Impacts of Healthcare 4.0 digital technologies on the resilience of hospitals

Abstract Healthcare 4.0 (H4.0) adapts principles and applications from the Industry 4.0 movement to healthcare, enabling real-time customization of care to patients and professionals. As such, H4.0 can potentially support resilient performance in healthcare systems, which refers to their adaptive capacity to cope with complexity. This paper explores the impact of ten H4.0 digital technologies on four abilities of resilient systems (monitor, anticipate, respond, and learn) in the context of hospitals. For that, we conducted a survey with 109 resilient healthcare and H4.0 experts from both emerging and developed economies. The collected data were analyzed using univariate and multivariate statistical techniques. Our findings indicate four H4.0 digital technologies that have a strong impact on the four resilience abilities: remote consultations and development of plan of care in real time; digital non-invasive care; interconnected medical emergency support; and digital platforms for collaborative sharing of patient data and information. These technologies can reduce over-reliance on human adaptive skills while at the same time offering new and expanded opportunities for resilient performance in healthcare.

[1]  M. Penadés,et al.  From planning to resilience: The role (and value) of the emergency plan , 2017 .

[2]  J. Braithwaite,et al.  Patterns of resilience: A scoping review and bibliometric analysis of resilient health care , 2019, Safety Science.

[3]  Giancarlo Fortino,et al.  An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0 , 2019, IEEE Transactions on Industrial Informatics.

[4]  Yichuan Wang,et al.  An integrated big data analytics-enabled transformation model: Application to health care , 2018, Inf. Manag..

[5]  Tarcisio Abreu Saurin,et al.  A framework for the analysis of slack in socio-technical systems , 2017, Reliab. Eng. Syst. Saf..

[6]  Sherif Sakr,et al.  Towards a Comprehensive Data Analytics Framework for Smart Healthcare Services , 2016, Big Data Res..

[7]  Rongxing Lu,et al.  Achieve Privacy-Preserving Priority Classification on Patient Health Data in Remote eHealthcare System , 2019, IEEE Access.

[8]  Noor Zaman,et al.  A Lightweight and Secure Authentication Scheme for IoT Based E-Health Applications , 2019 .

[9]  Arun Kumar Sangaiah,et al.  A novel mutual authentication scheme with formal proof for smart healthcare systems under global mobility networks notion , 2018, Comput. Electr. Eng..

[10]  G. Tortorella,et al.  Measuring the effect of Healthcare 4.0 implementation on hospitals’ performance , 2020, Production Planning & Control.

[11]  Mohamed Elhoseny,et al.  A hybrid model of Internet of Things and cloud computing to manage big data in health services applications , 2018, Future Gener. Comput. Syst..

[12]  A. C. Rencher Methods of multivariate analysis , 1995 .

[13]  Sheuwen Chuang,et al.  Measurement of resilience potentials in emergency departments: Applications of a tailored resilience assessment grid , 2020 .

[14]  Gunasekaran Manogaran,et al.  A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system , 2017, Future Gener. Comput. Syst..

[15]  Abdelmajid Oumnad,et al.  Challenges and Opportunities of Internet of Things in Healthcare , 2018, International Journal of Electrical and Computer Engineering (IJECE).

[16]  G. Tortorella,et al.  Effects of contingencies on healthcare 4.0 technologies adoption and barriers in emerging economies , 2020 .

[17]  Jan R. Jonassen,et al.  License to intervene: the role of team adaptation in balancing structure and flexibility in offshore operations , 2019, WMU Journal of Maritime Affairs.

[18]  Dhiya Al-Jumeily,et al.  Healthcare Services Innovations Based on the State of the Art Technology Trend Industry 4.0 , 2018, 2018 11th International Conference on Developments in eSystems Engineering (DeSE).

[19]  Mustafa Abdullah Azzawi,et al.  A Review on Internet of Things ( IoT ) in Healthcare , 2016 .

[20]  Christopher P. Nemeth,et al.  Building change: Resilience Engineering after ten years , 2015, Reliab. Eng. Syst. Saf..

[21]  Md. Zia Uddin A wearable sensor-based activity prediction system to facilitate edge computing in smart healthcare system , 2019, J. Parallel Distributed Comput..

[22]  Sally M. El-Ghamrawy,et al.  A Hybrid Real-time remote monitoring framework with NB-WOA algorithm for patients with chronic diseases , 2019, Future Gener. Comput. Syst..

[23]  T. Baines,et al.  Capturing the benefits of industry 4.0: a business network perspective , 2019, Production Planning & Control.

[24]  Kash Barker,et al.  A review of definitions and measures of system resilience , 2016, Reliab. Eng. Syst. Saf..

[25]  Anna Jobin,et al.  The global landscape of AI ethics guidelines , 2019, Nature Machine Intelligence.

[26]  R. DarshanK,et al.  A comprehensive review on usage of Internet of Things (IoT) in healthcare system , 2015 .

[27]  Edward P. Markowski,et al.  Conditions for the Effectiveness of a Preliminary Test of Variance , 1990 .

[28]  Shuai Ding,et al.  Exploring behavioural intentions toward smart healthcare services among medical practitioners: a technology transfer perspective , 2018, Int. J. Prod. Res..

[29]  Ik-Whan G. Kwon,et al.  Healthcare supply chain management; strategic areas for quality and financial improvement , 2016 .

[30]  Jin Wang,et al.  Wearable IoT enabled real-time health monitoring system , 2018, EURASIP Journal on Wireless Communications and Networking.

[31]  Dayana Bastos Costa,et al.  Applicability of unmanned aerial system (UAS) for safety inspection on construction sites , 2017 .

[32]  Mamas A Mamas,et al.  Applications of digital technology in COVID-19 pandemic planning and response , 2020, The Lancet Digital Health.

[33]  R. Sawhney,et al.  Organizational learning paths based upon industry 4.0 adoption: An empirical study with Brazilian manufacturers , 2020, International Journal of Production Economics.

[34]  Sidney Dekker,et al.  Drift into Failure: From Hunting Broken Components to Understanding Complex Systems , 2011 .

[35]  G. Tortorella,et al.  Identifying pathways to a high-performing lean automation implementation: An empirical study in the manufacturing industry , 2021 .

[36]  Jing Chen,et al.  Hospital Emergency Management Plan During the COVID‐19 Epidemic , 2020, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[37]  P. Buckle,et al.  Designing medical technology for resilience: integrating health economics and human factors approaches , 2018, Expert review of medical devices.

[38]  R. Viney,et al.  Breaking up is hard to do: why disinvestment in medical technology is harder than investment. , 2012, Australian health review : a publication of the Australian Hospital Association.

[39]  Peng-Ting Chen,et al.  Medical big data applications: Intertwined effects and effective resource allocation strategies identified through IRA-NRM analysis , 2018 .

[40]  T. Lumley,et al.  The importance of the normality assumption in large public health data sets. , 2002, Annual review of public health.

[41]  Erik Hollnagel,et al.  Resilience engineering and the built environment , 2014 .

[42]  Siobhan Corrigan,et al.  Human factors & safety culture: Challenges & opportunities for the port environment , 2019 .

[43]  Asoke K. Nandi,et al.  Integrative Cluster Analysis in Bioinformatics , 2015 .

[44]  Jun Cai,et al.  A Truthful Mechanism for Scheduling Delay-Constrained Wireless Transmissions in IoT-Based Healthcare Networks , 2019, IEEE Transactions on Wireless Communications.

[45]  Kyung Sup Kwak,et al.  An Internet of Things-based health prescription assistant and its security system design , 2017, Future Gener. Comput. Syst..

[46]  Antonio De Nicola,et al.  Serious games for industrial safety: An approach for developing resilience early warning indicators , 2019, Safety Science.

[47]  Won Kim,et al.  Challenges for wearable healthcare services , 2016, Int. J. Web Grid Serv..

[48]  S. Wiig,et al.  Resilience From a Stakeholder Perspective: The Role of Next of Kin in Cancer Care , 2018, Journal of patient safety.

[49]  D. Nagel,et al.  Cluster analysis in diagnosis. , 1992, Clinical chemistry.

[50]  G. V. R. K. Acharyulu,et al.  Information Management in a Health Care System: Knowledge Management Perspective , 2011 .

[51]  Oakyoung Han,et al.  A Design Characteristics of Smart Healthcare System as the IoT Application , 2016 .

[52]  Giuseppe De Pietro,et al.  A Continuous Noninvasive Arterial Pressure (CNAP) Approach for Health 4.0 Systems , 2019, IEEE Transactions on Industrial Informatics.

[53]  Haluk Demirkan,et al.  A Smart Healthcare Systems Framework , 2013, IT Professional.

[54]  J. E. Anderson,et al.  Defining adaptive capacity in healthcare: A new framework for researching resilient performance. , 2020, Applied ergonomics.

[55]  Erik Hofmann,et al.  Industry 4.0 and the current status as well as future prospects on logistics , 2017, Comput. Ind..

[56]  S. Southwick,et al.  Resilience definitions, theory, and challenges: interdisciplinary perspectives , 2014, European journal of psychotraumatology.

[57]  Thar Baker,et al.  An Edge Computing Based Smart Healthcare Framework for Resource Management , 2018, Sensors.

[58]  I. Helsloot,et al.  Organisational resilience: Shifting from planning-driven business continuity management to anticipated improvisation. , 2020, Journal of business continuity & emergency planning.

[59]  Danilo De Donno,et al.  An IoT-Aware Architecture for Smart Healthcare Systems , 2015, IEEE Internet of Things Journal.

[60]  W. Cooley,et al.  Multivariate Data Analysis. , 1973 .

[61]  J Pandia Rajan,et al.  An Internet of Things based physiological signal monitoring and receiving system for virtual enhanced health care network. , 2018, Technology and health care : official journal of the European Society for Engineering and Medicine.

[62]  Dominique Luzeaux Engineering Large‐Scale Complex Systems , 2013 .

[63]  M. Kho,et al.  Physiotherapy management for COVID-19 in the acute hospital setting: clinical practice recommendations , 2020, Journal of Physiotherapy.

[64]  V. Grover,et al.  An assessment of survey research in POM: from constructs to theory , 1998 .

[65]  Terry S. Overton,et al.  Estimating Nonresponse Bias in Mail Surveys , 1977 .

[66]  Riccardo Patriarca,et al.  A taxonomy of interactions in socio-technical systems: A functional perspective. , 2020, Applied ergonomics.

[67]  B. Shipman,et al.  Augmented Reality in Emergency Medicine: A Scoping Review , 2019, Journal of medical Internet research.

[68]  Peter J. Rousseeuw,et al.  Finding Groups in Data: An Introduction to Cluster Analysis , 1990 .

[69]  Antonio Pescapè,et al.  The role of Information and Communication Technologies in healthcare: taxonomies, perspectives, and challenges , 2018, J. Netw. Comput. Appl..

[70]  C. Bai,et al.  Health 4.0: Application of Industry 4.0 Design Principles in Future Asthma Management , 2017 .

[71]  Sulfikar Amir,et al.  Modelling Multilevel Interdependencies for Resilience in Complex Organisation , 2019, Complex..

[72]  Paul R. Schulman,et al.  The Negotiated Order of Organizational Reliability , 1993 .

[73]  G. B. Benitez,et al.  The expected contribution of Industry 4.0 technologies for industrial performance , 2018, International Journal of Production Economics.

[74]  Tarcisio Abreu Saurin,et al.  A systematic literature review of resilience engineering: Research areas and a research agenda proposal , 2015, Reliab. Eng. Syst. Saf..

[75]  Hodjat Hamidi,et al.  An approach to develop the smart health using Internet of Things and authentication based on biometric technology , 2019, Future Gener. Comput. Syst..

[76]  Fernando Deschamps,et al.  Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal , 2017, Int. J. Prod. Res..

[77]  more modern multivariate statistical techniques,et al.  Applied Multivariate Research , 2013 .

[78]  Erik Hollnagel,et al.  Safety-II in Practice: Developing the Resilience Potentials , 2017 .

[79]  Wei Li,et al.  Edge cognitive computing based smart healthcare system , 2018, Future Gener. Comput. Syst..

[80]  K. Voigt,et al.  Sustainable Industrial Value Creation: Benefits and Challenges of Industry 4.0 , 2017, Digital Disruptive Innovation.

[81]  J. Garza‐Reyes,et al.  Organizational learning and Industry 4.0: findings from a systematic literature review and research agenda , 2020 .

[82]  P. Fettke,et al.  Industry 4.0 , 2014, Bus. Inf. Syst. Eng..

[83]  Wei Xiang,et al.  An IoT-cloud Based Wearable ECG Monitoring System for Smart Healthcare , 2016, Journal of Medical Systems.

[84]  Marcello Ienca,et al.  Artificial Intelligence: the global landscape of ethics guidelines , 2019, ArXiv.

[85]  M. Pikkarainen,et al.  The change of pediatric surgery practice due to the emergence of connected health technologies , 2019, Technological Forecasting and Social Change.

[86]  Anand Nair,et al.  Technology alignment in the presence of regulatory changes: The case of meaningful use of information technology in healthcare , 2018, Int. J. Medical Informatics.

[87]  Yang Lu,et al.  Industry 4.0: A survey on technologies, applications and open research issues , 2017, J. Ind. Inf. Integr..

[88]  Tarcisio Abreu Saurin,et al.  A complexity theory perspective of kaizen: a study in healthcare , 2019, Production Planning & Control.

[89]  Li Da Xu,et al.  Industry 4.0: state of the art and future trends , 2018, Int. J. Prod. Res..

[90]  Muhammad Ali Imran,et al.  A Review on the Role of Nano-Communication in Future Healthcare Systems: A Big Data Analytics Perspective , 2018, IEEE Access.

[91]  The Evolution of Health Information Technology Policy in the United States , 2016 .

[92]  R. Sawhney,et al.  Healthcare 4.0: trends, challenges and research directions , 2019, Production Planning & Control.

[93]  C. Clar,et al.  Investment for health and well-being: a review of the social return on investment from public health policies to support implementing the Sustainable Development Goals by building on Health 2020 , 2017 .

[94]  Andrew Smaggus Safety-I, Safety-II and burnout: how complexity science can help clinician wellness , 2019, BMJ Quality & Safety.

[95]  Johan Bergström,et al.  On the rationale of resilience in the domain of safety: A literature review , 2015, Reliab. Eng. Syst. Saf..

[96]  Jeffrey Braithwaite,et al.  Resilient health care: turning patient safety on its head. , 2015, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[97]  Terry Anthony Byrd,et al.  Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations , 2018 .

[98]  Gunasekaran Manogaran,et al.  Big Data Knowledge System in Healthcare , 2017 .

[99]  A. Ancarani,et al.  Technology acquisition and efficiency in Dubai hospitals , 2016 .