Understanding the integration of artificial intelligence in healthcare organisations and systems through the NASSS framework: a qualitative study in a leading Canadian academic centre

BACKGROUND

Artificial intelligence (AI) technologies are expected to "revolutionise" healthcare. However, despite their promises, their integration within healthcare organisations and systems remains limited. The objective of this study is to explore and understand the systemic challenges and implications of their integration in a leading Canadian academic hospital.

METHODS

Semi-structured interviews were conducted with 29 stakeholders concerned by the integration of a large set of AI technologies within the organisation (e.g., managers, clinicians, researchers, patients, technology providers). Data were collected and analysed using the Non-Adoption, Abandonment, Scale-up, Spread, Sustainability (NASSS) framework.

RESULTS

Among enabling factors and conditions, our findings highlight: a supportive organisational culture and leadership leading to a coherent organisational innovation narrative; mutual trust and transparent communication between senior management and frontline teams; the presence of champions, translators, and boundary spanners for AI able to build bridges and trust; and the capacity to attract technical and clinical talents and expertise. Constraints and barriers include: contrasting definitions of the value of AI technologies and ways to measure such value; lack of real-life and context-based evidence; varying patients' digital and health literacy capacities; misalignments between organisational dynamics, clinical and administrative processes, infrastructures, and AI technologies; lack of funding mechanisms covering the implementation, adaptation, and expertise required; challenges arising from practice change, new expertise development, and professional identities; lack of official professional, reimbursement, and insurance guidelines; lack of pre- and post-market approval legal and governance frameworks; diversity of the business and financing models for AI technologies; and misalignments between investors' priorities and the needs and expectations of healthcare organisations and systems.

CONCLUSION

Thanks to the multidimensional NASSS framework, this study provides original insights and a detailed learning base for analysing AI technologies in healthcare from a thorough socio-technical perspective. Our findings highlight the importance of considering the complexity characterising healthcare organisations and systems in current efforts to introduce AI technologies within clinical routines. This study adds to the existing literature and can inform decision-making towards a judicious, responsible, and sustainable integration of these technologies in healthcare organisations and systems.

Telemedicine perceptions and experiences of socially vulnerable households during the early stages of the COVID-19 pandemic: a qualitative study

BACKGROUND

Early in the COVID-19 pandemic, efforts to decrease risk of viral transmission triggered an abrupt shift from ambulatory health care delivery toward telemedicine. In this study, we explore the perceptions and experiences of telemedicine among socially vulnerable households and suggest strategies to increase equity in telemedicine access.

METHODS

Conducted between August 2020 and February 2021, this exploratory qualitative study involved in-depth interviews with members of socially vulnerable households needing health care. Participants were recruited from a food bank and primary care practice in Montréal. Digitally recorded telephone interviews focused on experiences and perceptions related to telemedicine access and use. In our thematic analysis, we employed the framework method to facilitate comparison, and the identification of patterns and themes.

RESULTS

Twenty-nine participants were interviewed, 48% of whom presented as women. Almost all sought health care in the early stages of the pandemic, 69% of which was received via telemedicine. Four themes emerged from the analysis: delays in seeking health care owing to competing priorities and perceptions that COVID-19-related health care took precedence; challenges with appointment booking and logistics given complex online systems, administrative inefficiencies, long wait times and missed calls; issues around quality and continuity of care; and conditional acceptance of telemedicine for certain health problems, and in exceptional circumstances.

INTERPRETATION

Early in the pandemic, participants report telemedicine delivery did not accommodate the diverse needs and capacities of socially vulnerable populations. Patient education, logistical support and care delivery by a trusted provider are suggested solutions, in addition to policies supporting digital equity and quality standards to promote telemedicine access and appropriate use.

Trajectories of psychological distress during the COVID-19 pandemic among community-dwelling older adults in Quebec: A longitudinal study

OBJECTIVE

The COVID-19 pandemic and its associated public health measures may increase the risk for psychological distress among vulnerable older adults. This longitudinal study aimed to identify predictors of psychological distress trajectories among community-dwelling older adults in Quebec, Canada.

METHODS

The study spanned four time points across 13 months and three waves of the COVID-19 pandemic. The sample included 645 community-dwelling older adults ages 60 years and older in Quebec. Participants completed telephone-based interviews that included the Kessler 6-item Psychological Distress Scale (K6) to assess psychological distress at each time point as well as information on socioeconomic, medical, psychological and COVID-19 related factors. Group-based trajectory modelling was used to identify distinct trajectories of psychological distress across time.

RESULTS

Three group-based trajectories of psychological distress were identified: the resilient (50.5%), reactive (34.9%), and elevated distress groups (14.6%). Individuals with mobility issues, insomnia symptoms, COVID-19 related acute stress, general health anxiety, increased loneliness symptoms, and those unable to use technology to see others were more likely to be in the reactive and elevated groups than the resilient group. Those with past mental health problems had uniquely increased odds of being in the reactive group compared to the resilient group. Individuals living in poverty and those who reported taking psychotropic medication had increased odds of being in the elevated distress group compared to the resilient group.

CONCLUSION

These findings characterized distinct trajectories of psychological distress in older adults and identified risk factors for elevated distress levels.

Virtual Care and the Inverse Care Law: Implications for Policy, Practice, Research, Public and Patients

Virtual care spread rapidly at the outbreak of the COVID-19 pandemic. Restricting in-person contact contributed to reducing the spread of infection and saved lives. However, the benefits of virtual care were not evenly distributed within and across social groups, and existing inequalities became exacerbated for those unable to fully access to, or benefit from virtual services. This "perspective" paper discusses the extent to which challenges in virtual care access and use in the context of COVID-19 follow the Inverse Care Law. The latter stipulates that the availability and quality of health care is inversely proportionate to the level of population health needs. We highlight the inequalities affecting some disadvantaged populations' access to, and use of public and private virtual care, and contrast this with a utopian vision of technology as the "solution to everything". In public and universal health systems, the Inverse Care Law may manifests itself in access issues, capacity, and/or lack of perceived benefit to use digital technologies, as well as in data poverty. For commercial "Direct-To-Consumer" services, all of the above may be encouraged via a consumerist (i.e., profit-oriented) approach, limited and episodic services, or the use of low direct cost platforms. With virtual care rapidly growing, we set out ways forward for policy, practice, and research to ensure virtual care benefits for everyone, which include: (1) pay more attention to "capabilities" supporting access and use of virtual care; (2) consider digital technologies as a basic human right that should be automatically taken into account, not only in health policies, but also in social policies; (3) take more seriously the impact of the digital economy on equity, notably through a greater state involvement in co-constructing "public health value" through innovation; and (4) reconsider the dominant digital innovation research paradigm to better recognize the contexts, factors, and conditions that influence access to and use of virtual care by different groups.