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Commentary: Intelligent Forest Hospital as a New Management System for Hospital-Acquired Infection Control

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  • Abstract

    Hospital-acquired infection (HAI) is a significant global health concern, elevating the risks of morbidity and imposing a substantial socioeconomic burden. To enhance the management of HAI, particularly in the aftermath of the coronavirus disease 2019 (COVID-19) pandemic, the Guangdong Second Provincial General Hospital (GD2H) has launched a new system called Intelligent Forest Hospital (IFH). Leveraging advancements in artificial intelligence, 5G technology, and cloud networking, the IFH implements customized indoor air quality (IAQ) control strategies tailored to different medical settings. It utilizes various intelligent disinfection devices and air purification systems. The IFH features a dynamic 3D hospital model with real-time monitoring of crucial IAQ parameters and a risk assessment ranking for clinical departments, providing timely risk alerts, communication prompts, and automatic disinfection processes. The IFH aims to effectively mitigate HAI post-COVID-19 and other future pandemics, ensuring a safe and pleasant environment for patients, hospital staff, and visitors.

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  • Conflicts of interest: No conflicts of interest.
  • Funding: Supported by the Science Foundation of Guangdong Second Provincial General Hospital (number: YY2018-002, recipient: GL)
  • [1] Cassini A, Plachouras D, Eckmanns T, Abu Sin M, Blank HP, Ducomble T, et al. Burden of six healthcare-associated infections on European population health: estimating incidence-based disability-adjusted life years through a population prevalence-based modelling study. PLoS Med 2016;13(10):e1002150. https://doi.org/10.1371/journal.pmed.1002150CrossRef
    [2] Klompas M, Karan A. Preventing SARS-CoV-2 transmission in health care settings in the context of the omicron variant. JAMA 2022;327(7):619 − 20. https://doi.org/10.1001/jama.2022.0262CrossRef
    [3] Tang JW, Bahnfleth WP, Bluyssen PM, Buonanno G, Jimenez JL, Kurnitski J, et al. Dismantling myths on the airborne transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). J Hosp Infect 2021;110:89 − 96. https://doi.org/10.1016/j.jhin.2020.12.022CrossRef
    [4] Suleyman G, Alangaden G, Bardossy AC. The role of environmental contamination in the transmission of nosocomial pathogens and healthcare-associated infections. Curr Infect Dis Rep 2018;20(6):12. https://doi.org/10.1007/s11908-018-0620-2CrossRef
    [5] Otter JA, Yezli S, French GL. The role played by contaminated surfaces in the transmission of nosocomial pathogens. Infect Control Hosp Epidemiol 2011;32(7):687 − 99. https://doi.org/10.1086/660363CrossRef
    [6] Manian FA, Griesenauer S, Senkel D, Setzer JM, Doll SA, Perry AM, et al. Isolation of Acinetobacter baumannii complex and methicillin-resistant Staphylococcus aureus from hospital rooms following terminal cleaning and disinfection: can we do better? Infect Control Hosp Epidemiol 2011;32(7):667-72. http://dx.doi.org/10.1086/660357.
    [7] Saran S, Gurjar M, Baronia A, Sivapurapu V, Ghosh PS, Raju GM, et al. Heating, ventilation and air conditioning (HVAC) in intensive care unit. Crit Care 2020;24(1):194. https://doi.org/10.1186/s13054-020-02907-5CrossRef
    [8] Chen XJ, Tian JZ, Li GM, Li GW. Initiation of a new infection control system for the COVID-19 outbreak. Lancet Infect Dis 2020;20(4):397 − 8. https://doi.org/10.1016/s1473-3099(20)30110-9CrossRef
    [9] Li GW, Lian WM, Qu HY, Li ZY, Zhou QR, Tian JZ. Improving patient care through the development of a 5G-powered smart hospital. Nat Med 2021;27(6):936 − 7. https://doi.org/10.1038/s41591-021-01376-9CrossRef
    [10] Cheng WB, Lian WM, Tian JZ. Building the hospital intelligent twins for all-scenario intelligence health care. Digit Health 2022;8:1−4. https://doi.org/10.1177/20552076221107894
    [11] Chu CH, Chen SR, Wu CH, Cheng YC, Cho YM, Chang YK. The effects of negative air ions on cognitive function: an event-related potential (ERP) study. Int J Biometeorol 2019;63(10):1309 − 17. https://doi.org/10.1007/s00484-019-01745-7CrossRef
    [12] Liu S, Li C, Chu MT, Zhang WL, Wang WZ, Wang YZ, et al. Associations of forest negative air ions exposure with cardiac autonomic nervous function and the related metabolic linkages: a repeated-measure panel study. Sci Total Environ 2022;850:158019. https://doi.org/10.1016/j.scitotenv.2022.158019CrossRef
    [13] Jiang SY, Ma AL, Ramachandran S. Negative air ions and their effects on human health and air quality improvement. Int J Mol Sci 2018;19(10):2966. https://doi.org/10.3390/ijms19102966CrossRef
  • FIGURE 1.  Ceiling oxygen equipment in the outpatient hall.

    FIGURE 2.  The dynamic 3D hospital model diagram displaying real-time monitoring of key indoor air quality parameters on the main screen of the smart brain.

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Intelligent Forest Hospital as a New Management System for Hospital-Acquired Infection Control

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Abstract

Hospital-acquired infection (HAI) is a significant global health concern, elevating the risks of morbidity and imposing a substantial socioeconomic burden. To enhance the management of HAI, particularly in the aftermath of the coronavirus disease 2019 (COVID-19) pandemic, the Guangdong Second Provincial General Hospital (GD2H) has launched a new system called Intelligent Forest Hospital (IFH). Leveraging advancements in artificial intelligence, 5G technology, and cloud networking, the IFH implements customized indoor air quality (IAQ) control strategies tailored to different medical settings. It utilizes various intelligent disinfection devices and air purification systems. The IFH features a dynamic 3D hospital model with real-time monitoring of crucial IAQ parameters and a risk assessment ranking for clinical departments, providing timely risk alerts, communication prompts, and automatic disinfection processes. The IFH aims to effectively mitigate HAI post-COVID-19 and other future pandemics, ensuring a safe and pleasant environment for patients, hospital staff, and visitors.

  • 1. Center for Clinical Epidemiology and Methodology (CCEM), The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou City, Guangdong Province, China
  • 2. Medical Department, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou City, Guangdong Province, China
  • 3. Hospital-Acquired Infection Control Department, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou City, Guangdong Province, China
  • 4. Information Department, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou City, Guangdong Province, China
  • 5. Institute for Healthcare Artificial Intelligence Application, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou City, Guangdong Province, China
  • 6. Father Sean O’Sullivan Research Centre, St. Joseph’s Healthcare Hamilton, Hamilton, ON, Canada
  • 7. Department of Health Research Methods, Evidence, and Impact (HEI), McMaster University, Hamilton, ON, Canada
  • Corresponding authors:

    Guowei Li, ligw@gd2h.org.cn

    Hongying Qu, tggd2h@163.com

  • Funding: Supported by the Science Foundation of Guangdong Second Provincial General Hospital (number: YY2018-002, recipient: GL)
  • Online Date: September 13 2024
    Issue Date: September 13 2024
    doi: 10.46234/ccdcw2024.201
  • Hospital-acquired infection (HAI), or healthcare-associated infection, is a significant global health concern linked to increased morbidity and socioeconomic burden (1). The coronavirus disease 2019 (COVID-19) pandemic has highlighted the importance of addressing HAI, with reported rates ranging from 8.3% to 23.4% (2). HAI, including COVID-19, primarily spread through airborne and contaminated surface routes (3). Pathogens can persist in hospital environments for extended periods, with some resistant microorganisms surviving for years (4). Traditional cleaning methods often struggle to eliminate these pathogens effectively (5). Research has shown that even after four rounds of bleach disinfection, around 26.6% of hospital rooms remained contaminated (6). Therefore, adopting new technologies to maintain a safe hospital environment and improve indoor air quality (IAQ) is crucial for HAI prevention and control (7).

    In an effort to enhance the control of HAI, particularly in the post-COVID era, Guangdong Second Provincial General Hospital (GD2H) has introduced a novel management system called the Intelligent Forest Hospital (IFH). Drawing on advancements in artificial intelligence (AI), 5G technology, and cloud networking that have been effectively integrated into hospital operations at GD2H (810), the IFH has been tailored to manage IAQ in various medical settings. This system involves the deployment of specialized disinfection equipment and air purification terminals in areas such as delivery rooms, operating rooms, intensive care units, respiratory and infection wards, and emergency departments — locations where the risk of HAI for both healthcare staff and patients is notably high.

    While cleaning is crucial for preventing HAI, it is essential to consider hospital design, disinfection practices, and surface composition. GD2H utilizes various intelligent equipment categorized into disinfection [e.g., negative air ion (NAI) generator, plasma air sterilizer, ultraviolet sterilizer], surface composition (e.g., antibacterial coating, antibacterial fabric), and detection (e.g., microbial detection system). This combination effectively inhibits pathogens and controls IAQ parameters such as CO2 levels, formaldehyde, PM2.5, and particle mass concentration. In the outpatient hall of GD2H, where over 5,000 patients are served daily, around 60 air purification devices have been installed, including ceiling oxygen equipment, disinfection lamps, and plasma disinfection machines (Figure 1). The NAI concentration in the hospital reaches forest environment standards (>3,000/cm3), with some areas exceeding 100,000/cm3. Forest environments have high NAI concentrations known to benefit human health, including mental health, cognitive and cardiorespiratory function (1113), which inspired the IFH concept to create a safe and comfortable environment similar to a forest sanatorium.

    Figure 1. 

    Ceiling oxygen equipment in the outpatient hall.

    In 2020, GD2H collaborated with Huawei to develop the Hospital Intelligent Data Twins, which are essentially digital twins within the framework of Industry 4.0. These twins function as an integrated system to facilitate the seamless exchange of digitalized and visualized data. At the core of the Intelligent Data Twins lies cloud services that leverage AI techniques to enhance data utilization (10). All data gathered by the intelligent equipment at GD2H are concurrently transmitted to a virtual cloud platform within the hospital premises for IAQ monitoring and management. The central management hub, serving as the hospital’s smart brain, continuously monitors IAQ across all areas of GD2H round the clock. By harnessing AI, 5G technology, cloud services, and a virtual platform, the Intelligent Data Twins effectively process and receive vast amounts of data from all intelligent equipment, transmitting this information to the cognitive center for real-time IAQ visualization at GD2H (10). The primary interface of the cognitive center exhibits a dynamic 3D model diagram of the hospital, providing real-time monitoring of critical IAQ parameters such as pathogenic microorganisms, carbon dioxide, formaldehyde, PM2.5, and negative ions (Figure 2). Moreover, the cognitive center conducts a comprehensive analysis of the continuously updated real-time data, evaluating HAI risks from various sources. It generates a risk ranking index for clinical departments on screen, enabling prompt risk alerts and initiating automated disinfection measures when necessary. For example, upon detecting abnormal IAQ parameters in infection wards, the cognitive center promptly assesses the situation and triggers the automatic disinfection equipment in the affected area. Simultaneously, it communicates the IAQ status to the nurse stations in the infected wards to inform healthcare providers and patients about potential contamination and the ongoing automated disinfection process.

    Figure 2. 

    The dynamic 3D hospital model diagram displaying real-time monitoring of key indoor air quality parameters on the main screen of the smart brain.

    There are various challenges that need attention in the integration of IFH using technologies like AI and 5G. These challenges include the high costs and energy consumption, the absence of medical standards and regulations, ethical concerns regarding patient privacy, societal acceptance, real-time monitoring difficulties, and the general applicability of 5G and virtual cloud platforms. The IFH requires enhancements such as regular system updates for real-time data processing, improved data privacy and security measures, and further assessments of costs and benefits. Specific training and adjustments are necessary to ensure the system’s effectiveness in various contexts and to improve its generalizability. Despite these challenges, integrating IFH with AI and 5G technologies shows promise in enhancing the prevention and management of HAI, particularly in the context of post COVID-19 and future pandemics, aiming to create a safe and pleasant environment for patients, hospital staff, and visitors.

  • Conflicts of interest: No conflicts of interest.
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