MUSA – Spoke 2 WP5 Task 3

Multilayered Urban Sustainability Action; Spoke 2: Big Data-Open Data in Life Sciences; WP5: Develop, implement and sustain technological innovation in health; Task 3: Support innovation implementation

Grant agreement ID: nr. ECS 000037 

Principal investigator: Giulia Cappellaro (Bocconi, CeRGAS) 

Team UB/Cergas: Vittoria Ardito, Giulia Cappellaro, Amelia Compagni, Francesco Petracca, Luigi Maria Preti (CeRGAS) 

Partners: Politecnico di Milano 

Sponsor: European Union – NextGenerationEU, under the National Recovery and Resilience Plan (NRRP) Mission 4 Component 2 Investment Line 1.5 (Strengthening of research structures and creation of R&D “innovation ecosystems”, set up of “territorial leaders in R&D”) 

Duration: 3 years (September 2022 – August 2025) 

Abstract: 

The MUSA project has a broad scope, which is turning the Milan Metropolitan Area (MMA) into an ecosystem of innovation for urban regeneration from multiple perspectives, e.g. from the adoption of smart mobility models to the digitalization of platforms for biomedical data collection and use to improve citizens’ health and wellbeing. In this frame, the activities conducted under Spoke 2, WP5, Task 3 focus on investigating the implementation of artificial intelligence (AI) and machine learning (ML) applications within healthcare organizations, with a particular interest on understanding the resulting success factors, barriers, and implications at the organizational level (e.g., in terms of staff, healthcare delivery processes, patient pathway, and other relevant dimensions). 

The task ultimately aims at developing a conceptual framework for the implementation of AI/ML-based interventions in healthcare organizations. Multiple activities were preliminarily conducted, including i) mapping of the definitions on AI and ML in scholarly manuscripts, policy contributions and other reports by international institutions; ii) mapping of existing implementation frameworks from both Organization Studies and Implementation Science to comparatively assess them based on the distinctive dimensions, processes and mechanisms, and ultimately identify current gaps that a novel framework should address; iii) analysis of organizational and technological features that make the implementation of AI and ML unique and particularly challenging based on a literature analysis including dedicated editorials and commentaries. Consequently, a systematic review of the empirical literature on the implementation of AI and ML in healthcare organizations was conducted, with the aim of extracting main challenges and suggested solutions as documented in the scientific literature.  

In parallel, the task is focusing on the investigation of the state of the art with respect to the implementation of AI/ML-based interventions in the Lombardy region. The mapping of the AI and ML applications is ongoing and will be conducted through a survey targeting both public and private healthcare organizations within Lombardy. The survey is a joint effort from Bocconi University and Politecnico di Milano.  

Other ongoing research streams are focusing on the empirical investigation of the implementation of AI and ML applications, through selected case studies.  

The final steps of the task will focus on finetuning and finalizing the framework developed initially, as well as on drafting key recommendations to support the adoption of healthcare providers and the monitoring by regional policymakers. 

 

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Material produced and publications:  

Ardito V, Cappellaro G, Compagni A, Petracca F, Preti LM. Implementation of Machine Learning Applications in Health Care Organizations: Protocol for a Systematic Review of Empirical Studies. JMIR Res Protoc 2023;12:e47971 doi: 10.2196/47971  

 

Presentations:  

European Health Management Association (EHMA) Conference – June 5-7, 2023, Rome (presenter: Luigi Maria Preti) 

Il Dato in Sanità. Data Driven Healthcare: Sfide e Opportunità di una Sanità in Continua Evoluzione – June 9, 2023, Siena (presenter: Giulia Cappellaro) 

Associazione Italiana Economia Sanitaria (AIES) – December 5-6, 2023, Rome (forthcoming) (presenter: Francesco Petracca) 

XII Congresso Nazionale SIMIT (Società Italiana Malattie Infettive e Tropicali) - SIMPOSIO L’INTELLIGENZA ARTIFICIALE NELLA MEDICINA DEL III MILLENNIO Implementazione di AI in Sanità: sfide e opportunità organizzative, December 5, 2023 Florence (presenter: Giulia Cappellaro) 

Editorials: 

Cappellaro, G., 25 luglio 2023. “Organizzazioni Sanitarie: dal Gap alle Leve di Sviluppo su Intelligenza Artificiale” Editoriale Sole 24 Ore