A comprehensive maturity model for Health 5.0: integrating technology, digital governance, and information security in hospital environments

Rodrigo Nitai Bento Luna; Isabela Antunes de Souza Lima; Beatryz de Almeida Alcantara; Márcia Samed

doi:10.14488/1980-5411.20260051

Research Article

A comprehensive maturity model for Health 5.0: integrating technology, digital governance, and information security in hospital environments

Rodrigo Nitai Bento Luna; Isabela Antunes de Souza Lima; Beatryz de Almeida Alcantara; Márcia Samed

http://dx.doi.org/10.14488/1980-5411.20260051 Production, vol.36, e20260051, 2026

PDF

Downloads: 0

Abstract

Paper aims: This paper aims to develop a maturity model for assessing Health 5.0 maturity across five key hospital sectors: Triage, Outpatient Clinic, Diagnosis, Surgery, and Hospitalization, while also evaluating transversal governance and information security capabilities.

Originality: The study is original because it treats digital maturity as a systemic and conditional configuration rather than as a simple accumulation of technologies. Existing maturity models for hospital environments predominantly rely on additive aggregation logics, treating governance and security as parallel dimensions rather than enabling constraints. The proposed model addresses this gap by adopting a non-compensatory scoring logic that structurally limits technological maturity when governance and security capabilities are insufficient, a contribution that is both conceptually novel and practically relevant for high-risk settings.

Research method: The study follows a design-oriented research approach grounded in the Design Science Research (DSR) paradigm, focused on the conceptualization, structuring, and formalization of a maturity model. The model includes guiding axes, a structured assessment instrument with an evidence-based scoring rubric, and an explicit non-compensatory scoring mechanism. An illustrative hospital application demonstrates operational feasibility and analytical behavior.

Main findings: The results indicate that the model captures heterogeneous maturity profiles across hospital sectors and reveals structural vulnerabilities not identified through additive assessment approaches.

Implications for theory and practice: The study advances maturity model research by incorporating risk sensitivity into assessment and provides a diagnostic tool to support hospital managers in prioritizing interventions and aligning digital transformation with governance and security capabilities.

Keywords

Sociotechnical systems, Organizational resilience, Systemic risk, Organizational diagnostics, Non-compensatory logic

References

Argote, L., & Miron-Spektor, E. (2011). Organizational learning: from experience to knowledge. Organization Science, 22(5), 1123-1137. https://doi.org/10.1287/orsc.1100.0621.

Aven, T. (2016). Risk assessment and risk management: review of recent advances on their foundation. European Journal of Operational Research, 253(1), 1-13. https://doi.org/10.1016/j.ejor.2015.12.023.

Becker, J., Knackstedt, R., & Pöppelbuß, J. (2009). Developing maturity models for IT management. Business & Information Systems Engineering, 1(3), 213-222. https://doi.org/10.1007/s12599-009-0044-5.

Borges, G. A., Tortorella, G. L., Martínez, F., & Thurer, M. (2020). Simulation-based analysis of lean practices implementation on the supply chain of a public hospital. Production, 30, e20190131. https://doi.org/10.1590/0103-6513.20190131.

Chi, H. R., de Fátima Domingues, M., Zhu, H., Li, C., Kojima, K., & Radwan, A. (2023). Healthcare 5.0: in the perspective of consumer Internet-of-Things-based fog/cloud computing. IEEE Transactions on Consumer Electronics, 69(4), 745-755. https://doi.org/10.1109/TCE.2023.3293993.

Dresch, A., Lacerda, D. P., & Antunes, J. A. V. (2015). A method for science and technology advancement. In A. Dresch, D. P. Lacerda & J. A. V. Antunes (Eds.), Design science research: a method for science and technology advancement (pp. 67-102). Cham: Springer. https://doi.org/10.1007/978-3-319-07374-3_4.

Farhadighalati, N., Farhady Ghalaty, N., Nikghadam-Hojjati, S., Marchetti, E., & Barata, J. (2023). Safe-health: a secure framework for advancing edge-based health 5.0. In Proceedings of the 2023 IEEE 9th World Forum on Internet of Things (WF-IoT) (pp. 1-6). New York: IEEE. https://doi.org/10.1109/WF-IoT58464.2023.10539418.

Gayer, B., Marcon, E., Bueno, W. P., Wachs, P., Saurin, T. A., & Ghinato, P. (2020). Analysis of hospital flow management: the 3 R’s approach. Production, 30, e20200033. https://doi.org/10.1590/0103-6513.20200033.

Gomathi, L., Mishra, A. K., & Tyagi, A. K. (2023). Industry 5.0 for Healthcare 5.0: opportunities, challenges and future research possibilities. In 2023 7th International Conference on Trends in Electronics and Informatics (ICOEI) (pp. 204-213). New York: IEEE. https://doi.org/10.1109/ICOEI56765.2023.10125660.

Gregor, S., & Hevner, A. R. (2013). Positioning and presenting design science research for maximum impact. Management Information Systems Quarterly, 37(2), 337-355. https://doi.org/10.25300/MISQ/2013/37.2.01.

International Organization for Standardization – ISO. (2013) ISO 27001: information security management systems: requirements. Geneva: ISO; 2013.

Khan, T. A., Fatima, A., Shahzad, T., Atta-Ur-Rahman, Alissa, K., Ghazal, T. M., Al-Sakhnini, M. M., Abbas, S., Khan, M. A., & Ahmed, A. (2023). Secure IoMT for disease prediction empowered with transfer learning in healthcare 5.0, the concept and case study. IEEE Access : Practical Innovations, Open Solutions, 11, 39418-39430. https://doi.org/10.1109/ACCESS.2023.3266156.

Leveson, N. (2011). Engineering a safer world: systems thinking applied to safety. Cambridge: MIT Press.

Lima, I. A. S., Alcantara, B. A., Gomes, H. C., & Samed, M. M. A. (2026). Healthcare supply chain resilience during the COVID-19 pandemic: PPE procurement challenges and strategies. Gestão & Produção, 33, e1325. https://doi.org/10.1590/1806-9649-2025v33e1325.

Neira Sacaski, D. R., Graciano, P., Cerna Risco, K., Campos Llerena, J. P., Cafruni Gularte, A., & Lermen, F. H. (2025). The impact of digitalization on real estate agencies: the case of Peru. Production, 35, e20240146. https://doi.org/10.1590/0103-6513.20240146.

Pöppelbuß, J., & Röglinger, M. (2011). What makes a useful maturity model? A framework of general design principles for maturity models and its demonstration in business process management. In Proceedings of the European Conference on Information Systems (ECIS). Atlanta: Association for Information Systems.

Raja Santhi, A., & Muthuswamy, P. (2023). Industry 5.0 or industry 4.0S? Introduction to industry 4.0 and a peek into the prospective industry 5.0 technologies. International Journal on Interactive Design and Manufacturing, 17(2), 947-979. https://doi.org/10.1007/s12008-023-01217-8. PMid:40478102.

Rosas Quintero, W., & Namuche Maldonado, J. E. (2024). Competencies of the engineer in industry 4.0 context: a systematic literature review. Production, 34, e20230051. https://doi.org/10.1590/0103-6513.20230051.

Santos, K. C. P., Loures, E. F. R., Canciglieri Junior, O., & Micosky, A. L. (2022). Diagnostic assessment of product lifecycle management based on Industry 4.0 requirements. Production, 32, e20210082. https://doi.org/10.1590/0103-6513.20210082.

Schmeelk, S., Kanabar, M., Peterson, K., & Pathak, J. (2022). Electronic health records and blockchain interoperability requirements: a scoping review. JAMIA Open, 5(3), ooac068. https://doi.org/10.1093/jamiaopen/ooac068. PMid:35911668.

Sujith, A. V. L. N., Sajja, G. S., Mahalakshmi, V., Nuhmani, S., & Prasanalakshmi, B. (2022). Systematic review of smart health monitoring using deep learning and Artificial intelligence. Neuroscience Informatics (Online), 2(3), 100028. https://doi.org/10.1016/j.neuri.2021.100028.

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. Management Information Systems Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412.

Verma, S. K. Nadeem, M., Verma, V., Sayeed, M. A., Agrawal, A., & Khan, R. A. (2023). Blockchain application in healthcare domain: industry 5.0 perspective. In Proceedings of the 2023 6th International Conference on Contemporary Computing and Informatics (IC3I) (pp. 208-215). New York: IEEE. https://doi.org/10.1109/IC3I59117.2023.10397614.

Wazid, M., Singh, J., Das, A. K., & Rodrigues, J. J. P. C. (2024). An ensemble-based machine learning-envisioned intrusion detection in Industry 5.0-driven healthcare applications. IEEE Transactions on Consumer Electronics, 70(1), 1903-1912. https://doi.org/10.1109/TCE.2023.3318850.

Yadav, M., Vardhan, A., Chauhan, A. S., & Saini, S. (2023). A Study on Creation of Industry 5.0: New Innovations using big data through artificial intelligence, Internet of Things and next-origination technology policy. In Proceedings of the 2023 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS) (pp. 1-12). New York: IEEE. https://doi.org/10.1109/SCEECS57921.2023.10063069.

Yin, R. K. (2017). Case study research and applications: design and methods (6th ed.). Thousand Oaks: Sage Publication.

Zhang, H., Luo, J., Tu, Y., Wang, R., Wu, D., & Yang, J. (2023). Microservice deployment mechanism with diversified QoS requirements for smart health system in Industry 5.0. IEEE Transactions on Consumer Electronics, 69(4), 869-880. https://doi.org/10.1109/TCE.2023.3296534.

Submitted date:
04/14/2026

Accepted date:
08/24/2026

A comprehensive maturity model for Health 5.0: integrating technology, digital governance, and information security in hospital environments

Rodrigo Nitai Bento Luna; Isabela Antunes de Souza Lima; Beatryz de Almeida Alcantara; Márcia Samed

Abstract

Keywords

References

Links

Share

Production