NHS Midlands and Lancashire Launches Activate, Incorporating a Scalable, Cost-Effective Patient Contact Center Solution with Digital Space on AWS, Reducing Patient Waiting Lists by 9–14%

NHS ML helps to support general practitioners (GPs), hospital trusts, and other healthcare providers with services for patient communication and engagement. These traditionally included postal and telephony services. However, the increasing number of patients on waiting lists nationally was beginning to become an expensive and time-consuming challenge to overcome with paper-based and manual telephony methods of communication. This prompted NHS ML to look for more efficient, automated solutions to help address this growing problem.

Previous NHS methods of sending letters and making phone calls were difficult to manage, expensive to deliver, and resulted in a poor experience for patients. Healthcare communications are a vital part of a patient’s journey with the NHS services, and inefficiency can lead to worsening patient outcomes. It was clear that a more efficient system would not only help to manage the waiting lists more effectively, but also lead to better patient experiences. NHS ML saw an opportunity to transform the waiting list validation process and associated patient contacts by automating the patient contact center, introducing innovative solutions such as automation to improve the service for both the patient and NHS staff.

NHS ML asked Digital Space to help it consolidate the services into a single cloud-based solution and develop its chatbots to automate a large proportion of telephone calls. The solution would form part of Activate, an NHS communication platform aimed at delivering more effective and efficient services for patients, clinicians, and system leaders. The organization had already been collaborating to pilot chatbots after meeting at an innovation conference. Moving to a cloud-based telephony solution was an integral part of Digital Space’s approach.

The NHS ML team chose to use AWS, supported by Digital Space. “We cannot do everything for ourselves and recognize the effectiveness of using an expert partner like Digital Space to use AWS technology,” says John Uttley, digital innovation director at NHS ML. Digital Space worked with NHS ML to commission an Amazon Connect telephony solution and to create chatbots with Amazon Lex that would implement clinically validated scripts to ask a series of questions and collect information from patients. After NHS ML receives a validated list of patients, a second, automated validation is performed. Patients are sent an SMS text with a link to a personal survey on a secure web portal. If after a set period the patient has not completed the web survey, they will receive a chatbot call. The chatbot calls the patients by name, quoting their specialty listing on the waiting list, and asks them a series of clinically approved questions to assess their current needs.

If a patient informs the chatbot that they want to come off the list, the system diverts the chatbot call to an NHS ML Referral Management Centre call center operator in near real time and supplies the operator with the answers it has received so far, on screen. The call center operator then validates the response and agrees they no longer require the appointment. They are then removed from the waiting list by the healthcare provider, and the patient and their GP are notified of the discharge. If after a pre-defined number of calls initial contact has not been made, NHS ML attempts to contact the patient with up to two agent calls. This supports patients who do not want to engage with the chatbot, along with those whose details could not be easily comprehended by the system. Vulnerable patients are also excluded from chatbot calls.

The solution can use different scripts for each clinical specialty, and results are recorded electronically and are provided back to the healthcare provider. This enables the healthcare provider to discharge patients who no longer need to be on the waiting list with confidence and to prioritize other patients who need treatment more urgently, which optimizes the delivery of services. The process can be repeated as many times as required.