Simulation modelling in mental health services

Hampshire and Isle of Wight Sustainability and Transformation Partnership

  • Led by the Hampshire and Isle of Wight Sustainability and Transformation Partnership (STP), with Wessex Academic Health Science Network, and Wessex Centre of Implementation Science.
  • Aiming to increase mental health analytic capacity and capability to allow better understanding of the problems faced by people accessing services, and to improve planning and delivery of services.
  • Analysts will be trained in simulation modelling – an innovative and powerful analytical approach.
  • Will run from August 2018 to September 2019.

The Hampshire and Isle of Wight STP is reviewing how to improve outcomes for adults using acute mental health services. including reducing out-of-area placements to enable people to receive care and treatment as close to home as possible.

As part of this, an evidence base is needed to support commissioning decisions. This project will use an innovative approach to building that evidence base.

Simulation modelling involves analysts testing a range of scenarios in a safe environment. This allows them to better understand the problems faced by people when accessing services, and by managers and frontline clinicians when designing services.

Local data analysts will be trained in problem structuring and simulation modelling techniques, working alongside experts from the Wessex Centre of Implementation Science and the University of Southampton Business School.

A modelling tool will be created to run and test scenarios. This will allow the STP to identify challenges with the current mental health acute pathway, including gaps and duplication of services, and understand the cause and effect of changing demand and commissioning decisions on the system. The scenarios can then be adjusted and tested in a safe way that does not disrupt people who use the services, or staff. The optimal scenarios for improving outcomes for people who use services and increasing efficiencies for the local health care system will then be able to be identified.

Through the project, analysts will increase their analytical skills and learn how to be better equipped to extract key meaning from data, evaluate the consequences of change, and put forward a case that includes the rationale for change.

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