The innex.ai platform integrates a comprehensive database with a user-friendly chatbot interface, effectively reducing search times by 35%, and enhancing the quality of responses by 53%. This breakthrough promises not only to streamline access to information, but also to enhance collaboration and decision-making across the NHS. Following a successful pilot at Cambridge University Hospitals NHS Foundation Trust, where the platform demonstrated significant benefits in operational efficiency and compliance with regulatory standards, the platform is now set to expand to more pioneering NHS Trusts. This expansion will equip more teams with the essential tools to overhaul their information management practices, ensure rigorous compliance, and foster a more collaborative environment within the built environment of the NHS.
Daunting infrastructure and workforce challenges
High-quality facilities are crucial for providing safe healthcare services, ensuring patient care, and safeguarding staff health and wellbeing. Sadly, a substantial portion of healthcare infrastructure across the UK is severely outdated, and grapples with a substantial maintenance backlog of £11.6 bn (up 13.6% year-on-year) due to chronic underinvestment.1,2
Additionally, workforce challenges exacerbate these problems, with roughly 34% of the estates and facilities management (EFM) workforce aged 55 or above, and a higher sickness absence rate among EFM staff, at 7.5%, compared with 4.9% across the broader NHS workforce.3 The NHS Staff Survey 2023 highlights the many challenges faced by EFM staff, many of whom reported lower levels of satisfaction, especially in the areas of feeling rewarded and included in workplace matters. Notably, there were significant gaps in the scores for ‘We are always learning’, and ‘We are a team’ compared with national averages. This dissatisfaction is mirrored in the higher leaver rate of 7.6% among EFM staff, which is higher than the overall rate of 7.2%.4
Navigating regulatory and best practice information presents additional difficulties to NHS EFM staff. To ensure statutory compliance and operational efficiency, NHS EFM staff are required to search through various repositories. These include national information sources, such as HTMs, HBNs, PAM, the Model Hospital, and the Collaboration Hub. Staff also need to consult industry information sources (e.g. on funding support, professional body guidance, practitioner journals, and industry trends), and Trust-specific information such as Trust policies, strategies, site information, equipment manuals, and intranet resources. However, these repositories are difficult to navigate, as described by a Director of EFM, who likened the process to ‘searching for a needle in a haystack’, while an Authorising Engineer added that ‘guidance is frequently outdated and overlaps’.
A study at the University of Cambridge investigated the inefficient search for regulatory and best practice documents, with 64 participants from various NHS Band levels and external consultants such as AEs. The findings from this study (see Figure 1) show that on average, NHS EFM staff — ranging from tradespersons to Directors of Estates and Facilities, spend an average of 11 hours per week on searching for information from fragmented repositories. Notably, staff in Band Levels 8a-d spend the most time, averaging about 12.3 hours weekly. The breakdown of this time shows that staff dedicate about 3.6 hours to national guidance and 3.8 hours to Trust-specific documents each week, indicating a significant effort in maintaining compliance and staying updated within their respective Trusts. Keeping abreast of industry trends and developments also demands a notable investment of time, with an average of 2.6 hours weekly across all staff, and up to 3.8 hours for those in Band Levels 8a-d.
AI solution to streamline search for information
Faced with these daunting challenges, technology offers promising solutions. To reduce the time wasted on frustrating information search, Carl-Magnus von Behr, having studied knowledge sharing among NHS EFM teams, and Dr. Jan Blümel, expert on Natural Language Processing and Artificial Intelligence (AI), developed the platform, innex.ai. At the heart of this AI-driven platform is a robust database coupled with a user-friendly chatbot interface. Working together with NHS England and IHEEM, the team has curated a range of repositories filled with essential regulations, guidelines, and best practices.
The platform revolutionises the way users interact with information. Through a conversational interface, users can pose questions and refine their search by selecting specific types of documents — such as NHS guidelines, building regulations, or practitioner journals — or by focusing on particular domains such as decontamination, ventilation, or sustainability. This sophisticated hybrid search mechanism significantly enhances search precision.
The AI ‘copilot’, a pivotal feature of the platform, not only retrieves, but also summarises, the most relevant sections from the database. Moreover, it ensures that users have immediate access to the original documents by providing direct links to the relevant reference materials. This integration of advanced AI with user-centric design transforms the cumbersome process of information retrieval into a seamless and efficient experience.
The introduction of the innex.ai platform represents a significant advancement in the efficiency of information retrieval for NHS EFM staff. In the study at the University of Cambridge, EFM staff participated in a structured experiment to measure the platform’s effectiveness. As part of the study, participants performed a baseline task without AI tools, followed by two further tasks — one with the innex.ai platform and another without — covering topics such as hot water distribution and energy management.
The study demonstrated that innex.ai enhances the speed of accessing information by an impressive 35%. Considering the 11 hours that staff spend weekly on such tasks, innex.ai can save EFM staff up to four hours per week, freeing up nearly 10% of weekly staff time. This substantial time saving not only boosts productivity, but also allows staff to dedicate more time to critical operational tasks and patient care, rather than navigating cumbersome information systems. The potential cumulative impact across the NHS could lead to significant improvements in service delivery and operational efficiency, demonstrating the transformative power of integrating advanced AI technologies in healthcare administration.
In addition to significant time savings, the study also showed that participants who used innex.ai saw a 53% increase in answer quality ratings compared with the control group. Hence, staff not only find information faster, but they are also much more likely to find the correct and evidence-based information. This has a substantial positive effect on decision-making in the NHS, leading to better compliance with regulations, enhanced patient safety, and more effective implementation of sustainability strategies — key areas of focus given the NHS’s ambitious Net Zero carbon targets and the existing £11.6 bn maintenance backlog. The platform contributes to workforce development initiatives, and reduces the time and costs associated with staff training and onboarding, especially for new staff members from non-healthcare backgrounds.
Insights and opportunities from the Wales conference
In May 2024, at the IHEEM Wales Regional Conference, innex.ai showcased the transformative potential of its solution. The presentation and exhibition stand illustrated how this technology is pioneering the integration of siloed information sources into a unified, efficient system for knowledge sharing. Addressing critical issues such as patient safety, emergency preparedness, and the ambitious Net Zero carbon targets, innex.ai demonstrated its significant impact on the NHS’s EFM sector. The conference not only served as a platform for demonstrating innex.ai’s impact on the sector, but also underscored the importance of integrating lessons from both past and present to foster a more innovative healthcare estate.
Following the presentation, attendees had the opportunity to sign up for a free account, enabling them to test the platform’s capabilities first-hand. This hands-on experience led to an exceptionally engaged Q&A session, where the potential of AI to drive significant collaboration among stakeholders — encompassing NHS Trusts, Authorising Engineers, professional and industry bodies, and many more — was discussed. The discussions on the exhibition stand explored how innex.ai could become a cornerstone for an ecosystem of partners united by a shared commitment to compliance, sustainability, and efficiency. Such collaboration promises to enhance knowledge sharing and decision-making across the entire network.
innex.ai is currently being piloted at Cambridge University Hospitals NHS Foundation Trust. The pilot provides users from the Trust’s Maintenance & Engineering team with access to the AI platform. The feedback from users is overwhelmingly positive, particularly highlighting the platform’s impact on reducing the time spent searching for critical information. Users reported that accessing up-to-date national guidelines and regulations became significantly faster and more intuitive, which contributed to notable improvements in their daily workflow and efficiency. Encouraged by these results, the scope of the pilot is now being expanded to include Capital Projects teams. The data gathered during these stages provides invaluable insights into user behaviour, platform usability, and the overall impact on operational efficiency, which in turn informed continuous improvements to innex.ai.
Expanding the platform across the NHS
Encouraged by the positive feedback, innex.ai is keen to expand the platform to additional NHS Trusts and organisations within the NHS ecosystem. Participating organisations instantly benefit from immediate time savings for their EFM teams, enhanced compliance, and a multi-year discount on the platform’s subscription fee after the six-month pilot. Furthermore, the team is dedicated to collaborating with each organisation to customise the implementation process to its unique needs, ensuring that every department gains the fullest advantages from innex.ai.
To learn more about joining the pilot programme, please contact us at carl@innex.ai, or speak to us at the Healthcare Estates Conference 2024. We will be on stand G47, directly opposite the IHEEM Members’ Lounge. Join us, and together we can drive collaboration for a more compliant, sustainable, and efficient NHS built environment.
Carl-Magnus von Behr
Carl-Magnus von Behr is an industrial engineer specialising in interdisciplinary problem-solving in healthcare facilities management. He says witnessing the ‘silo working’ and challenges faced by NHS EFM departments during the COVID-19 pandemic inspired him to dedicate four years to PhD research focused on improving knowledge sharing among NHS Trusts. Drawing on the insights from his research, he co-founded innex.ai, with the goal of driving innovation and operational efficiency across the NHS.
Dr Jan Blümel
Dr Jan Blümel, CTO and co-founder of innex.ai, combines expertise in engineering and artificial intelligence with a focus on Large Language Models (LLMs) and their applications. He earned his PhD from the University of Cambridge, specialising in the use of LLMs for conversational AI. He also holds a BSc in Mechanical Engineering from the RWTH Aachen University. Bridging the gap between engineering and AI, his current work centres on developing innovative LLM systems for compliance management and knowledge sharing, specifically tailored for healthcare EFM.
Alan Saji
Alan Saji is a final-year medical student and researcher at the University of Southampton, exploring advances in medical technology and biosensors. With a strong interest in healthcare management, and a drive to address prominent healthcare challenges, he brings a valuable clinical perspective to innex.ai, supporting its goal to streamline hospital management throughout the NHS.
References
1 British Medical Association. Building the Future – Brick by brick: The case for urgent investment in safe, modern, and sustainable healthcare estates. London. 1 Dec 2022. [Online]. https://tinyurl.com/bddtf6yn
2 NHS England, ‘Estates Returns Information Collection, Summary page and dataset for ERIC 2022/23’, NHS England Digital. [Online]. https://tinyurl.com/5n8sah5p
3 NHS Estates and Facilities Workforce Action Plan, London, PAR292, June 2022. [Online]. Available https://tinyurl.com/5n6fnzzw
4 NHS 2023 NHS Staff Survey Results. Accessed: Jul. 21, 2024. [Online]. https://www.nhsstaffsurveys.com/results/
5 Partow C. ‘AI/LLM Tools to Streamline Information Retrieval for Hospital Infrastructure Support Staff’, M.Sc. Dissertation, ETH Zürich & University of Cambridge, Cambridge, UK, 2024.