Abstract
Common mental health disorders such as anxiety and depression are cited as the largest cause of disability in England and their prevalence is increasing. The Improving Access to Psychological Therapies (IAPT) programme was established to support the delivery of such therapies in England. This evidence-based programme is based on the principle of stepped care, where effective but less resource intensive treatments are delivered to patients first.
IAPT received nearly 1.7 million referrals between April 2019 and March 2020, and the NHS aims for 1.9 million people to be able to access IAPT services by 2023/24. In the challenging environment of limited resources and waiting time targets, effectively managing waiting lists and minimising preventable patient drop-outs from the care pathway are central to the success of the programme.
Our research is part of a 3-year project which aims to develop innovative, advanced, analytical tools to help support decisions around IAPT service improvements. Our plans include using process mining and other data-driven methods, augmented by simulation modelling and a comprehensive programme of engaging with end-users. We present the early findings of applying process mining methods to routinely collected data from a number of IAPT services using Iaptus, a specialised electronic patient record management system. The focus of our analysis is on mapping the care pathway and identifying potential bottlenecks.
IAPT received nearly 1.7 million referrals between April 2019 and March 2020, and the NHS aims for 1.9 million people to be able to access IAPT services by 2023/24. In the challenging environment of limited resources and waiting time targets, effectively managing waiting lists and minimising preventable patient drop-outs from the care pathway are central to the success of the programme.
Our research is part of a 3-year project which aims to develop innovative, advanced, analytical tools to help support decisions around IAPT service improvements. Our plans include using process mining and other data-driven methods, augmented by simulation modelling and a comprehensive programme of engaging with end-users. We present the early findings of applying process mining methods to routinely collected data from a number of IAPT services using Iaptus, a specialised electronic patient record management system. The focus of our analysis is on mapping the care pathway and identifying potential bottlenecks.
| Original language | English |
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| Publication status | Published - Jul 2022 |
| Event | 48th Annual Meeting of the EURO Working Group on Operational Research Applied To Health Service - Bergamo, Italy Duration: 17 Jul 2022 → 22 Jul 2022 Conference number: 48 http://orahs2022.eu/ |
Conference
| Conference | 48th Annual Meeting of the EURO Working Group on Operational Research Applied To Health Service |
|---|---|
| Abbreviated title | ORAHS2022 |
| Country/Territory | Italy |
| City | Bergamo |
| Period | 17/07/22 → 22/07/22 |
| Internet address |
