Using AI-Based Technology to Enhance Outcomes on the NHS Discharge to Assess (D2A) Process

Funded by an Innovate UK Smart Grant, Connected Places Catapult participated in a consortium led by MiiCare and in collaboration with De Montfort University, Willows Health, and the Leicester, Leicestershire, and Rutland Integrated Care Board. This project developed and tested Miicare’s existing Monica solution to enhance outcomes for patients and clinical teams within the NHS Discharge to Assess process. This whitepaper presents the findings from the user research and trial development. 

Approach  

The work was carried out in four stages: 

1. User Research: Desktop research and stakeholder  interviews with healthcare professionals and patients to identify challenges and opportunities within the D2A process and potential benefits of AI integration. 
2. Technology Development: Refining Monica, an AI-based virtual assistant, to support patients at home and provide relevant information to clinical teams. 
3. Technology Deployment and Evaluation: Deploying Monica in 27 homes of patients who had gone through Pathway 1 of the D2A model and evaluating its impact. 
4. Synthesis and dissemination: Synthesis of data and distilling and disseminating insights for the sector. 

Main Findings 

Through our research, we found that there are challenges within the three stages of the D2A model (pre-admission, during hospital stay, and post-discharge). We identified specific areas where AI-based monitoring technology could alleviate these challenges and improve the experience for clinicians, patients and care teams, particularly during the post-discharge phase. In the post- discharge phase, continuous monitoring of an individual’s health and wellbeing, their home, and 24-hour virtual support can ensure the patient’s safe recovery after they return home. 

Through deploying Monica in patient homes, we found that it can bring reassurance to carers, can serve as a companionship aid, especially for patients with limited social networks, and can encourage healthy behaviours. Patients also reported some challenges with Monica including connectivity issues due to weak signals, lack of speech diversity programmed into Monica, and occasional out-of-sync engagements. The findings suggest that patients were comfortable with Monica, as on average, 2/3 of engagements were initiated by the patient. 

Conclusion 

The project demonstrates the potential of AI-based technologies like Monica to enhance post-discharge care within the D2A model. While there are areas for improvement, the initial findings are promising.  We recommend deploying Monica in more patient homes and along various discharge pathways to support the refinement of the technology and collect further impact data. Additionally, coordinating with local authorities will help integrate these technologies into care systems, enhancing patient outcomes. 

Using AI-Based Technology to Enhance Discharge to Assess Services

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Watch the webinar recording below to learn how digital innovation is transforming Discharge to Assess (D2A) services, enabling patients to leave hospitals safely while continuing care at home.

Experts will discuss current challenges, such as poor patient flow and information sharing, and explore the potential of AI-based solutions like Monica from MiiCare to streamline workflows, improve care, and reduce emergency hospital bed days. Gain insights from clinicians and innovators on real-world impacts and explore opportunities for future collaboration.