AI in Health from Challenges to Impacts Through the Case Study of the Valenciennes Hospital Center

Artificial Intelligence (AI)-powered healthcare has the potential to revolutionize national healthcare systems especially during stressful times. Research has shown that there are ethical and managerial challenges associated with health AI, and our work aims to deepen knowledge on these challenges and their impacts. Our case study focused on the Valenciennes Hospital Center (CHV) in France, where an AI solution has been deployed to predict flows in the emergency department. Through 32 semi-structured interviews with professionals, we were able to identify the real tensions caused by the ethical and managerial challenges of AI. However, our study also showed that health organizations can take advantage of AI to reduce these tensions and strengthen individual skills, leading to better organizational performance. Our work contributes to the IS literature on health AI by highlighting the impacts in terms of appropriation, and relationships between entities of the same organization

Novel functional hepatitis C virus glycoprotein isolates identified using an optimised viral pseudotype entry assay

Retrovirus pseudotypes are a highly tractable model used to study the entry pathways of enveloped viruses. This model has been extensively applied to the study of the hepatitis C virus (HCV) entry pathway, pre-clinical screening of antiviral antibodies and for assessing the phenotype of patient-derived viruses using HCV pseudoparticles (HCVpp) possessing the HCV E1 and E2 glycoproteins. However, not all patient-isolated clones produce particles that are infectious in this model. This study investigated factors that might limit phenotyping of patient-isolated HCV glycoproteins. Genetically related HCV glycoproteins from individual patient quasispecies were discovered to behave very differently in this entry model. Empirical optimisation of the ratio of packaging construct and glycoprotein-encoding plasmid was required for successful HCVpp genesis for different clones. The selection of retroviral packaging construct also influenced the function of HCV pseudoparticles. Some glycoprotein constructs tolerated a wide range of assay parameters, while others were much more sensitive to alterations. Furthermore, glycoproteins previously characterised as unable to mediate entry were found to be functional. These findings were validated using chimeric cell-cultured HCV bearing these glycoproteins. Using the same empirical approach we demonstrated that generation of infectious ebolavirus pseudoviruses (EBOVpv) were also sensitive to the amount, and ratio, of plasmids used, and that protocols for optimal production of these pseudoviruses is dependent on the exact virus glycoprotein construct. These findings demonstrate that it is crucial for studies utilising pseudoviruses to conduct empirical optimisation of pseudotype production for each specific glycoprotein sequence to achieve optimal titres and facilitate accurate phenotyping

L’Intelligence Artificielle dans un Hôpital à la Croisée des Tensions Paradoxales de la Transformation Digitale

Les recherches sur la transformation digitale (DT) signalent des opportunités de nouveaux modèles théoriques. La DT implique la transformation d\u27une organisation informatique en une organisation digitale basée les ressources digitales, comme l\u27intelligence artificielle (IA). Cette transformation révèle souvent des paradoxes, mais les recherches n\u27ont pas abordé les tensions liées à la DT basée sur l\u27IA en santé. Pour combler cette lacune, nous menons une étude multi-cas dans un hôpital français (CHX) engagé dans un programme de DT basé sur l\u27IA. Cette étude vise à éclairer les tensions paradoxales de la DT basée sur l’IA

AI in Health from Challenges to Impacts Through the Case Study of the Valenciennes Hospital Center

International audienceArtificial Intelligence (AI)-powered healthcare has the potential to revolutionize national healthcare systems especially during stressful times. Research has shown that there are ethical and managerial challenges associated with health AI, and our work aims to deepen knowledge on these challenges and their impacts. Our case study focused on the Valenciennes Hospital Center (CHV) in France, where an AI solution has been deployed to predict flows in the emergency department. Through 32 semi-structured interviews with professionals, we were able to identify the real tensions caused by the ethical and managerial challenges of AI. However, our study also showed that health organizations can take advantage of AI to reduce these tensions and strengthen individual skills, leading to better organizational performance. Our work contributes to the IS literature on health AI by highlighting the impacts in terms of appropriation, and relationships between entities of the same organization

Les chemins tortueux de la transformation digitale d’un hôpital

International audienceLa transformation digitale (DT) dans une organisation pluraliste, notamment un hôpital, est un sujet hautement d’actualité car le secteur de la santé expérimente beaucoup d’initiatives de DT. Cette recherche examine l’inertie organisationnelle et son impact potentiel sur la DT dans un environnement complexe. Notre étude de cas souligne les dynamiques inertielles impulsées par la DT dans un hôpital. Notre analyse, ancrée dans la littérature existante, affine les modèles théoriques et fournit des informations pratiques aux professionnels de la santé

L’Intelligence Artificielle dans un Hôpital à la Croisée des Tensions Paradoxales de la Transformation Digitale

International audienceLes recherches sur la transformation digitale (DT) signalent des opportunités de nouveaux modèles théoriques. La DT implique la transformation d'une organisation informatique en une organisation digitale basée les ressources digitales, comme l'intelligence artificielle (IA). Cette transformation révèle souvent des paradoxes, mais les recherches n'ont pas abordé les tensions liées à la DT basée sur l'IA en santé. Pour combler cette lacune, nous menons une étude multi-cas dans un hôpital français (CHX) engagé dans un programme de DT basé sur l'IA. Cette étude vise à éclairer les tensions paradoxales de la DT basée sur l’IA

Les défis éthiques et managériaux de l'IA dans le secteur de la santé : une revue systématique de littérature

International audienceAre recent developments in Artificial Intelligence (AI) the solution to the crises facing the health sector? Experiments at the initiative of public authorities, large technological companies and healthcare organizations have experienced dazzling progress in recent years, as hopes are so high. The research objective of this paper is to achieve a systematic literature review on the AI technologies in the healthcare sector. The results reveal ethical and managerial challenges that arise from the perception of actors confronted with AI. These issues are included in a conceptual framework that provides a better understanding of the influence of actors' perceptions on the success of AI in health. Finally, this research allows to identify futures research avenues, a sign that this theme is richly promising for Information Systems research.Les développements récents de l'Intelligence Artificielle (IA) sont-ils la solution aux crises que traversent le secteur de la santé ? Les expérimentations à l'initiative des pouvoirs publics, des grandes sociétés technologiques et des organisations de soin connaissent ces dernières années une progression fulgurante tant les espoirs sont immenses. Cette étude a pour objectif de réaliser une revue de littérature sur les technologies de l'IA dans le secteur de la santé. Les résultats font apparaître des défis éthiques et managériaux qui naissent de la perception des acteurs confrontés à l'IA. Ces défis sont repris dans un cadre conceptuel qui permet de mieux appréhender l'influence des perceptions des acteurs sur la réussite de l'IA en santé. Enfin, ces travaux ont permis de dégager plusieurs pistes de recherche, signe que ce thème est riche et prometteur pour la recherche en management des systèmes d'information