Exeter researchers are helping to underpin vital decisions with evidence
Real life organisations can be incredibly complex; when changes are made to a process or service, it can be difficult to predict the outcomes and ensure the intended effects are achieved.
In the National Health Service – where actions might also impact on patient safety – this uncertainty has the potential to result in serious consequences. So, University of Exeter researchers have teamed up with NHS Trusts across the South West to roll out a programme of training that uses computer modelling to help make difficult decisions.
Devised and implemented by NIHR PenCLAHRC at the University of Exeter Medical School, the HSMA programme has been designed to build modelling capacity in the NHS, fostering the skills to embed evidence-based practice in all areas of their operational activities. The researchers involved also hope the training will have a wider influence on teams within the health service in effective, sustainable and long-lasting ways.
“We’ve been able to reap the benefits of this way of working with areas outside of the emergency department, extending our work to impact decisions on ward numbers, cardiac treatment and eye care,” said Nic Harrison, Principle Analyst, Northern Devon Healthcare NHS Trust.
The scheme allows staff from a range of backgrounds to spend one day a week with University experts, learning how to use the latest advances in computer simulation. Launched in April 2016, the first wave of the programme saw staff from six NHS organisations sign up to take part.
The Health Service Modelling Associates (HSMAs for short) spent 12 months with their academic mentors, receiving support and training to tackle an important problem facing their Trust. One year on, the individuals and institutions involved in the training are already seeing significant benefits.
In one example, Northern Devon Healthcare NHS Trust has improved both wait times and admission rates in Accident and Emergency. Nic Harrison, Senior Analyst and HSMA trainee, built a detailed model of the way patients flow through their emergency department so he could experiment with various configurations. The final optimised solution allowed the Trust to meet crucial targets and receive a financial reward that could then be reinvested in improving patient care.
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