Designing Training Models for Health Workers on Data Security and Information Confidentiality in the Digital Era

Authors

  • Damilola Oluyemi Merotiwon  Independent Researcher, Texas. USA
  • Opeyemi Olamide Akintimehin  Department of Human Nutrition and Dietetics, University of Ibadan, Nigeria
  • Opeoluwa Oluwanifemi Akomolafe  Micmakin Nigeria Limited, Akure, Ondo, Nigeria

Keywords:

digital health, data security, information confidentiality, health worker training, cybersecurity education, healthcare compliance

Abstract

ABSTRACT The proliferation of digital technologies in healthcare has revolutionized data access, storage, and sharing. However, these advancements introduce significant risks to the confidentiality, integrity, and security of patient information. Health workers play a pivotal role in safeguarding data, yet studies indicate insufficient training in data protection and information confidentiality practices. This literature-based paper explores the design of effective training models for health workers, emphasizing competencies required in the digital era. Drawing from over 100 scholarly sources, including health informatics standards, cybersecurity guidelines, and adult learning theories, the study synthesizes best practices to recommend a comprehensive, tiered training model. The paper is structured into an extensive introduction and literature review, followed by conceptual framework development, discussion, and recommendations. This review offers insights to policy-makers, health educators, and digital health implementers aiming to fortify human-centric defenses in healthcare information ecosystems.

References

  1. M. Muthuppalaniappan and K. Stevenson, “Healthcare cyber-attacks and the COVID-19 pandemic: An urgent threat to global health,” International Journal for Quality in Health Care, vol. 33, no. 1, 2021, doi: 10.1093/INTQHC/MZAA117.
  2. R. Wash and M. M. Cooper, “Who provides phishing training? Facts, stories, and people like me,” Conference on Human Factors in Computing Systems - Proceedings, vol. 2018-April, Apr. 2018, doi: 10.1145/3173574.3174066.
  3. T. Martin, “Assessing mHealth: Opportunities and barriers to patient engagement,” J Health Care Poor Underserved, vol. 23, no. 3, pp. 935–941, Aug. 2012, doi: 10.1353/HPU.2012.0087.
  4. F. Khatun, A. E. Heywood, P. K. Ray, S. M. A. Hanifi, A. Bhuiya, and S. T. Liaw, “Determinants of readiness to adopt mHealth in a rural community of Bangladesh,” Int J Med Inform, vol. 84, no. 10, pp. 847–856, Oct. 2015, doi: 10.1016/j.ijmedinf.2015.06.008.
  5. A. A. Abayomi, C. A. Mgbame, O. E. Akpe, E. Ogbuefi, and O. O. Adeyelu, “Advancing Equity Through Technology: Inclusive Design of Healthcare Analytics Platforms for Healthcare,” Healthcare Analytics, vol. 45, no. 45 SP 45–45, 2021, Online]. Available: https://www.irejournals.com/paper-details/1708220
  6. C. A. Mgbame, O. E. Akpe, A. A. Abayomi, E. Ogbuefi, and O. O. Adeyelu, “Barriers and Enablers of Healthcare Analytics Tool Implementation in Underserved Healthcare Communities,” Healthcare Analytics, vol. 45, no. 45 SP 45–45, 2020, Online]. Available: https://www.irejournals.com/paper-details/1708221
  7. E. C. Chianumba, N. Ikhalea, A. Y. Mustapha, A. Y. Forkuo, and D. Osamika, “A conceptual framework for leveraging big data and AI in enhancing healthcare delivery and public health policy,” IRE Journals, vol. 5, no. 6, pp. 303–310, 2021.
  8. J. C. Ogeawuchi, A. C. Uzoka, A. A. Abayomi, O. A. Agboola, and P. Gbenle, “Innovations in Data Modeling and Transformation for Scalable Healthcare Intelligence on Modern Cloud Platforms,” Healthcare Analytics, vol. 45, no. 45 SP 45–45, 2021, Online]. Available: https://www.irejournals.com/paper-details/1708319
  9. A. A. Abayomi, B. C. Ubanadu, A. I. Daraojimba, O. A. Agboola, and S. Owoade, “A Conceptual Framework for Real-Time Data Analytics and Decision-Making in Cloud-Optimized Healthcare Intelligence Systems,” Healthcare Analytics, vol. 45, no. 45 SP 45–45, 2022, Online]. Available: https://www.irejournals.com/paper-details/1708317
  10. E. C. Chianumba, N. Ikhalea, A. Y. Mustapha, A. Y. Forkuo, and D. Osamika, “Developing a predictive model for healthcare compliance, risk management, and fraud detection using data analytics,” International Journal of Social Science Exceptional Research, vol. 1, no. 1, pp. 232–238, 2022.
  11. R. Heartfield, G. Loukas, and D. Gan, “You Are Probably Not the Weakest Link: Towards Practical Prediction of Susceptibility to Semantic Social Engineering Attacks,” IEEE Access, vol. 4, pp. 6910–6928, 2016, doi: 10.1109/ACCESS.2016.2616285.
  12. K. McCracken and D. R. Phillips, “Global health: An introduction to current and future trends: Second edition,” Global Health: An Introduction to Current and Future Trends: Second Edition, pp. 1–437, Jun. 2017, doi: 10.4324/9781315691800/GLOBAL-HEALTH-KEVIN-MCCRACKEN-DAVID-PHILLIPS.
  13. E. C. Chianumba, N. Ikhalea, A. Y. Mustapha, and A. Y. Forkuo, “A Conceptual Model for Addressing Healthcare Inequality Using AI-Based Decision Support Systems,” 2022.
  14. A. Fayoumi and R. Williams, “An integrated socio-technical enterprise modelling: A scenario of healthcare system analysis and design,” J Ind Inf Integr, vol. 23, p. 100221, Sep. 2021, doi: 10.1016/J.JII.2021.100221.
  15. A. Y. Mustapha, E. C. Chianumba, A. Y. Forkuo, D. Osamika, and L. S. Komi, “Systematic Review of Digital Maternal Health Education Interventions in Low-Infrastructure Environments,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 2, 2021.
  16. L. S. Komi, E. C. Chianumba, A. Yeboah, D. O. Forkuo, and A. Y. Mustapha, “Advances in Public Health Outreach Through Mobile Clinics and Faith-Based Community Engagement in Africa,” 2021.
  17. E. O. Alonge, N. L. Eyo-Udo, B. C. Ubanadu, A. I. Daraojimba, E. D. Balogun, and K. O. Ogunsola, “Real-time data analytics for enhancing supply chain efficiency,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 2, no. 1, pp. 759–771, 2021, doi: 10.54660/.IJMRGE.2021.2.1.759-771.
  18. “Journal of Medical Internet Research - Cyber Hygiene Methodology for Raising Cybersecurity and Data Privacy Awareness in Health Care Organizations: Concept Study.” Accessed: Jun. 07, 2025. Online]. Available: https://www.jmir.org/2023/1/e41294/
  19. A. Vishwanath et al., “Cyber hygiene: The concept, its measure, and its initial tests,” Decis Support Syst, vol. 128, Jan. 2020, doi: 10.1016/J.DSS.2019.113160.
  20. L. S. Komi, E. C. Chianumba, A. Y. Forkuo, D. Osamika, and A. Y. Mustapha, “A conceptual framework for training community health workers through virtual public health education modules,” IRE Journals, vol. 5, no. 11, pp. 332–335, 2022.
  21. J. C. Ogeawuchi, O. E. Akpe, A. A. Abayomi, O. A. Agboola, and S. Owoade, “Systematic Review of Advanced Data Governance Strategies for Securing Cloud-Based Data Warehouses and Pipelines,” Healthcare Analytics, vol. 45, no. 45 SP 45–45, 2022, Online]. Available: https://www.irejournals.com/paper-details/1708318
  22. Adelusi, O. B. S., K.-A. D., M. M. C., A. Y. Ikhalea, and N, “A deep learning approach to predicting diabetes mellitus using electronic health records,” S., Osamika, D., Kelvin-Agwu, M. C., Mustapha, A. Y., & Ikhalea, N. (2022). A deep learning approach to predicting diabetes mellitus using electronic health records. Journal of Frontiers in Multidisciplinary Research, vol. 2022), 2022.
  23. A. A. Cain, M. E. Edwards, and J. D. Still, “An exploratory study of cyber hygiene behaviors and knowledge,” Journal of Information Security and Applications, vol. 42, pp. 36–45, Oct. 2018, doi: 10.1016/J.JISA.2018.08.002.
  24. M. S. Jalali, M. Bruckes, D. Westmattelmann, and G. Schewe, “Why employees (still) click on phishing links: Investigation in hospitals,” J Med Internet Res, vol. 22, no. 1, Jan. 2020, doi: 10.2196/16775.
  25. M. Bar-Sinai, L. Sweeney, and M. Crosas, “DataTags, Data Handling Policy Spaces and the Tags Language,” Proceedings - 2016 IEEE Symposium on Security and Privacy Workshops, SPW 2016, pp. 1–8, Aug. 2016, doi: 10.1109/SPW.2016.11.
  26. E. O. Alonge, N. L. Eyo-Udo, B. C. Ubanadu, A. I. Daraojimba, and E. D. Balogun, “Enhancing data security with machine learning: A study on fraud detection algorithms,” Journal of Data Security and Fraud Prevention, vol. 7, no. 2, pp. 105–118, 2021.
  27. O. Ilori, C. I. Lawal, S. C. Friday, N. J. Isibor, and E. C. Chukwuma-Eke, “The Role of Data Visualization and Forensic Technology in Enhancing Audit Effectiveness: A Research Synthesis,” Journal of Frontiers in Multidisciplinary Research, vol. 3, no. 1, 2022.
  28. O. E. Adesemoye, E. C. Chukwuma-Eke, C. I. Lawal, N. J. Isibor, A. O. Akintobi, and F. S. Ezeh, “Improving financial forecasting accuracy through advanced data visualization techniques,” IRE Journals, vol. 4, no. 10, pp. 275–277, 2021, Online]. Available: https://irejournals.com/paper-details/1708078
  29. E. D. Balogun, K. O. Ogunsola, and A. Samuel, “A Risk Intelligence Framework for Detecting and Preventing Financial Fraud in Digital Marketplaces,” ICONIC RESEARCH AND ENGINEERING JOURNALS, vol. 4, no. 08, pp. 134–149, 2021.
  30. B. I. Adekunle, E. C. Chukwuma-Eke, E. D. Balogun, and K. O. Ogunsola, “Machine learning for automation: Developing data-driven solutions for process optimization and accuracy improvement,” Mach Learn, vol. 2, no. 1, p. 18, 2021.
  31. O. Ilori, C. I. Lawal, S. C. Friday, N. J. Isibor, and E. C. Chukwuma-Eke, “The Role of Data Visualization and Forensic Technology in Enhancing Audit Effectiveness: A Research Synthesis,” 2022.
  32. D. Jiang and G. Shi, “Research on Data Security and Privacy Protection of Wearable Equipment in Healthcare,” J Healthc Eng, vol. 2021, 2021, doi: 10.1155/2021/6656204.
  33. S. M. Boyne, “Data Protection in the United States,” American Journal of Comparative Law, vol. 66, pp. 299–343, Jul. 2018, doi: 10.1093/AJCL/AVY016.
  34. N. Hayatu, A. A. Abayomi, and A. C. Uzoka, “Advances in Managed Services Optimization for End-to-End Network Performance in High-Density Mobile Environment,” Iconic Research and Engineering Journals, vol. 3, no. 9, pp. 301–322, 2021, Online]. Available: https://www.irejournals.com/paper-details/1708634
  35. O. E. Akpe, J. C. Ogeawuchi, A. A. Abayomi, O. A. Agboola, and E. Ogbuefi, “Systematic Review of Last-Mile Delivery Optimization and Procurement Efficiency in African Logistics Ecosystems,” Iconic Research and Engineering Journals, vol. 5, no. 6, pp. 377–388, 2021, Online]. Available: https://www.irejournals.com/paper-details/1708521
  36. O. E. Akpe, J. C. Ogeawuchi, A. A. Abayomi, O. A. Agboola, and E. Ogbuefi, “A Conceptual Framework for Strategic Business Planning in Digitally Transformed Organizations,” Iconic Research and Engineering Journals, vol. 4, no. 4, pp. 207–222, 2020, Online]. Available: https://www.irejournals.com/paper-details/1708525
  37. B. I. Ashiedu, E. Ogbuefi, U. S. Nwabekee, J. C. Ogeawuchi, and A. A. Abayomi, “Automating Risk Assessment and Loan Cleansing in Retail Lending: A Conceptual Fintech Framework,” Iconic Research and Engineering Journals, vol. 5, no. 9, pp. 728–744, 2022, Online]. Available: https://www.irejournals.com/paper-details/1708535
  38. O. E. Akpe, J. C. Ogeawuchi, A. A. Abayomi, and O. A. Agboola, “Advances in Sales Forecasting and Performance Analysis Using Excel and Tableau in Growth-Oriented Startups,” International Journal of Management and Organizational Research, vol. 1, no. 1, pp. 231–236, 2022, doi: 10.54660/ijmor.2022.1.1.231-236.
  39. A. C. Mgbame, O. E. Akpe, A. A. Abayomi, E. Ogbuefi, and O. O. Adeyelu, “Developing Low-Cost Dashboards for Business Process Optimization in SMEs,” International Journal of Management and Organizational Research, vol. 1, no. 1, pp. 214–230, 2022, doi: 10.54660/ijmor.2022.1.1.214-230.
  40. E. Ogbuefi, A. C. Mgbame, O. E. Akpe, A. A. Abayomi, and O. O. Adeyelu, “Data Democratization: Making Advanced Analytics Accessible for Micro and Small Enterprises,” International Journal of Management and Organizational Research, vol. 1, no. 1, pp. 199–212, 2022, doi: 10.54660/ijmor.2022.1.1.199-212.
  41. E. C. Onukwulu, I. A. I. N.-D. Dienagha, W. N. Digitemie, and P. I. Egwumokei, “Advances in Digital Twin Technology for Monitoring Energy Supply Chain Operations,” Iconic Research and Engineering Journals, vol. 5, no. 12, pp. 372–400, 2022.
  42. J. L. Kamerer and D. McDermott, “Cybersecurity: Nurses on the Front Line of Prevention and Education,” J Nurs Regul, vol. 10, no. 4, pp. 48–53, Jan. 2020, doi: 10.1016/S2155-8256(20)30014-4.
  43. C. Wang, Z. Wang, G. Wang, J. Y. N. Lau, K. Zhang, and W. Li, “COVID-19 in early 2021: current status and looking forward,” Signal Transduct Target Ther, vol. 6, no. 1, Dec. 2021, doi: 10.1038/S41392-021-00527-1.
  44. A. T. Gebremeskel, A. Otu, S. Abimbola, and S. Yaya, “Building resilient health systems in Africa beyond the COVID-19 pandemic response,” BMJ Glob Health, vol. 6, no. 6, Jun. 2021, doi: 10.1136/BMJGH-2021-006108.
  45. K. Zhang et al., “Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography,” Cell, vol. 181, no. 6, pp. 1423-1433.e11, Jun. 2020, doi: 10.1016/J.CELL.2020.04.045.
  46. T. Jose et al., “Digital Health Surveillance Strategies for Management of Coronavirus Disease 2019,” Mayo Clin Proc Innov Qual Outcomes, vol. 5, no. 1, pp. 109–117, Feb. 2021, doi: 10.1016/J.MAYOCPIQO.2020.12.004.
  47. A. Y. Forkuo, E. C. Chianumba, A. Y. Mustapha, D. Osamika, and L. S. Komi, “Advances in digital diagnostics and virtual care platforms for primary healthcare delivery in West Africa,” Methodology, vol. 96, no. 71, p. 48, 2022.
  48. L. S. Komi, E. C. Chianumba, A. Yeboah, D. O. Forkuo, and A. Y. Mustapha, “Advances in Community-Led Digital Health Strategies for Expanding Access in Rural and Underserved Populations,” 2021.
  49. Iyiola Oladehinde Olaseni, “Digital Twin and BIM synergy for predictive maintenance in smart building engineering systems development,” World Journal of Advanced Research and Reviews, vol. 8, no. 2, pp. 406–421, Nov. 2020, doi: 10.30574/wjarr.2020.8.2.0409.
  50. K. O. Ogunsola, E. D. Balogun, and A. S. Ogunmokun, “Developing an automated ETL pipeline model for enhanced data quality and governance in analytics,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 3, 2022.
  51. L. Rusu and R. P. Tenga, “IT governance in the healthcare sector: A case study of a public and private hospital in Tanzania,” Int J Inf Syst Change Manag, vol. 4, no. 4, pp. 314–337, 2010, doi: 10.1504/IJISCM.2010.036915.
  52. U. Shrivastava, J. Song, B. Han, … D. D.-J. of M., and undefined 2021, “Do data security measures, privacy regulations, and communication standards impact the interoperability of patient health information? A cross-country,” Elsevier, Accessed: Jun. 05, 2025. Online]. Available: https://www.sciencedirect.com/science/article/pii/S1386505621000277
  53. K. O. Ogunsola, E. D. Balogun, and A. S. Ogunmokun, “Enhancing financial integrity through an advanced internal audit risk assessment and governance model,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 2, p. 21, 2021.
  54. O. Ilori, C. I. Lawal, S. C. Friday, N. J. Isibor, and E. C. Chukwuma-Eke, “Cybersecurity auditing in the digital age: A review of methodologies and regulatory implications,” Journal of Frontiers in Multidisciplinary Research, vol. 3, no. 1, pp. 174–187, 2022, Online]. Available: https://doi.org/10.54660/IJFMR.2022.3.1.174-187
  55. E. Ogbuefi, C. A. Mgbame, O. E. Akpe, A. A. Abayomi, and O. O. Adeyelu, “Affordable Automation: Leveraging Cloud-Based Healthcare Analytics Systems for Healthcare Innovation,” Healthcare Analytics, vol. 45, no. 45 SP 45–45, 2022, Online]. Available: https://www.irejournals.com/paper-details/1708219
  56. O. E. Akpe, C. A. Mgbame, E. Ogbuefi, A. A. Abayomi, and O. O. Adeyelu, “Bridging the Healthcare Intelligence Gap in Healthcare Enterprises: A Conceptual Framework for Scalable Adoption,” Healthcare Analytics, vol. 45, no. 45 SP 45–45, 2021, Online]. Available: https://www.irejournals.com/paper-details/1708222
  57. J. C. Ogeawuchi, O. E. Akpe, A. A. Abayomi, O. A. Agboola, and S. Owoade, “Systematic Review of Advanced Data Governance Strategies for Securing Cloud-Based Data Warehouses and Pipelines,” Iconic Research and Engineering Journals, vol. 6, no. 1, pp. 784–794, 2022, Online]. Available: https://www.irejournals.com/paper-details/1708318
  58. O. M. Oluoha, A. Odeshina, O. Reis, F. Okpeke, V. Attipoe, and O. Orieno, “Optimizing Business Decision-Making with Advanced Data Analytics Techniques,” Iconic Research and Engineering Journals, vol. 6, no. 5, pp. 184–203, 2022, Online]. Available: https://www.irejournals.com/paper-details/1703887
  59. J. C. Ogeawuchi, A. C. Uzoka, A. A. Abayomi, O. A. Agboola, and P. Gbenle, “Innovations in Data Modeling and Transformation for Scalable Business Intelligence on Modern Cloud Platforms,” Iconic Research and Engineering Journals, vol. 5, no. 5, pp. 406–415, 2021, Online]. Available: https://www.irejournals.com/paper-details/1708319
  60. I. Eaton and M. McNett, “Protecting the data: Security and privacy,” Data for Nurses: Understanding and Using Data to Optimize Care Delivery in Hospitals and Health Systems, pp. 87–99, Jan. 2019, doi: 10.1016/B978-0-12-816543-0.00006-6.
  61. A. Geissbuhler et al., “Trustworthy reuse of health data: A transnational perspective,” Int J Med Inform, vol. 82, no. 1, pp. 1–9, Jan. 2013, doi: 10.1016/J.IJMEDINF.2012.11.003.
  62. S. Nifakos et al., “Influence of human factors on cyber security within healthcare organisations: A systematic review,” Sensors, vol. 21, no. 15, Aug. 2021, doi: 10.3390/S21155119.
  63. L. A. Saxon, N. Varma, L. M. Epstein, L. I. Ganz, and A. E. Epstein, “Factors influencing the decision to proceed to firmware upgrades to implanted pacemakers for cybersecurity risk mitigation,” Circulation, vol. 138, no. 12, pp. 1274–1276, 2018, doi: 10.1161/CIRCULATIONAHA.118.034781.
  64. M. Allen et al., “Maximising value from a united kingdom biomedical research centre: Study protocol,” Health Res Policy Syst, vol. 15, no. 1, Aug. 2017, doi: 10.1186/S12961-017-0237-1.
  65. M. Dixon-Woods et al., “Culture and behaviour in the English National Health Service: overview of lessons from a large multimethod study,” BMJ Qual Saf, vol. 23, no. 2, pp. 106–115, Feb. 2014, doi: 10.1136/BMJQS-2013-001947.
  66. I. E. Agbehadji, B. O. Awuzie, A. B. Ngowi, and R. C. Millham, “Review of big data analytics, artificial intelligence and nature-inspired computing models towards accurate detection of COVID-19 pandemic cases and contact tracing,” Int J Environ Res Public Health, vol. 17, no. 15, pp. 1–16, Aug. 2020, doi: 10.3390/IJERPH17155330.
  67. A. Ifesinachi Daraojimba, F. Uche Ojika, W. Oseremen Owobu, O. Anthony Abieba, O. Janet Esan, and B. Chibunna Ubamadu, “Optimizing AI Models for Cross-Functional Collaboration: A Framework for Improving Product Roadmap Execution in Agile Teams,” 2021. Online]. Available: https://www.researchgate.net/publication/390928998
  68. J. G. Faulkenberry, A. Luberti, and S. Craig, “Electronic health records, mobile health, and the challenge of improving global health,” Curr Probl Pediatr Adolesc Health Care, vol. 52, no. 1, Jan. 2022, doi: 10.1016/j.cppeds.2021.101111.
  69. O. E. Akpe, J. C. Ogeawuchi, A. A. Abayomi, and O. A. Agboola, “Advances in Stakeholder-Centric Product Lifecycle Management for Complex, Multi-Stakeholder Energy Program Ecosystems,” Healthcare Analytics, vol. 45, no. 45 SP 45–45, 2021, Online]. Available: https://www.irejournals.com/paper-details/1708349
  70. E. C. Chianumba, N. Ikhalea, A. Y. Mustapha, A. Y. Forkuo, and D. Osamika, “Integrating AI, blockchain, and big data to strengthen healthcare data security, privacy, and patient outcomes,” Journal of Frontiers in Multidisciplinary Research, vol. 3, no. 1, pp. 124–129, 2022.
  71. L. S. Komi, E. C. Chianumba, A. Yeboah, D. O. Forkuo, and A. Y. Mustapha, “A Conceptual Framework for Telehealth Integration in Conflict Zones and Post-Disaster Public Health Responses,” 2021.
  72. K. McCracken and D. R. Phillips, “Health systems, finance and planning,” Global Health, pp. 247–286, Nov. 2018, doi: 10.4324/9781315691800-8/HEALTH-SYSTEMS-FINANCE-PLANNING-KEVIN-MCCRACKEN-DAVID-PHILLIPS.
  73. G. B. Melton, C. J. McDonald, P. C. Tang, and G. Hripcsak, “Electronic health records,” Biomedical Informatics: Computer Applications in Health Care and Biomedicine: Fifth Edition, pp. 467–509, Jul. 2021, doi: 10.1007/978-3-030-58721-5_14.
  74. F. Reza, J. T. Prieto, and S. P. Julien, “Electronic Health Records: Origination, Adoption, and Progression,” pp. 183–201, 2020, doi: 10.1007/978-3-030-41215-9_11/FIGURES/1.
  75. I. N. Dienagha, F. O. Onyeke, W. N. Digitemie, and M. A. Adewoyin, “Strategic reviews of greenfield gas projects in Africa: Lessons learned for expanding regional energy infrastructure and security,” GSC Advanced Research and Reviews, vol. 8, no. 01, pp. 187–195, 2021.
  76. Ikiomoworio Nicholas Dienagha, Fidelis Othuke Onyeke, Wags Numoipiri Digitemie, and Musa Adekunle Adewoyin, “Strategic reviews of greenfield gas projects in Africa: Lessons learned for expanding regional energy infrastructure and security,” GSC Advanced Research and Reviews, vol. 8, no. 1, pp. 187–195, Jul. 2021, doi: 10.30574/gscarr.2021.8.1.0156.
  77. A. Odeshina, O. Reis, F. Okpeke, V. Attipoe, and O. Orieno, “Artificial Intelligence Integration in Regulatory Compliance: A Strategic Model for Cybersecurity Enhancement,” Journal of Frontiers in Multidisciplinary Research, vol. 3, pp. 35–46, 2022, Online]. Available: https://www.researchgate.net/publication/391901838
  78. E. C. Chianumba, N. Ikhalea, A. Y. Mustapha, and A. Y. Forkuo, “Developing a framework for using AI in personalized medicine to optimize treatment plans,” Journal of Frontiers in Multidisciplinary Research, vol. 3, no. 1, pp. 57–71, 2022.
  79. B. I. Adekunle, E. C. Chukwuma-Eke, E. D. Balogun, and K. O. Ogunsola, “Predictive Analytics for Demand Forecasting: Enhancing Business Resource Allocation Through Time Series Models,” Journal of Frontiers in Multidisciplinary Research, vol. 2, no. 01, pp. 32–42, 2021.
  80. T. A. Wani, A. Mendoza, and K. Gray, “Hospital Bring-your-own-device security challenges and solutions: Systematic review of gray literature,” JMIR Mhealth Uhealth, vol. 8, no. 6, Jun. 2020, doi: 10.2196/18175.
  81. C. M. Williams, R. Chaturvedi, and K. Chakravarthy, “Cybersecurity risks in a pandemic,” J Med Internet Res, vol. 22, no. 9, Sep. 2020, doi: 10.2196/23692.
  82. O. M. Oluoha, A. Odeshina, O. Reis, F. Okpeke, V. Attipoe, and O. Orieno, “Development of a Compliance-Driven Identity Governance Model for Enhancing Enterprise Information Security,” Iconic Research and Engineering Journals, vol. 4, no. 11, pp. 310–324, 2021, Online]. Available: https://www.irejournals.com/paper-details/1702715
  83. G. O. Osho, “Decentralized Autonomous Organizations (DAOs): A Conceptual Model for Community-Owned Banking and Financial Governance,” Unknown Journal, 2020.
  84. B. C. Ubamadu, D. Bihani, A. I. Daraojimba, G. O. Osho, and J. O. Omisola, “Optimizing Smart Contract Development: A Practical Model for Gasless Transactions via Facial Recognition in Blockchain,” Unknown Journal, 2022.
  85. B. Adebisi, E. Aigbedion, O. B. Ayorinde, and E. C. Onukwulu, “A Conceptual Model for Predictive Asset Integrity Management Using Data Analytics to Enhance Maintenance and Reliability in Oil & Gas Operations,” International Journal of Multidisciplinary Research and Growth Evaluation, vol. 2, 2021.
  86. J. O. Omisola, J. O. Shiyanbola, and G. O. Osho, “A Predictive Quality Assurance Model Using Lean Six Sigma: Integrating FMEA, SPC, and Root Cause Analysis for Zero-Defect Production Systems,” Unknown Journal, 2020.
  87. G. Fredson, B. Adebisi, O. B. Ayorinde, E. C. Onukwulu, and O. Adediwin, “Maximizing Business Efficiency through Strategic Contracting: Aligning Procurement Practices with Organizational Goals,” International Journal of Social Science Exceptional Research, vol. 1, no. 1, pp. 1–15, 2022.
  88. B. Adebisi, E. Aigbedion, O. B. Ayorinde, and E. C. Onukwulu, “A Conceptual Model for Implementing Lean Maintenance Strategies to Optimize Operational Efficiency and Reduce Costs in Oil & Gas Industries,” International Journal of Management and Organizational Research, vol. 1, no. 1, pp. 50–57, 2022.
  89. O. E. Akpe, J. C. Ogeawuchi, A. A. Abayomi, and O. A. Agboola, “Advances in Stakeholder-Centric Product Lifecycle Management for Complex, Multi-Stakeholder Energy Program Ecosystems,” Iconic Research and Engineering Journals, vol. 4, no. 8, pp. 179–188, 2021, Online]. Available: https://www.irejournals.com/paper-details/1708349
  90. D. Classen, M. Li, S. Miller, and D. Ladner, “An electronic health record–based real-time analytics program for patient safety surveillance and improvement,” Health Aff, vol. 37, no. 11, pp. 1805–1812, Nov. 2018, doi: 10.1377/HLTHAFF.2018.0728;CTYPE:STRING:JOURNAL.
  91. K. Alam, R. A. Mahumud, F. Alam, S. A. Keramat, M. O. Erdiaw-Kwasie, and A. R. Sarker, “Determinants of access to eHealth services in regional Australia,” Int J Med Inform, vol. 131, Nov. 2019, doi: 10.1016/j.ijmedinf.2019.103960.
  92. L. P. C. Brewer et al., “Back to the future: Achieving health equity through health informatics and digital health,” JMIR Mhealth Uhealth, vol. 8, no. 1, 2020, doi: 10.2196/14512.
  93. J. Shaw, L. P. C. Brewer, and T. Veinot, “Recommendations for health equity and virtual care arising from the COVID-19 pandemic: Narrative review,” JMIR Form Res, vol. 5, no. 4, Apr. 2021, doi: 10.2196/23233.
  94. S. Helou et al., “The effect of the covid-19 pandemic on physicians’ use and perception of telehealth: The case of lebanon,” Int J Environ Res Public Health, vol. 17, no. 13, pp. 1–17, Jul. 2020, doi: 10.3390/IJERPH17134866.
  95. A. Odeshina, O. Reis, F. Okpeke, V. Attipoe, O. Orieno, and A. Pub, “A Unified Framework for Risk-Based Access Control and Identity Management in Compliance-Critical Environments,” Journal of Frontiers in Multidisciplinary Research, vol. 3, pp. 23–34, 2022, Online]. Available: https://www.researchgate.net/publication/390618881
  96. V. Saini, D. Pal, and S. R.-J. of A. I. Research, “Data Quality Assurance Strategies In Interoperable Health Systems,” researchgate.net, Accessed: Jun. 05, 2025. Online]. Available: https://www.researchgate.net/profile/Dheeraj-Kumar-Pal/publication/390931351_Data_Quality_Assurance_Strategies_In_Interoperable_Health_Systems/links/6802f59edf0e3f544f42c826/Data-Quality-Assurance-Strategies-In-Interoperable-Health-Systems.pdf
  97. “Data Governance and Data Sharing Agreements for Community-Wide Health Information Exchange: Lessons from the Beacon Communities - PMC.” Accessed: Jun. 05, 2025. Online]. Available: https://pmc.ncbi.nlm.nih.gov/articles/PMC4371395/
  98. K. McCracken and D. R. Phillips, “Global environmental change and health,” Global Health, pp. 287–309, Nov. 2018, doi: 10.4324/9781315691800-9/GLOBAL-ENVIRONMENTAL-CHANGE-HEALTH-KEVIN-MCCRACKEN-DAVID-PHILLIPS.
  99. Chianumba, I. E. C., M. N., F. A. Y., A. Y. Osamika, and D, “Developing a predictive model for healthcare compliance, risk management, and fraud detection using data analytics,” C., Ikhalea, N., Mustapha, A. Y., Forkuo, A. Y., & Osamika, D. (2022). Developing a predictive model for healthcare compliance, risk management, and fraud detection using data analytics. International Journal of Social Science Exceptional Research, vol. 2022), 2022.
  100. E. Kirkland et al., “Patient Demographics and Clinic Type Are Associated with Patient Engagement within a Remote Monitoring Program,” Telemedicine and e-Health, vol. 27, no. 8, pp. 843–850, Aug. 2021, doi: 10.1089/TMJ.2020.0535.
  101. J. A. Andersen, D. Scoggins, T. Michaud, N. Wan, M. Wen, and D. Su, “Racial Disparities in Diabetes Management Outcomes: Evidence from a Remote Patient Monitoring Program for Type 2 Diabetic Patients,” Telemedicine and e-Health, vol. 27, no. 1, pp. 55–61, Jan. 2021, doi: 10.1089/TMJ.2019.0280.
  102. L. Coventry and D. Branley, “Cybersecurity in healthcare: A narrative review of trends, threats and ways forward,” Maturitas, vol. 113, pp. 48–52, Jul. 2018, doi: 10.1016/J.MATURITAS.2018.04.008.
  103. H. Alami, M. P. Gagnon, M. A. Ag Ahmed, and J. P. Fortin, “Digital health: Cybersecurity is a value creation lever, not only a source of expenditure,” Health Policy Technol, vol. 8, no. 4, pp. 319–321, Dec. 2019, doi: 10.1016/J.HLPT.2019.09.002.

International Journal of Scientific Research in Science and Technology

Downloads

Published

2022-04-30

Issue

Volume 9, Issue 2, March-April-2022

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Damilola Oluyemi Merotiwon, Opeyemi Olamide Akintimehin, Opeoluwa Oluwanifemi Akomolafe "Designing Training Models for Health Workers on Data Security and Information Confidentiality in the Digital Era " International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 9, Issue 2, pp.616-630, March-April-2022.