Here you can find details of a range of HSMA projects that are currently being worked on.
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.
Projects In Progress
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…
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…
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.
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.
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…
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.
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…
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.
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…
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.
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.
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…
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,
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.
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…
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…
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.
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Agent Based Simulation modelling influences on access to hospice care
Not everyone eligible for hospice care is offered, or accepts it. There is research relating to all potential agents in the decision to access hospice care where healthcare…
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…
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…
Automating and scaling waiting list equity analysis at a trust level
More information coming soon!
SIMPACT: Simulation of Medical Patient Admission and Care Throughput
More information coming soon!
eFIT: Extra funding allocation - inequality tool
More information coming soon!
Modelling resourcing scenarios to meet increases in demand on a Devon eye clinic
More information coming soon!
Using Machine Learning to predict whether a patient might develop a SSI (Surgical Site Infection)
More information coming soon!