treatment (RTT) pathways.
The aim of this project is to use machine learning approaches to support analysis of patients with multiple concurrent RTT pathways, focusing particularly on healthcare…
Discrete Event Simulation model to support the flow of patients through Community Diagnostic Centres
Community Diagnostic Centres (CDCs) are a relatively new implementation in the NHS, with the intention of improving patient flow and reducing waits for diagnostic tests, by…
Analysis and prediction of seasonality in pathologies requiring ITU admission
Anecdotally, many intensive care clinicians know that admission causes follow specific patterns, for example we see more cardiac arrests in summer, more pancreatitis in…
Automating and scaling waiting list equity analysis at a trust level
More information coming soon!
eFIT: Extra funding allocation - inequality tool
More information coming soon!