Periodic Reporting for period 2 - ENVISION (Intelligent plug-and-play digital tool for real-time surveillance of COVID-19 patients and smart decision-making in Intensive Care Units)
Reporting period: 2021-10-01 to 2023-01-31
ENVISION aims at providing an artificial intelligence (AI) based tool for the intensive care unit (ICU) personnel to treat COVID-19 patients according to best practices and experiences learned from previous COVID-19 patient data from the ICU – the Sandman.IC. If successful, the developed methods for data collection and best treatment prediction will be incorporated into the medical devices used in ICUs. By collecting data from 13 ICUs located in hospitals across Europe a large set of COVID-19 patient data will be ensured. With the support of our health prediction tool and thanks to its alerting system, ICU staff will be able to respond to any patient health deterioration promptly. Further, the AI-based decision support tool will provide clear guidance to ICU personnel, allowing them to conduct the appropriate measures, possibly halting the patient’s deterioration and initiating their recovery. This will increase the survival rate in the ICUs and shorten the recovery time of the COVID-19 patients which are the overall objectives of the project.
During the reporting period indicated, the ENVISION project made significant progress in developing an AI-based tool for ICU staff to use in the treatment of COVID-19 patients. The project team focused on key activities including the development of the AI tool, data collection and analysis, and the creation of a rule-based decision support tool.
The AI tool was developed extensively, with the team specifying the requirements and designing the software architecture for seamless integration with existing ICU systems. Previous COVID-19 ICU patient data collected by Sandman.IC and other electronic clinical management systems were collected and analysed, providing valuable insights into patient profiles, disease progression and treatment outcomes. In addition, a rule-based decision support tool incorporating clinical guidelines and expert input was developed to help healthcare professionals make informed decisions for the treatment of COVID-19 patients.
The paper, titled "‘Do-not-intubate’ orders in patients assisted by non-invasive respiratory support for acute hypoxaemic failure caused by coronavirus disease 2019; a systematic review and meta-analysis” addresses the critical issue of decision-making regarding "Do-not-intubate" orders during the COVID-19 pandemic. The paper presents a comprehensive meta-analysis of existing data from the European Union, examining the decision-making process and the implications of these orders on patient care. The findings contribute to a deeper understanding of the challenges faced by healthcare professionals and help inform guidelines and practices for managing COVID-19 patients.
The paper currently in press, titled "Expectations of Anesthesiology and Intensive Care Professionals Toward Artificial Intelligence: Observational Study" focuses on the implementation of the expectations of EU healthcare professionals towards AI tools in anaesthesiology and intensive care and aims to evaluate their impact on patient outcomes and ICU practices. The paper highlights the project's commitment to advancing the field to the digital present.
Furthermore, the ENVISION project had the opportunity to represent its work at the Euroanasthesia 2023 congress, a prestigious event for target stakeholder groups. The project team showcased their achievements through a poster and a presentation, providing an overview of the AI-based tool development, data analysis, and publications. This participation allowed ENVISION to engage with key stakeholders and gather valuable feedback and insights.
These achievements highlight the progress made in building the necessary infrastructure and acquiring insights from previous patient data. The project has laid a strong foundation for the development of advanced AI capabilities to support ICU personnel in their treatment of COVID-19 patients.
The AI tool was developed extensively, with the team specifying the requirements and designing the software architecture for seamless integration with existing ICU systems. Previous COVID-19 ICU patient data collected by Sandman.IC and other electronic clinical management systems were collected and analysed, providing valuable insights into patient profiles, disease progression and treatment outcomes. In addition, a rule-based decision support tool incorporating clinical guidelines and expert input was developed to help healthcare professionals make informed decisions for the treatment of COVID-19 patients.
The paper, titled "‘Do-not-intubate’ orders in patients assisted by non-invasive respiratory support for acute hypoxaemic failure caused by coronavirus disease 2019; a systematic review and meta-analysis” addresses the critical issue of decision-making regarding "Do-not-intubate" orders during the COVID-19 pandemic. The paper presents a comprehensive meta-analysis of existing data from the European Union, examining the decision-making process and the implications of these orders on patient care. The findings contribute to a deeper understanding of the challenges faced by healthcare professionals and help inform guidelines and practices for managing COVID-19 patients.
The paper currently in press, titled "Expectations of Anesthesiology and Intensive Care Professionals Toward Artificial Intelligence: Observational Study" focuses on the implementation of the expectations of EU healthcare professionals towards AI tools in anaesthesiology and intensive care and aims to evaluate their impact on patient outcomes and ICU practices. The paper highlights the project's commitment to advancing the field to the digital present.
Furthermore, the ENVISION project had the opportunity to represent its work at the Euroanasthesia 2023 congress, a prestigious event for target stakeholder groups. The project team showcased their achievements through a poster and a presentation, providing an overview of the AI-based tool development, data analysis, and publications. This participation allowed ENVISION to engage with key stakeholders and gather valuable feedback and insights.
These achievements highlight the progress made in building the necessary infrastructure and acquiring insights from previous patient data. The project has laid a strong foundation for the development of advanced AI capabilities to support ICU personnel in their treatment of COVID-19 patients.
The impact of the project goes beyond the immediate results. The knowledge gained from the analysis of previous COVID-19 patient data and the development of the AI tool can be transferred and applied to future infectious disease outbreaks or other critical care scenarios. This not only benefits patients during the current pandemic but also promises to improve ICU practices in a broader context.
In addition, the ENVISION project recognises the importance of ethical considerations, data protection and patient confidentiality. Robust anonymisation techniques and data protection protocols are implemented to ensure the privacy and security of patient information. Ethical guidelines and legal frameworks are followed to ensure compliance with legal and ethical standards throughout the data collection and analysis process. The project team places great emphasis on protecting patient rights and maintaining the highest standards of data management.
In addition to the technical aspects, the ENVISION project aims to contribute to policymaking and the creation of guidelines for the implementation of AI in the ICU. By actively engaging relevant stakeholders, policymakers and clinical experts, the project seeks to shape the ethical and regulatory landscape around AI in critical care. This includes addressing issues of transparency, accountability, and responsible use of AI technologies.
The developed AI tool was designed with scalability and adaptability in mind, allowing for customisation to different ICUs and healthcare facilities. This flexibility ensures broad acceptance and relevance across different patient populations and evolving medical practices. With long-term benefits and sustainability, the tool has the potential to become an integral part of ICU workflows, helping healthcare professionals make informed decisions and improve patient outcomes.
The knowledge, methods and advances gained in the ENVISION project are of great value for future pandemics or outbreaks of infectious diseases. The knowledge gained through the analysis of the COVID-19 patient data and the development of the AI tool can serve as a valuable basis for understanding and managing similar health crises in the future. The knowledge gained, best practices identified, and ethical considerations can be used to improve ICU practices, decision support systems and patient care in future pandemics. By leveraging the expertise and advances made through the ENVISION project, health systems will be better equipped to respond effectively in the face of future health challenges, optimise resource allocation and improve patient outcomes.
In addition, the ENVISION project recognises the importance of ethical considerations, data protection and patient confidentiality. Robust anonymisation techniques and data protection protocols are implemented to ensure the privacy and security of patient information. Ethical guidelines and legal frameworks are followed to ensure compliance with legal and ethical standards throughout the data collection and analysis process. The project team places great emphasis on protecting patient rights and maintaining the highest standards of data management.
In addition to the technical aspects, the ENVISION project aims to contribute to policymaking and the creation of guidelines for the implementation of AI in the ICU. By actively engaging relevant stakeholders, policymakers and clinical experts, the project seeks to shape the ethical and regulatory landscape around AI in critical care. This includes addressing issues of transparency, accountability, and responsible use of AI technologies.
The developed AI tool was designed with scalability and adaptability in mind, allowing for customisation to different ICUs and healthcare facilities. This flexibility ensures broad acceptance and relevance across different patient populations and evolving medical practices. With long-term benefits and sustainability, the tool has the potential to become an integral part of ICU workflows, helping healthcare professionals make informed decisions and improve patient outcomes.
The knowledge, methods and advances gained in the ENVISION project are of great value for future pandemics or outbreaks of infectious diseases. The knowledge gained through the analysis of the COVID-19 patient data and the development of the AI tool can serve as a valuable basis for understanding and managing similar health crises in the future. The knowledge gained, best practices identified, and ethical considerations can be used to improve ICU practices, decision support systems and patient care in future pandemics. By leveraging the expertise and advances made through the ENVISION project, health systems will be better equipped to respond effectively in the face of future health challenges, optimise resource allocation and improve patient outcomes.