Anticipated barriers and facilitators to the
implementation of an AI guided tool advising on the
placement of mitigation strategies to improve air
quality in the hospital setting: A qualitative study
Yolanda Barrado-Martín, Sanjoli Mathur, Zarnie Khadjesari, Sigrún Eyrúnardóttir
Clark, Cecilia Vindrola-Padros, Laurence B Lovat, Fiona Stevenson
Submitted to: Journal of Medical Internet Research
on: February 12, 2026
Disclaimer: © The authors. All rights reserved. This is a privileged document currently under peer-review/community review. Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review purposes only. While the final peer-reviewed paper may be licensed under a CC BY license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.

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Anticipated barriers and facilitators to the implementation of an AI guided tool advising on the placement of mitigation strategies to improve air quality in the hospital setting: A qualitative study
Yolanda Barrado-Martín1 PhD; Sanjoli Mathur2 MSc; Zarnie Khadjesari2 PhD; Sigrún Eyrúnardóttir Clark3 MSc; Cecilia Vindrola-Padros3 PhD; Laurence B Lovat4 MBBS, PhD; Fiona Stevenson1 PhD
1Research Department of Primary Care & Population Health University College London London GB
2 School of Health Sciences University of East Anglia Norwich GB
3Rapid Research Evaluation and Appraisal Lab (RREAL), Department of Targeted Intervention University College London London GB 4Intelligent Systems in Gastroenterology & Healthcare Technology Lab (InSIGHT AI), Division of Surgery and Interventional Science University College London London GB
Corresponding Author:
Yolanda Barrado-Martín PhD
Research Department of Primary Care & Population Health
University College London
University College London, Upper 3rd Floor, Royal Free Campus,
Rowland Hill St.
London
GB
Abstract
Background: Artificial intelligence (AI) is increasingly prevalent within healthcare, however, its implementation within the hospital setting may come with its own limitations given the high pressured and sensitive environment. Only a few studies have qualitatively explored barriers and facilitators to the implementation of AI within hospitals and there is a scarcity of qualitative research on the implementation of AI guided tools to improve air quality.
Objective: This study aims to qualitatively explore, through a Normalisation Process Theory (NPT) lens, the anticipated barriers and facilitators to the successful implementation of an AI tool to guide the placement of mitigation strategies to reduce airborne transmission of infections within the hospital setting. Our objectives were to: a) Understand the day-to-day work of key hospital staff involved in reducing airborne transmission of infections; b) Identify potential barriers to the implementation of an AI tool to guide the placement of mitigation strategies in the hospital setting; and c) recognise necessary conditions for the successful implementation of the AI tool within the hospital setting.
Methods: We conducted ethnographic observations (n=4) and semi-structured interviews (n=9) with hospital staff following preliminary and wider stakeholder engagement work involving patients, members of the public, national leaders in ventilation working within academic and industry environments, and hospital staff (n=70). Interview transcripts, fieldnotes and summaries from preliminary wider engagement work activities were analysed in NVivo 12, to facilitate triangulation through comparisons between data. Findings were organised according to the core constructs of NPT.
Results: Hospital staff understanding of the AI guided tool and their preparedness to invest time in its implementation was variable across hospital staff at this pre-implementation stage (coherence and cognitive participation). The work hospital staff will need to do to successfully implement the AI guided tool and its recommended mitigation strategies, is expected to be a significant challenge for the implementation of the AI guided tool at scale given the differences in the ways of working among Trusts and the competition for limited resources (collective action). The effectiveness of the AI guided tool will need to be proved and anticipated concerns around its future refinement addressed (reflexive monitoring).
Conclusions: This pre-implementation study suggests that the successful implementation of an AI guided tool advising on the placement of mitigation strategies to improve air quality in the hospital setting depends not only on the effectiveness demonstrated by the AI tool at trial stage but the way outcomes are shared with relevant stakeholders within the hospital setting. While initial resistance by hospital staff is expected, the impact of the AI tool and suggested mitigation strategies in workflows, costs and staff and patient outcomes, together with the way this information is conveyed to hospital staff may be decisive.
(JMIR Preprints 12/02/2026:93420)
DOI: https://doi.org/10.2196/preprints.93420
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Anticipated barriers and facilitators to the implementation of an AI guided tool advising on the placement of mitigation strategies to improve air quality in the hospital setting: A qualitative study
Authorship Information
1.		Dr Yolanda Barrado-Martín, PhD; ORCID: 0000-0002-9912-6345; Research Department of Primary Care & Population Health, University College London, London, United Kingdom.
2.		Ms Sanjoli Mathur; MSc; ORCID: 0009-0002-0259- 1 4; Affiliation: School of Health Sciences, University of East Anglia, Norwich, UK.
3.		Dr Zarnie Khadjesari; PhD; ORCID: 0000-0002-295 -9555; School of Health Sciences University of East Anglia, Norwich, UK.
4.		Ms Sigrún Eyrúnardóttir Clark; MSc; ORCID: 0000-0001-5679-2535; Affiliation: Rapid Research, Evaluation and Appraisal Lab (RREAL), Department of Targeted Intervention University College London, London, UK
5.		Prof Cecilia Vindrola-Padros; PhD; ORCID: 0000-0001-7 59-1646; Affiliation: Rapid Research Evaluation and Appraisal Lab (RREAL), Department of Targeted Intervention University College London, London, UK.
6.		Prof Laurence B Lovat; highest academic degree MBBS PhD; ORCID: 0000-0003-45423915; Affiliation: Intelligent Systems in Gastroenterology & Healthcare Technology Lab (InSIGHT AI), Division of Surgery and Interventional Science, University College London, London, UK.
7.		Prof Fiona Stevenson; PhD; ORCID: 0000-0003-2139-2309; Affiliation: Research Department of Primary Care & Population Health, University College London, London, United Kingdom.
Complete contact details for the corresponding author:
		Yolanda Barrado-Martín, y.barrado@ucl.ac.uk, Tel.: +44 (0)2031 0 2 2, Address: Research Department of Primary Care & Population Health University College London, Upper 3rd Floor, Royal Free Campus, Rowland Hill St. London, NW3 2PF (United Kingdom)
Abstract
Background
Artificial intelligence (AI) is increasingly prevalent within healthcare, however, its implementation within the hospital setting may come with its own limitations given the high pressured and sensitive environment. Only a few studies have qualitatively explored barriers and facilitators to the implementation of AI within hospitals and there is a scarcity of qualitative research on the implementation of AI guided tools to improve air quality.
Objectives
This study aims to qualitatively explore, through a Normalisation Process Theory (NPT) lens, the anticipated barriers and facilitators to the successful implementation of an AI tool to guide the placement of mitigation strategies to reduce airborne transmission of infections within the hospital setting. Our objectives were to: a) Understand the day-to-day work of key hospital staff involved in reducing airborne transmission of infections; b) Identify potential barriers to the implementation of an AI tool to guide the placement of mitigation strategies in the hospital setting; and c) recognise necessary conditions for the successful implementation of the AI tool within the hospital setting.
Methods
We conducted ethnographic observations (n=4) and semi-structured interviews (n=9) with hospital staff following preliminary and wider stakeholder engagement work involving patients, members of the public, national leaders in ventilation working within academic and industry environments, and hospital staff (n=70). Interview transcripts, fieldnotes and summaries from preliminary wider engagement work activities were analysed in NVivo 12, to facilitate triangulation through comparisons between data. Findings were organised according to the core constructs of NPT.
Results
Hospital staff understanding of the AI guided tool and their preparedness to invest time in its implementation was variable across hospital staff at this pre-implementation stage (coherence and cognitive participation). The work hospital staff will need to do to successfully implement the AI guided tool and its recommended mitigation strategies, is expected to be a significant challenge for the implementation of the AI guided tool at scale given the differences in the ways of working among Trusts and the competition for limited resources (collective action). The effectiveness of the AI guided tool will need to be proved and anticipated concerns around its future refinement addressed (reflexive monitoring).
Conclusions
This pre-implementation study suggests that the successful implementation of an AI guided tool advising on the placement of mitigation strategies to improve air quality in the hospital setting depends not only on the effectiveness demonstrated by the AI tool at trial stage but the way outcomes are shared with relevant stakeholders within the hospital setting. While initial resistance by hospital staff is expected, the impact of the AI tool and suggested mitigation strategies in workflows, costs and staff and patient outcomes, together with the way this information is conveyed to hospital staff may be decisive.
Keywords
Barriers and facilitators; Artificial Intelligence; Implementation Science; Hospital; Cross Infections; Air Filters; Infection Control; Qualitative Research; Normalisation Process Theory
Introduction
Artificial intelligence (AI) is increasing its prevalence within healthcare, with its adoption supported by UK health policy, such as the NHS 10-Year Plan and the creation of AI working groups to steer the use of AI and speed up its use within the NHS 1 2. Despite AI’s predominant use in medical imaging3, it has the potential to contribute to other areas facilitating clinical decision-making, early diagnosis4 and hospital documentation5. This aligns with the NHS ambition to shift “from analogue to digital” prioritizing digital tools including AI-driven solutions to promote continuous monitoring with views to enhance prevention 2.
AI encompasses computational methods such as machine learning, neural networks, and predictive analytics designed to perform tasks traditionally requiring human intelligence at a faster pace and more efficiently. Despite these benefits, the implementation of AI within the hospital setting is not without challenges6 , with barriers such as the lack of trust, issues with generalizability, privacy and maintenance plans, or the previous lack of AI implementation guidelines7 which have only been recently addressed .
The NHS 10-Year Plan also calls for a change “from sickness to prevention” to improve population health but also to improve the sustainability of health care 2. AI-enabled tools have already shown potential in predicting hospital-acquired infections with high accuracy 9,10. Early detection and intervention of airborne disease transmission can protect frontline workers and facilitate hospitals working at full capacity by reducing staff sickness.
Responding to these challenges, our wider research team is developing and implementing an AI tool – the Artificial Intelligence air Safety Tool (AISaT). AISaT will process data about the characteristics of a hospital room such as its dimensions, and position of people in the room, to then produce recommendations on where best to position mitigation strategies within that room to reduce airborne infection transmission. Examples of mitigation strategies could include devices such as HEPA filters11,12, or equipment such as screens, curtains, windows or doors13,14.
Despite the promise of AI in infection prevention and the potential of qualitative research to help facilitate implementation 15, few studies have qualitatively explored barriers and facilitators to implementation of AI within hospital settings. The aim of this study was to explore, through a Normalisation Process Theory (NPT) lens16,17, the anticipated barriers and facilitators to the successful implementation of AISaT. By focusing on stakeholder experiences, including those of clinical, technical, and leadership teams, this work seeks to inform strategies that align with the NHS’s preventative care vision and support the normalisation of such innovations in routine hospital practice.
The study sought to answer the question: How do relevant stakeholders perceive the implementation of an AI tool to guide the placement of mitigation strategies to reduce airborne transmission of infections within the hospital setting? Our objectives were to: a) Understand the day-to-day work of key hospital staff involved in reducing airborne transmission of infections; b) Identify potential barriers to the implementation of an AI tool to guide the placement of mitigation strategies in the

JMIR Preprints

Barrado-Martín et al
hospital setting; and c) recognise necessary conditions for the successful implementation of the AI tool within the hospital setting.
Methods
Design
Wider stakeholder engagement activities, drawing on findings from two systematic reviews in this area 1 ,19 , were conducted. These comprised (i) an in-person patient advisory group (PAG) meeting (ii) an online workshop with national stakeholders (iii) follow-up conversations with national stakeholders and (iv) hospital staff based at two hospitals who would be involved in the subsequent clinical trial (Trial registration number: ISRCTN124214 6).
Drawing on insights from this wider stakeholder engagement, we conducted formal data collection (ethnographic observations and semi-structured observations) between 15/10/2025 and 1 /12/2025 at a large teaching hospital in an urban location. The focus of this research was on the roles and responsibilities of hospital staff working to keep hospitals free from airborne disease transmission. Data collected at this stage was triangulated with aggregated summaries from the wider stakeholder engagement activities as reflected in Figure 1.
Figure 1. Summary of types of data collected
All data were collected prior to trialling of the Air Safety system. The Consolidated criteria for Reporting Qualitative Research (COREQ) checklist was used to support the presentation of methods and results20 (see Multimedia Appendix 1).
Wider stakeholder engagement
The patient advisory group (PAG) was involved throughout the study. The PAG was consulted on the relevance and priority of a clean air within hospitals, and their initial reactions to HEPA filters and to AISaT. Members of the group were recruited through advertisement on the NIHR People in Research website, charity connections and established patient networks. The interaction with patients was led by SM, guided by SW and FS.
National leaders invited to the online workshop and follow-up conversations were drawn from academic, industry and healthcare sectors, through connections with members of the trial team and through online searches, because of their contributions to the field of ventilation. The workshop shared the project aims, sought first reactions about the trial and helped to identify further national leaders in the field and key hospital job roles to target in ethnographic observations and interviews. It was held online and lasted 60 minutes to maximise participation by people working in the health service in high pressured roles. The online workshop was led by YBM and SM, with support from FS, ZK and SEC.
The online workshop was supplemented by follow-up conversations which allowed stakeholders to share more detail in relation to their views. Follow-up conversations were also conducted with people who could not join the workshop, and those who were identified through snowball sampling (n= ). Additionally, after collecting information at the workshop about relevant hospital roles to engage with, the research team scheduled follow-up conversations with professionals in these roles (n=27). These informal conversations clarified the contribution of different job roles in keeping the hospital free from airborne disease transmission. A draft summary of barriers and enablers identified through the PAG, national leaders’ workshop and preliminary contacts in hospitals is provided in Multimedia Appendix 2, is the focus of a separate publication which reports on the development of an implementation strategy for roll-out.
Ethnographic observations and semi-structured interviews
Hospital staff were recruited following a combination of purposive and snowball sampling techniques. Participants with diverse roles (e.g., infection prevention control, estates, clinical) were invited to capture the views of all those likely to be involved in the implementation of Air Safety. Potential participants were approached by email, with 3 further follow-up emails where there was no response. We completed ethnographic observations in the work environment and online semistructured interviews in line with a predefined internal study protocol. Researchers had no prior relationship with participants. Participants had read a participant information sheet and knew the aims of the study and the researcher introduced themselves through their role as part of the implementation team of the study and explained the rationale to do the semi-structured interviews or ethnographic observations. Researchers had an interest in finding ways to facilitate the implementation of interventions.
Ethnographic observations were unstructured, but a minimal data collection template was used (see Multimedia Appendix 3). These were conducted by female researchers trained in ethnographic research methods and with previous experience (FS and YBM). Eight hours of ethnographic observation were conducted in Site 1 with four research participants. Fieldnotes were taken in situ and transcribed electronically as soon as possible after the ethnographic observation. Interactions with non-participants were not included in ethnographic fieldnotes.
Each semi-structured interview was guided by an interview schedule (see Multimedia Appendix 4) which had been pilot tested in preliminary conversations with stakeholders. A researcher with expertise in qualitative methods (YBM) and a background in psychology conducted the interviews. The interviews were conducted iteratively, building on previous insights.
Semi-structured interviews lasted for between 25 and 39 minutes (median 2 .45min). All interviews were audio or video-recorded on Microsoft Teams with automatic transcription. The researcher (YBM) cross-checked transcripts for accuracy and pseudonymised the data. Given hospital staff’s limited availability, interviews were not returned to participants to check their content, but during the interview summarising and clarification was used instead. Semi-structured interviews concluded when data saturation had been reached. No interviews were repeated. Participants did not provide feedback on the findings.
Analysis
Ethnographic observations and semi-structured interview transcripts were analysed using codebook thematic analysis 21 in NVivo 12 22. YBM coded two interviews and developed a preliminary coding framework inductively that was presented and discussed with FS. SM coded the same two transcripts and the agreement reached between coders was almost perfect (Kappa value 0. 5). The rest of ethnographic observations and semi-structured interviews, and the wider stakeholder engagement work, were coded by YBM applying the agreed framework. Subthemes were developed organised according to the core constructs of Normalisation Process Theory (NPT)16,17,23 .
Ethical considerations
The Air Safety Trial was approved by the Health Research Authority and Health and Care Research Wales Ethics Committee (ref 25/EM/0156). All participants involved in ethnographic observations and semi-structured interviews provided informed written consent.
Results
Stakeholder characteristics
We involved 12 public contributors (through the PAG) living around the Greater London Area. All have a long-term condition and experience of care in multiple hospitals. Contributors were aged between 20- 0 years, included women and 4 men, self-identifying as Black / African / Caribbean / Black British (n=4), Asian / Asian British (n=4), and White (n=4).
A total of 5 stakeholders were involved in conversations around the project and its implementation: 23 were involved in a workshop with national leaders (including senior NHS staff and policymakers industry experts and academics), and national leaders took part in follow-up conversations, like the 27 hospital staff who were identified either using online searches or purposive sampling within the two clinical trial hospitals.
Ethnographic observations were only conducted with 4 hospital staff and semi-structured interviews with 9 staff members: including 6 male and 7 female from Black / African / Caribbean / Black British (n=1), Asian / Asian British (n=5), and White (n=7) ethnic backgrounds. Staff interviewed had not been observed. Of 42 hospital staff members initially approached for observation and interviews at Site 1, 5 declined to participate (feeling other colleagues were better placed to respond (n=1), having no time (n=4)). A further 17 did not respond to our contact and with another 7, communication was lost after having expressed initial interest.
The job roles of those observed or interviewed were clinical (n=5), infection prevention control (n=2), estates (n=4) and roles within the management of the hospital (n=2). Among those interviewed, they had been in post during an average of 10.4 years (min=1; max=26) and most ranked the importance of ventilation within their roles as high (min 1- max 10): 1 or 2 (n=1), 4 (n=1) (n=3), 10 (n=4).
Hospital staff interviewed or involved in follow-up conversations as part of the wider stakeholder work described several tasks undertaken to reduce airborne disease transmission (summarised in Table 1). Their main work was isolating or managing patients with known airborne transmitted infections, placing them in appropriate spaces according to their risk level or advising others on how to do this.
Table 1. Hospital staff’s reported roles in keeping the hospital free from airborne disease transmission
Category	Specific tasks	
Room usage and air changes	•		Assessing	room-use	changes.
•		Checking that required air-changes-per-hour (ACH) are being achieved within rooms.	
Ward and patients’ oversight	•		Management and placement of patients with known airborne transmitted infections (including isolation prioritization).
•		Conducting	ward	audits.
•		Daily review of side-room usage.
•		Ensuring adequate testing of patients.	

Staff supervision	•		Ensuring staff are aware of infections and alerting Infection Prevention and Control (IPC) when needed.
•		Ensuring compliance with IPC training and practices.
•		Ensuring staff have adequate protection and providing related advice.	
Ventilation system management	•		Ensuring the ventilation system is functioning adequately.
•		Following Health Building Notes and Health Technical Memoranda (HTMs).	
Liaison with other teams	•		Continuous liaison with Estates regarding ventilation issues.
•		Attending multidisciplinary quarterly ventilation meetings within the Trust.	

Main findings
Findings are organized according to the four constructs of Normalisation Process Theory (NPT): Coherence, Cognitive Participation, Collective Action, and Reflexive Monitoring. (see Table 2).
Table 2. Summary table:
NPT Construct	Focus	Sub-Themes	Key insights	Enablers	Risks	&
barriers	
Coherence	Understan ding how the interventio n would work in the hospital environme nt	Current practices to mitigate airborne disease transmission;
Shared goals; Anticipated barriers and facilitators to adoption of AISaT;
Requirements for AISaT’s implementatio n.	Understandin g of value varies;
organizationa l staff are optimistic, while clinical/IPC staff are more sceptical or cautious.	•		Use in outpatient areas.
•		Userfriendly interface.
•		Inclusion in national guidelines.
•		Senior leadership buy-in.	•		Conflicts with fixed ventilation systems.
•		Old NHS building infrastructure.
•		PPE/Hand- washing seen as	higher priority.
•		Focus on aerosol vs. air changes.	
Cognitive Participati on	Developin g interest in	the
implement ation and enhancing its relevance	Decision making and ownership of AISaT;
Content and design	of
AISaT; Timing of AISaT’s implementatio n.	Engagement depends on multidisciplin ary buy-in and having designated "champions" to lead.	Multidiscipli nary decisionmaking.
•		Local champions to cascade info.
•		Potential (though risky) mandated use.	•		Lack of staff agency/owner ship.
•		Staff burnout and workload.
•		Financial constraints.
•		Not seen as a top priority vs. patient care.	
Collective	Planning	Identification	Implementati	• External	• Costs of	

Action	for the implement ation and roll out	of resources; Generalisabilit y and sustainability.	on	is
hampered by technical fragmentatio n and the cost of maintaining recommendat ions.	contractors to manage tool (reduces staff workload).
• Integration with
Electronic Health Records (EHR).	implementatio n/maintenance
•		Restricted data access.
•		Fragmented AI tool use within Trusts.
•		Lack of universal EHR systems.	
Reflexive Monitorin g	Planning for the evaluation and refinement	Providing key metrics and assurances;
Futureproofing AISaT.	Success is defined by long-term evidence and expert validation of effectiveness.	•		Expert validation.
•		Strong evidence from clinical trials.	•		Lack of a clear plan for future refinement support.
•		Uncertainty regarding post-project sustainability.	

1.		Coherence (How do stakeholders understand AISaT and its recommended mitigation strategies?)
This section explores how observed and interviewed hospital staff and wider stakeholders understood AISaT and the mitigation strategies that may be recommended by AISaT in the future, making them inseparable from AISaT’s implementation. It summarises current practices within the hospital setting to prevent airborne disease transmission and the potential barriers and facilitators of AISaT.
Current practices to mitigate airborne disease transmission
The most common mitigation strategy comes from the building management system (or air handling units) that represents the centralised ventilation system of the building. Our ethnographic observations captured how different units provide clean air and extract used air from hospital areas usually one machine would cover more than one hospital area. Usually, the placement of ventilation outlets is decided by architects and any changes to these require an authorising engineer’s sign off.
HEPA filters available [within ventilation outlets] all have been allocated at design stage. It could be possible to uninstall as needed, things can change, and more things can be added. The authorising engineer (AE) for ventilation would need to agree and sign off. (Ethnographic observations Informal conversation, Estates, HS104)
However, some interviewees raised concerns where portable HEPA filters have been trialled within the Trust, mainly related to space constraints where they can obstruct staff’s work or pose as a hazard to patients.
…if they [agitated patients] move the locker or they're able to reach that and push it, it poses quite a danger of the actual physical unit being dropped and damaged, but also it then causing harm to somebody if it falls on them. (Semi-structured interview, Clinical, HS102)
Further concerns included the impact of a device, such as a portable HEPA filter, increasing room temperature and noise; competition for limited sockets; the lack of evidence proving their effectiveness; that they take significant time to clean the air; the lack of maintenance plans; the high numbers required in wards; and their associated costs. Despite these reservations, staff who had HEPA devices within their work environment agreed they would be happy to have HEPA devices that were affixed to walls.
So, this [HEPA devices] is good if it's not the fact that the size [of the devices] ... if it could be a bit smaller or maybe attached to the wall because we also have a limited outlet. (Semi-structured interview, Clinical, HS108)
Other mitigation strategies reported included: prioritising isolation of potentially infectious individuals; faster patient testing; improving hand hygiene; reducing the number of visitors when necessary; the use of PPE; the construction of further isolation single or side rooms in new buildings; and curtains or transparent partitioning screens. An interviewee flagged that some of this equipment is hardly being used after the Covid-19 pandemic due to limited storage and risk of falls for patients. Also discussed in the interviews was that some spaces contain or have tested air filtration machines (such as HEPA mobile devices), however, this is not a generalised approach across the hospital.
As far as I know there are some units like I think dental units that have filtration machines. But it's not something that we would routinely put in all...areas such depends... on the risk assessment of what sort of procedure they're going to undertake in the room, the size of the room obviously. What's the current air change? What's the supply and extract...within the room. So yeah, we have some mitigations like filtration machines, but they're not widely used… (Semi structured interview, IPC, HS110)
Fans are not used as a mitigation strategy but rather for the comfort of staff and patients and are not allowed in particular areas of the hospital (e.g., theatres, or endoscopy) where its use could lead to the spread of infections.
During Covid, the access and number of patients in a room was regulated to ensure there was enough time within empty rooms to renew the air for the next patient. Currently, longer cleaning times are allowed after conducting certain procedures with patients with specific infections.
The NHS estate is generally old and comes with its own limitations (e.g., lack of ceiling space, limited ability for new infrastructure projects, limited electrical supply and clinical space).
…when we build new buildings (…) there's always more and more required from an engineering point of view. (…) you end up with a situation that (…) there's just no space. (…) a good idea is to look at the ceiling heights and make sure that you've got more space. The problem is, the more space you have and the higher the building, the more expensive it is... (Semi structured interview, Management, HS101)
Natural ventilation was not generally recommended within the Trust but does seem to be the only option in some older buildings. Despite this some staff in the older buildings had to seal windows due to nearby building works.
On the whole, mitigation strategies were welcomed as a way of protecting staff and patients and staff were happy with current strategies in place but did share that they would appreciate further isolating rooms and “20 air changes that would be great. (…) that was the envy that I held for other areas. But in terms of [wanting further] technology, not really” (Semistructured interview, Clinical, HS103).
Beyond the challenges already discussed with practices to reduce airborne disease transmission, hospital staff also reflected on the high costs of enhancing ventilation; the limited impact of mitigation strategies on air changes; and the limited number of isolation rooms. Due to financial constraints and need for space, sometimes hospital areas have been repurposed without following the required procedures, resulting in a tension between teams.
…they'll just change the use of a room, but obviously there's a process to go through to do that, to make sure it's safe, but not everybody understands that, and to be honest, they think (...)it's a bit of a fuss and they know it's going to cost them money (...) And if they don't have any money, but yet they desperately need to do something in a space because it's the only space they've got, they're just going to go ahead and do it. (Semi-structured interview, Management, HS101)
Shared goals
Hospital staff interviewed reported the aims of AISaT were a good fit with the Trust’s overall goals of keeping staff and patients safe. Individuals involved in the wider engagement work raised that hospitals are perceived as risky spaces where people can catch infections, so they need to be protected prioritising the most vulnerable. The staff interviewed also described that the AI tool could be a source of reassurance to demonstrate the effectiveness of existing practices and support faster decision-making.
I think it would give everyone reassurance. Certainly, in terms of pandemic or significant heightened risk, it would be helpful, not really for the confidence of the staff, but also the safety of the staff. And it would overcome the challenge we have in not being able to change the footprint of the healthcare facility. (Semi-structured interview, Clinical, HS103)
Interviewees were positive about the potential impact of AISaT on their work as it would make their environment safer, as long as it did not take a lot of their time to input the data into AISaT. A couple of staff raised, that AISaT could guide hospital staff, but also architects and engineers to keep the hospital air clean and optimise staff capacity and space utilization.
If we had a tool like that (...)every time that you had a new space (…) you could run the whole of the design through the AI software, and it would identify where you may (...) add in things at the base build level (…) I can't see a problem with using models to help to help give you the optimum design for a room. It’s a good idea. (Semi-structured interview, Management, HS101)
Anticipated barriers and facilitators to adoption of AISaT
Hospital staff observed and interviewed, and wider stakeholders, pointed that new buildings still have ventilation issues, but that it may be easier to implement AISaT in these settings as they are more likely to have standardised room measurements to comply with the latest regulations. Hospital staff also raised that AISaT would be particularly valued in areas where ventilation cannot be improved systemically across the site (e.g., old buildings).
…in an ideal world, we would have something like a built-in air conditioning system or something that was systemic across the building. But being such an old building and I think the electrical grid is the reason why we couldn't have anything more systemic built-in. So, we're having to rely on things like windows and maintaining good infection control with our isolation in our side rooms… (Semi-structured interview, Clinical, HS102, Clinical, HS102)
Concerns related to staff resistance were raised as “it is quite tricky in a Trust to get them[staff] to accept changes like this and to get them to think it's worthwhile because they can't. They don't necessarily see the value of it.” (Semi-structured interview, Management, HS101). Not seeing a clear benefit from AISaT and its recommended mitigation strategies or not experiencing an immediate benefit would be the main barriers to staff’s engagement. Additional barriers included: the lack of awareness and knowledge around ventilation and the impact that the positioning of mitigation strategies can have; limited digital understanding and guidance; preventative mindset （e.g., acting before it becomes a problem）; and limited trust or confidence in AI in general. Some hospital staff felt the pandemic had raised staff’s awareness of ventilation and they were now actively requiring ventilation improvements within the Trust. Trust in AI was also described as a facilitator for the adoption of AISaT as staff reported AI is becoming more present in daily lives and at work. Also raised was that hospital staff’s workload could be a source of staff’s resistance, however if the AI could reduce workload, it could be seen as a facilitator.
Some hospital staff interviewed and involved in wider engagement work referred to in-patient areas or wards as areas where the implementation would not be a priority given the number of people working within those areas, with the associated movement, the lack of space, connectivity issues within hospitals, and the number of beds which would require several HEPA devices. Wider stakeholder engagement work involving hospital staff encouraged the use of mitigation strategies already existing within the wards and that AISaT should consider the space available and size of any new suggested strategies. Implementation of AISaT in outpatient areas, isolation rooms, labs, or neonatal spaces was more acceptable.
…you have 6-7 patients in there and then some patients, they bring quite a lot of their stuff...they put a lot of things in their cupboard and we have only a small one（…） they need to consider... space （…） It's another tool [HEPA device] that they don't see any results from it. It's just there physically. （…） they're still getting sick. They're still getting infection （…） I don't think anything would eradicate that. They don't see any success to it. They're just thinking, you know, it's another thing that's occupying the space of the patient, that it's unnecessary. It's another tool that...they have to make sure it's on （…） let's be honest, it's not a priority for us to do that. It's not our job...to do that （…） it shouldn't be us who needs to check it. （Semi-structured interview, Clinical, HS108）
Besides some clinicians not feeling dealing with AISaT and the associated mitigation strategies are part of their role, an interviewee was struggling to think in what area of the hospital the AI tool could be of use:
…[AISaT] it's an interesting tool... in certain areas like theatres or operating rooms I don't think they would be useful because if the air changes... will have to depend on the... centralised ventilation system, because...they're essentially critical departments...With the AI tool, I'm not sure where we can use them.（Semi-structured interview, IPC, HS110）
Stakeholders mentioned that PPE may be seen as a cheaper alternative to the mitigation strategies AISaT may be offering. This was in contrast with several staff members mentioning the inconvenience of working with PPE “It's not amazing, to be honest, if you can imagine doing quite a difficult procedure over a pronounced amount of time wearing masks and PPE is not amazing.” （Semi-structured interview, Clinical, HS112） particularly in buildings with poorly balanced temperatures.
Although hospital staff did not perceive the need for further mitigation strategies, and some failed to see the point of AISaT, the benefits, such as staff and patient benefit and cost reductions, may be needed to make AISaT attractive to hospital staff （see section 4）.
People's time is the crux. （…） you can usually win hearts and minds from people if they can really see a benefit to a bit of effort that they might have to put in during implementation. But if they can see that this is going to reduce my staff sickness is going to mean I've got less patients getting cross infected on the wards. And I'm going to have my beds all open and not closed due to infection. I think they're massive pluses. (Semi-structured interview, Management, HS111)
Requirements for AISaT’s implementation
Hospital staff and wider stakeholders suggested using a series of strategies to facilitate implementation and a future roll out of AISaT. Most discussed was buy-in from senior staff (e.g., the chief executive, IPC director, and authorising engineers), board members, but also identifying champions on the ground.
Your best bet is to go to the director of infection control and prevention. If he was interested and if he thought it was an advantage, I would say that would be a good place to start. (…) If you could get [Chief Executive] interested, obviously that would be the best person (...) if he was interested and thought it was a good idea and it was protecting his patients. (Semistructured interview, Management, HS101)
Clear communication was recommended, with staff and patients, about what is needed from users and about AISaT complementing human-decision making. Also raised was the need to transparently report how AISaT is better than a human, how the AI works, and clarity on its benefits as well as its limitations.
Wider stakeholder work suggested that gaining support from recognised bodies would also be required, through appearance in guidelines such as NICE; dissemination at national meetings (National Clinical Engineering, Ventilation Teams Meetings); and having the support of medical organisations.
Providing training on AISaT to hospital staff who would subsequently use it or work around it could facilitate its uptake and build trust in the AI tool. Ensuring all staff were involved in training would be positive, to promote inclusivity and facilitate the acceptability of AISaT. Stakeholders thought training should include ventilation, the relevance of positioning the mitigation strategies, and AISaT itself. One interviewee doubted the need for training as they envisaged the implementation of AISaT as a one-off interaction with an external contractor. Another participant cautioned that colleagues may not react well to training on ventilation when they are faced with poor ventilation levels, high temperatures, and unable to open (sealed) windows or use fans due to electrical supply limitations and scarcity of sockets.
I think it [training] would be beneficial, but I think the response would be…interesting. (…) we've had such challenges every summer...where it's been very hot on the ward and we've had to use fans and…We're trying to as best as we can to isolate these patients who've got airborne infections to then talk about ventilation and the joys of ventilation. I think that may not be received as well. (Semi-structured interview, Clinical, HS102)
Hospital staff were generally cautious and expressed concerns about the need for appropriate validation and assurances that the AI would be providing safe recommendations. This caution was not necessarily negative as “proper use of it could really help ease our workflow (…) having it do the recommendations for you and then you just check it makes it convenient” (Semi-structured interview, IPC, HS113). However, some interviewees stated they could not comment on the acceptability and potential to implement AISaT without having seen it, and knowing in detail how had been trained, or having a summary of its impact when used within the hospital environment.
2.		Cognitive Participation (How will staff engage with AISaT and its recommended mitigation strategies?)
Decision making and ownership of AISaT
It was agreed that early staff engagement would be required, not only to gather their views to develop AISaT but to facilitate the decision-making process of who should take ownership of the AI tool. Similar to current practice, the development of a multidisciplinary working group would ensure the decision-making was not “down to a person” but to a multidisciplinary team to determine whether AISaT should be used, and the details on when and how.
First funding would need to be sought. Then, the contractor (<HS104> and their team) would gather evidence and information about AISaT. Then they would present the idea to the Committee. If the Committee agrees, then they would need to ensure buy -in from IPC. Discussions between estates, medical and IPC teams would need to happen to explore what effect is this going to have (e.g., having to close an area to assess the impact of adding new HEPA filters or placing them where AISaT suggests) and would provide suggestions as to how this effect could be managed. Nine out of ten times medical teams and IPC will say no; the area cannot be closed and there will need to be negotiations until there is agreement between all parts. This may mean that the implementation does not occur soon. (Ethnographic observations, notes from informal conversation, Estates, HS104)
An interviewee suggested a similar process of group decision making when choosing from the recommended mitigation strategies suggested by AISaT.
…the decision will not ultimately be from one person. It's always a multidisciplinary thing...you'll have to present the options to the end users, to other experts to see what is really the best option in practise. (Semi-structured interview, IPC, HS110)
Another interviewee suggested that implementation of AISaT should come as an imposition from IPC rather than an exercise requiring hospital staff’s engagement and acceptance.
I think for this realistically it wouldn't so much be staff engagement and encouragement, it would be imposed. So, if it's supported, it would be supported on one ground or another, be a patient safety or financial and they would be imposed. (Semi-structured interview, Clinical HS103)
On this line, another interviewee wondered whether the strategies shared by AISaT would be recommendations (something staff could choose to follow or not) or actual policy they would need to follow. If the latter, current policies on this area come from the Trust and from IPC and any AISaT recommendations should be aligned with those existing policies.
Despite most participants being in favour of a multidisciplinary effort involving IPC, Clinical Estates and Operations for AISaT implementation, none of the participants suggested they or their team would be involved in leading the implementation of a tool like AISaT. Only one infection and prevention control (IPC) staff member agreed when prompted by the researcher that IPC may be best positioned to lead on AISaT’s implementation.
Well, it could fall under IPC... 'cause sometimes with estates, if we let them lead on it...some trusts outsource them. So, I do get the point of IPC trying to lead on this... I would agree, it’s part of the things that we check and that we try to enforce as a team to ensure that the ventilation throughout the hospital is good. So yeah, I think we can take a lead on it. (Semistructured interview, IPC, HS113)
Most hospital staff involved in interviews and wider stakeholder work placed ownership on IPC “infection control [IPC] (…) can oversee the project because (…) when it comes to infection, they need to be involved in that” (Semi-structured interview, Clinical, HS109) and given their cross-Trust presence. One interviewee pointed that IPC “are good at imposing things” (HS103) and that this project’s implementation would need to be imposed. Contrasting this an IPC staff member insisted this would be a role for the estates team who have expertise in ventilation and lead critical ventilation meetings.
I think it should be a multidisciplinary approach on the initial stages until we all have a full understanding of...how it works in practise. But I think ultimately it will have to be estates leading on it. Obviously with our...expert input from ...clinical areas, IPC, ventilation engineers...Anything ventilation related would fall under estates responsibility. (Semistructured interview, IPC, HS110)
There were mixed opinions among hospital staff involved in interviews and wider stakeholder work who felt so long as staffing costs were funded, then the inputting of data into AISaT could fall under estates, or engineers or IPC.
There was more agreement in the cascading down of decisions where estates and facilities teams would be the ones in charge of cleaning, maintaining and replacing the recommended devices or equipment to mitigate airborne transmission of infections. Participants further raised if the HEPA filters are considered non-medical devices, then installation could come from estates.
Content and design of AISaT
There was a difference in opinions on how AISaT should be designed to facilitate its uptake. Some hospital staff thought a ranking of potential mitigation strategies that are the best at preventing airborne transmission of infection should be provided. They felt that regardless of lack of availability within the Trust, staff having a comprehensive list may help the Trust push to purchase these items, especially in preparation for a future pandemic. Others suggested a ranked list should only contain mitigation strategies available within the Trust as it may create anxiety among staff if they do not have access to the best rated options, or they may get “overwhelmed” (HS113) by a list of endless options.
Interviewees shared some technical factors that may help with the implementation of AISaT this included: ease of use, integrating AISaT within NHS systems (or whitelisting websites / the AI tool); compatibility with diverse devices such as computers and iPads; facilitation of automatic data entry through lidar software to capture room dimension, or importing patients’ data from Electronic Health Records. A participant recalled getting “the [floor] plans for most ward spaces in COVID. (…) I can't imagine it would be staff measuring spaces.” (Semi-structured interview, Clinical, HS103) when it came to discussing who would be responsible for inputting data into AISaT.
Further suggestions on AISaT’s functionality included its ability to perform a risk assessment for use of physical separation equipment and an air filter (e.g., HEPA device) with a prediction model to alert staff of outbreak risks. Also suggested was demonstrating through AISaT the variable cost of a mitigation strategy which could help to choose from what is available in the market. The ethnographic work suggested it would be helpful if AISaT could keep record of a HEPA filters performance and dates of installation, and other stakeholders suggested AISaT could include reminders to staff to attend PPE fit testing. It was suggested that AISaT should account for movement and that it should take account of the fact staff may be contagious. This is particularly relevant in wards with more vulnerable patients who are usually seen by a range of staff. Two clinical hospital staff members also reflected on the need to involve clinical experts to tailor the AI tool to the needs of different areas with different ventilation needs.
…you need people or clinical staff that understand their local areas so you can tailor it for the area that you're using it in because each procedure each diagnosis, medical diagnosis, etcetera has a different outcome for every different area (Semi-structured interview, Clinical HS112)
Timing of AISaT implementation
Among interviewees many agreed that implementation of AISaT was not a priority now, but it would become priority in future pandemics and, hence, highlighted the relevance of this research. However, about one third of those interviewed felt AISaT is currently relevant for prevention of infection
I'd hope that you could use it every day, because I'd hope it would really help us to prevent cross infection, prevent outbreaks...So I think... for prevention, be proactively using it... I'm sure it's useful...in a pandemic or an outbreak as well. But...I'd want to use it before you got to that point. I’m completely with...try to prevent it and control it. (Semi-structured interview Management, HS111)
3.		Collective Action (How will staff work to implement AISaT and its recommended mitigation strategies?)
This section focuses on the practical points that need to be considered for AISaT to be implemented and integrated into daily routines of hospital staff.
Identification of resources
Often hospital staff were unclear about who would fund the implementation and roll out of AISaT and its recommendations. When hospital staff had suggestions, they mentioned “maybe NHSE can provide a sponsorship if we're looking into a bigger perspective of the whole UK” (Semi-structured interview, Clinical, HS109). However, there were also suggestions that “executives would agree to fund from... a central pot because it's not one area (Semi-structured interview, Management, HS111)” or that Integrated Care Boards (ICBs) should be able to provide funding or suggestions of possible funding. The need to develop a business plan to cost staff and time required for the implementation of AISaT and its recommendations was mooted.
Likewise, hospital staff interviewed and involved in wider stakeholder work raised concerns about the costs to maintain the mitigation strategies (e.g. HEPA filters), as well as impact of maintenance on staff’s workload and capacity. They also referred to the high costs of making changes to ventilation systems and that any changes must meet latest guidelines or Health Technical Memoranda (HTMs). Conversations reflected the items costs (e.g., AISaT and implementing its recommendations), the associated staff costs (e.g., data entry into the AI tool, deliver on maintenance plans, etc.), and concerns as to whether the Trust would be willing to invest in AISaT and its recommended mitigation strategies even if the trial proved its effectiveness.
I think with the amount of (...)maintenance involved like routine cleaning, routine maintenance, reporting of equipment that's faulty, it's already a bit of a challenge just on day-to-day with clinical items that patients use(...) It can be quite challenging on a large [busy] ward (…)and a substantial service to then add another item in there that isn't immediately impacting the day-to-day tasks or benefiting the patients in that immediately visible way It can be a barrier. (Semi-structured interview, Clinical, HS102)
As previously mentioned, an interviewee envisaged AISaT being used by an external contractor, as the rooms of interest would usually maintain their size and characteristics and so the need to enter data into AISaT and to choose a recommended mitigation strategy was perceived as a one-off action. Such implementation was seen as advantageous as it would not impact staff’s capacity or require further training. In successive interviews, further hospital staff members agreed this could be a feasible option to facilitate implementation without negatively impacting on staff’s workload.
…Like a contractor. (…) Yeah, like I said... it's just another thing to think of and we already have a load of things...you know, pressured. So you...don't want to commit to something that you can't really [do]. (Semi-structured interview, Clinical, HS108)
Generalisability and sustainability
Hospital staff interviewed raised that communication among staff could become a barrier to the implementation of AISaT when different members of staff work on similar issues but from different teams such as the NHS and contractors working together. Also raised was fragmentation in how different Trusts incorporate new devices, and a lack of guidelines on how to integrate new digital developments into hospitals, which would take a long time to develop. Unsurprisingly, the acquiring of funding for AISaT implementation may also be different across Trusts.
Access restrictions were also identified as barriers by hospital staff involved in wider stakeholder work regarding data on room characteristics (e.g., size, height, objects in the room, ventilation characteristics) and floor maps. Difficulties may also arise when attempting to import data as floor maps are often in PDF format instead of in electronic formats that could be easily exported. Different hospital buildings, even within the same Trust, also have different levels of data available within their records. This would, therefore, require manual data entry which would need to be costed in terms of staff time.
The ethnographic work suggested that the implementation of AISaT and its recommended mitigation strategies would need approval from multi-disciplinary committees. The implementation timing would need to be agreed, as it is not uncommon for projects to be approved but face delays in green lights for actual implementation. Within the approval process the different management systems in different buildings (e.g., privately funded or NHS maintained) would need to be factored in as there are differences in these processes even for buildings within the same Trust. In privately funded buildings, for instance, there is the need to factor in the landlord’s position regarding the implementation of AISaT and its mitigation strategies.
Don't forget that this building is not owned by the NHS. It's rented. They [Landlords] would need to be in agreement with it, so you'd have to bring them in if potentially you were thinking about that [installation of mitigation strategies]. (Semi-structured interview, Clinical, HS112)
4.		Reflexive Monitoring (How will people assess the success of AISaT and its recommended mitigation strategies?)
This section addresses how stakeholders and staff anticipated the intervention would be evaluated by the Trust and hospital staff to support its implementation.
Providing key metrics and assurances
Hospital staff interviewed referred to the need to prove the effectiveness of AISaT addressing the three NHS priorities: costs, effectiveness and implementation practicalities. Key metrics should include those of interest for IPC such as the extent AISaT reduces infections; whether it has an impact on staff, patients or both; whether it leads to bed days savings or fewer closed beds, fewer appointment cancellations (in out-patients); and reduction of outbreaks. But also, the extent it is effective such as the impact in air changes per hour; its energy and financial savings (e.g., reduction of costs to ventilate an area). It would need to produce benefits on safety grounds but also need to lead to financial benefits.
…they're pushing for sustainability and they're pushing for capacity, bed capacity, patients flow and reduction of infections as such. And it would help the hospital if it's done properly, that they have seen all the areas of concerns before they actually invest into something. Because...we've seen some projects that had been invested, they've spent quite a lot of money, but it hasn't been pushed through...before the commitment to be set out there, they really need to make sure that this is... worth it to the benefit of the hospital, the patients and the staff. (Semi-structured interview, Clinical, HS108)
Beyond the health economics assessment, hospital staff also raised the need for expert validation to explore to what extent AISaT’s recommendations are aligned with gold standards, and evaluate differences between human and AISaT , to explain why AISaT is better.
As long as we're happy that it's...tested and validated and that there's always the double check until we've got confidence that it does actually predict. I think there's got to be that validation process continually (…) sort of accuracy tolerances built-in. (…) Because it's there's a lot at stake if it takes us to the wrong decision or the wrong action. (Semistructured interview, Management, HS111)
Participants also suggested the need for live monitoring of the quality of the air in parallel to the implementation of AISaT and its recommended mitigation strategies.
If introducing HEPA, there would need to be a live measurement of pressure, as this will tell them when the filter is filled and needs changing. (Ethnographic observations, notes from informal conversation, Estates, HS106 and HS107)
Futureproofing AISaT
Interviews with hospital staff and conversations with those involved in wider stakeholder engagement referred to the need to develop AISaT to be able to adapt to different technologies (e.g. PC, phones, tablets and advancements in these devices), settings (e.g., different hospitals and room characteristics), and policy, as these are likely to evolve with time. When considering preparedness for the future, an individual involved in the wider stakeholder engagement work raised the need to confirm who would be responsible for refining and providing technical support to hospitals following the research trial or development phase of AISaT, showing concerns about the ongoing feasibility and ownership of AISaT.
Discussion
This paper explores the anticipated barriers and facilitators to the implementation of AISaT. Our findings, conceptualised within the Normalisation Process Theory, suggest that while AISaT and its recommended mitigation strategies are generally positively received, their wide implementation may be hindered by its associated maintenance and staff costs; the lack of perceived need and immediately observable benefits; and organizational differences within Trusts and hospital buildings.
1.		Coherence (How do staff understand AISaT and its recommended mitigation strategies?)
Coherence was variable across hospital staff. While hospital staff in organisational roles anticipated AISaT’s usefulness in their daily work, hospital staff in clinical and IPC roles were more divided on the value of AISaT tool, with some reluctant to share their views on AISaTs potential prior to reviewing results from a clinical trial. The main risks to AISaT’s implementation were that existing strategies used within hospitals such as fixed ventilation systems are hard to change and may be different to the strategies AISaT may recommend, which are likely to involve portable HEPA filters. Additional risks to AISaTs implementation were the challenges associated with HEPA devices and the lack of standardised rooms in old NHS buildings. A number of additional challenges have also been identified, such as PPE being seen as a more economical alternative; that hand-wash and isolation rooms are being prioritised in current guidelines24; and that hospital staff felt improving air changes should be prioritised whereas it AISaT’s current prioritisation is focused on diminishing aerosol concentrations. The main enablers identified related to the implementation of AISaT in outpatient areas; ensuring the AISaT interface is easy-to-use and responding to staff’s needs; buy-in from senior staff and its dissemination through national guidelines.
2.		Cognitive Participation (How will staff engage with AISaT and mitigation strategies?)
Cognitive participation is anticipated to depend on multidisciplinary decision making on the implementation of AISaT and its recommendations and having champions to cascade decisions down and encourage implementation in the ground. Barriers to implementation could be overcome by imposing the use of AISaT rather than relying on staff’s engagement. Imposition, however, would come with the inherent risk of losing the feeling of shared ownership which would add to a lack of agency among staff. The implementation of AISaT was often not perceived as a priority, in a climate where staff feel overloaded, there are increasing financial constraints, and direct patient care is the most pressing matter.
3.		Collective Action (How will staff work to implement AISaT and recommended mitigation strategies?)
Collective action is anticipated to be impacted by costs associated with the implementation and maintenance of AISaT and its recommended mitigation strategies; the fragmented implementation of AI tools and devices within Trusts; restrictions in accessing data; and variations in approval processes within Trusts and buildings. While it was suggested that AISaT could be best integrated within a comprehensive Electronic Health Record, this comes with an added layer of difficulty since Electronic Health Records systems are not universally used across UK hospitals which would require further adaptations to different systems used. This is a known generalisability issue previously identified in the literature25,26. An enabler identified was the external implementation of AISaT (e.g. by a contractor), reducing its impact on staff workload.
4.		Reflexive Monitoring (How will people assess the success of AISaT and mitigation strategies?)
Reflexive monitoring is anticipated to derive from expert validation and evidence on effectiveness and impact prior to the implementation of AISaT. A risk identified is the need for future refinement support that is unclear after the end of this project.
Comparison with prior work
Our findings are consistent with those of a recent systematic review where AI implementation within hospital was found to be influenced by understanding and trust on AI, quantification of the benefits of the AI, external validation to facilitate generalisation, costs of implementing the AI, training staff and maintaining the AI, and the availability of policies to fund and regulate AI solutions19. However our findings also point towards other critical elements such as specific environmental characteristics where the AI and mitigation strategies will be implemented (e.g., old buildings with busy and crowded wards, with scarce space and overloaded hospital staff) together with the priority given to AISaT and its mitigation strategies within the existing ways of working and measures already available. These findings also align well with a recent criticism to the NHS 10-year plan that AI implementation cannot sort the whole structural issues within the NHS like the constrained budgets27. Beyond our focus on AISaT’s implementation but very closely related, difficulties to the use of HEPA devices such as noise which had been previously reported in the literature2 , did not preclude its hospital wide use though ventilation outlets installed in ceilings. This is in line with HEPA filters being the most common mitigation strategy used in hospitals to reduce airborne disease transmission within papers included in a recent review 1 , subsequent research29, and aligned with estates technical guidelines30. Although the review reported improvements in patients’ health outcomes1 , some stakeholders included in our study stressed the lack of RCTs proving HEPA devices’ effectiveness.
Strengths and limitations
This work involved extensive stakeholder engagement work, capturing views from the public subject matter experts, and hospital healthcare professionals, which helped identify a common ground, but also areas of discordance between accounts even among professionals with similar job roles. This study is not without limitations, we struggled accessing the hospital environment for further ethnographic work, only being able to observe estates work within one building. Difficulties may have been aggravated by the timing of our research during flu season. Furthermore, AISaT was under development at the time of conducting this study, and hence neither researchers or participants had a tangible idea of what the tool would look like. This may have made it difficult for hospital staff and stakeholders to provide more specific responses and imagine how its implementation could look like in practice. Future research should involve relevant stakeholders in designing user friendly AI tools and seeking their feedback with demonstrations of the product to visualise the end-product and think of ways to implement it in their practice.
Conclusions
Even when AISaT and its recommended mitigation strategies are not considered a priority within the hospital environment now, even in a climate of tight budgets, staff shortages and heavy workloads staff demonstrated a willingness to accommodate AI innovations if the effectiveness and benefits are proved and shared with them.
Acknowledgments
We would like to thank all stakeholders involved in this study, from those involved in wider stakeholder engagement work (via patient advisory group meetings, the National leaders’ workshop and follow-up conversations) to those being observed and interviewed as part of this study. We would like to thank to Mr Simon Watt (Public Engagement Manager) for his work in recruiting managing and facilitating patient advisory group meetings; Ms Anna Byrne (Air Safety Programme Manager) for her work identifying and inviting National Leaders to the workshop; and the Air Safety’s Project Team for their collaboration and support through this study.
Funding
This study is funded by the National Institute for Health and Care Research (NIHR) under its Programme Grants for Applied Research Programme (Ref: NIHR205439). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.
Prof Vindrola and Sigrun Clark were partially supported by the NIHR Central London Patient Safety
Research Collaboration (CL PSRC), reference number NIHR204297.
Authors’ Contributions
Conceptualization – YBM (lead), FS (supporting), CVP (supporting), ZK (supporting), LBL (supporting)
Data curation – YBM
Formal analysis – YBM (lead), SM (supporting)
Funding acquisition – LBL (lead), FS (supporting), CVP (supporting), ZK (supporting) Investigation – YBM (lead), FS (supporting), SM (supporting), SEC (supporting), ZK (supporting) Methodology – FS (lead), CVP (supporting), ZK (supporting), YBM (supporting)
Project administration – YBM
Supervision – FS
Writing – original draft – YBM
Writing – review & editing – YBM, FS, SEC, LBL, ZK, SM, CVP
Conflicts of Interest
None declared.
Data Availability
Data that support the findings of this study are not publicly available due to their containing information that could identify participants and they did not provide consent to this data being shared outside the research team beyond anonymised quotes in publications. If you would like more information about the nature of the data, please contact the corresponding author.
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Summary of types of data collected.

Consolidated criteria for reporting qualitative research (coreq): 32-item checklist.
URL: http://asset.jmir.pub/assets/e92550c2bd9c703fa5a2eff25eb3c0dc.doc
Determinants of implementation of AISaT identified through wider stakeholder engagement. URL: http://asset.jmir.pub/assets/0db327be457bf39735c8ed15674f1528.doc
Ethnographic observations sheet.
URL: http://asset.jmir.pub/assets/f73b861c4440d76d11577b425ea44ba0.doc
Semi-structured interview topic guide.
URL: http://asset.jmir.pub/assets/6d5ed587efbf4acc6f1b470cb28a3475.doc