Abstract
It is estimated that one in six adults in England have a mental health disorder and would benefit from a course of psychological therapy. The NHS Talking Therapies Programme treats over a million patients with common mental health problems each year according to the principle of stepped care, where effective but less resource intensive treatments are delivered to patients first and higher intensity interventions are then provided if required.
In order to meet NHS targets, the programme will need to increase access rates, while meeting service standards for waiting times and recovery rates. Mental healthcare providers are therefore looking at all opportunities to increase capacity and productivity. The aim of this project is to develop innovative, advanced, analytical tools to help improve understanding and management of NHS Talking Therapies services’ demand and capacity.
This study analyses data from iaptus, the leading digital care record for psychological therapy services, to investigate and model patient flows through talking therapy care pathways using process mining and other data-driven methods, augmented by simulation modelling to evaluate pathway performance and explore relationships between performance issues. The major impacts of this project are expected to be improved access to services, improved utilisation of resources, resulting in reduced waiting times, better recovery rates and reduced patient drop out.
In order to meet NHS targets, the programme will need to increase access rates, while meeting service standards for waiting times and recovery rates. Mental healthcare providers are therefore looking at all opportunities to increase capacity and productivity. The aim of this project is to develop innovative, advanced, analytical tools to help improve understanding and management of NHS Talking Therapies services’ demand and capacity.
This study analyses data from iaptus, the leading digital care record for psychological therapy services, to investigate and model patient flows through talking therapy care pathways using process mining and other data-driven methods, augmented by simulation modelling to evaluate pathway performance and explore relationships between performance issues. The major impacts of this project are expected to be improved access to services, improved utilisation of resources, resulting in reduced waiting times, better recovery rates and reduced patient drop out.
| Original language | English |
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| Publication status | Published - 2024 |
| Event | 33rd European Conference on Operational Research - Copenhagen, Denmark Duration: 30 Jun 2024 → 3 Jul 2024 Conference number: 33 https://euro2024cph.dk/ |
Conference
| Conference | 33rd European Conference on Operational Research |
|---|---|
| Abbreviated title | EURO24 |
| Country/Territory | Denmark |
| City | Copenhagen |
| Period | 30/06/24 → 3/07/24 |
| Internet address |