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Using automation to reduce waiting lists

We have helped a hospital trust to tackle the backlog of waiting lists while maintaining quality of care by using a combination of chatbot, risk stratification and artificial intelligence.

We are working with Worcestershire Acute Hospitals NHS Trust on the application of automated call (chatbot) technology to manage its patient waiting list backlogs. The aim is to provide an end-to-end digital solution to expedite work that otherwise would take considerable time and staff resource to complete.

Specialists from our Digital Innovation Unit (DIU), Referral Management Centre (RMC), and Cloud Development, Information Governance and Business Intelligence teams, have been working together on the pilot. The first two of its three stages have been completed successfully.

Stage 1 chatbots and RMC calling 1000 patients in the first proof of concept. The automated call to patients asks a series of questions to determine if the patient still requires the appointment, would prefer to be taken off the list, and if they require an appointment whether they would be happy to receive a telephone or/and video consultation. The automated call script to patients was designed with input from senior clinicians and validated through patient forums. If patients prefer not to speak to the chatbot, they are put through to our RMC for a human call operator.

Stage 2 feeding back of call results to the hospital Patient Administration System (PAS) by using robotic process automation (RPA), providing more contemporary information for clinical validation direct into the PAS.

Stage 3 (in progress) – supporting consultants to review the outpatient waiting list to help prioritise patients. Our DIU is working with one of its digital partners on a proof of concept using their unique ‘clinical natural language processing’ (artificial intelligence – AI) to vastly reduce the level of clinician input to this prioritisation. Clinicians would currently have to read and review all patient records – a large, intensive task potentially subject to human errors. This technology will structure the electronic data the trust has for the patients and offer proposed prioritisation based on acceptance criteria agreed with each clinical specialty.

Using this combination of chatbot, risk stratification and artificial intelligence, we are helping the trust to prioritise and clinically validate waiting lists efficiently. It has helped to tackle the backlog of waiting lists, reducing waiting times, while maintaining quality of care.

The successfully completed first two stages of our pilot project with the trust quickly cleansed the waiting list and provided up-to-date information for clinical validation.

Approximately 10 per cent of patients either no longer needed to be on the waiting list or wanted to come off it and 68 per cent were happy with a telephone consultation.

This solution saves huge amounts of time and staff resource, reducing hospital costs. Using RPA avoids the need for temporary admin teams to be interviewed, employed, on-boarded, trained and so on. Chatbot costs are a tiny fraction of those incurred in producing, printing and posting letters.

Stage 3 of the pilot is in progress. Following the success of the first two stages, the project is being extended to Wye Valley NHS Trust and East Lancashire Hospitals NHS Trust.