Design and Implementation of an Intelligent Automated Medical Record Management System with Cloud Integration for Primary Health Care in a Typical Nigerian Local Government Area

References

[1] A. Bitton, H. L Ratcliffe, J. H. Veillard, D. H. Kress, S. Barkley, M. Kimball, F. Secci, E. Wong, L Basu, C. Taylor, J. Bayona, H. Wang, G. Lagomarsino & L. R. Hirschhorn. Primary health care as a foundation for strengthening health systems in low- and middle-income countries. Journal of General Internal Medicine, 2017, 32(5), 566–571. https://doi.org/10.1007/s11606-016-3898-5

[2] A. Aghaji. Assessing the technical capacity of primary health care facilities in Anambra State, Nigeria to implement the World Health Organisation African Region's primary eye care package. 2024: Doctoral dissertation, London School of Hygiene & Tropical Medicine).

[3] J. N. Igabari. The population question in Nigeria: Models and reliable projections. Asian Research Journal of Mathematics, 2017:5(3), 1–10. https://doi.org/10.9734/ARJOM/2017/33989

[4] O. K. Boyinbode & G. Toriola. CloudeMR: A cloud based electronic medical record system. International Journal of Hybrid Information Technology, 2015:8(4), 201–212. https://doi.org/10.14257/ijhit.2015.8.4.23

[5] J. Adler-Milstein & A. K. Jha . HITECH Act Drove Large Gains In Hospital Electronic Health Record Adoption. Health Aff (Millwood). 2017: 36(8): 1416 – 1422. doi:10.1377/hlthaff.2016.1651. PMID: 28784734.

[6] D. W. Bates, M. Cohen, L. L Leape, J. M. Overhage, M. M. Shabot & T. Sheridan. Reducing the frequency of errors in medicine using information technology. Journal of the American Medical Informatics Association, 2001: 8(4), 299–308. https://doi.org/10.1136/jamia.2001.0080299

[7] A. A. Abubakar, A. Abba, O. Fasawe, T. Hussaini, N. Umar, A. Bukari & K. Gulma. Improving facility-level performance in primary healthcare systems through strengthening management and financial resource utilization in Kano State, Nigeria. SSM – Health Systems, 2025: 100080.

[8] Akanbi, M. O., Ocheke, A. N., Agaba, P. A., Daniyam, C. A., Agaba, E. I., Okeke, E. N., & Ukoli, C. O. (2012). Use of electronic health records in sub-Saharan Africa: Progress and challenges. Journal of Medicine in the Tropics, 2012:14(1), 1–6. https://pmc.ncbi.nlm.nih.gov/articles/PMC4167769/

[9] E. O. Aghanenu, J. N. Igabari, R Jenije & F. I. Arunaye. Simulating models for the transmission dynamics of a novel coronavirus under the administration of an imperfect vaccine in Nigeria. Journal of Mathematics and Computer Science. 2022: 12, Article 155. https://doi.org/10.28919/jmcs/7254

[10] J. C. Ehiwario, J. N. Igabari & P. E. Ezimadu. Theory and applications of the alpha power type II Topp–Leone-generated family of distributions. Reliability: Theory & Applications. 2023: 18(3.74), 785–807. https://doi.org/10.24412/1932-2321-2023-374-785-807

[11] D. Jegede. Challenges facing the administration of ICT infrastructural facilities in public primary schools in Nigeria. Electronic Research Journal of Engineering, Computer and Applied Sciences. 2019: 1, 30–40. https://ssrn.com/abstract=3703495

[12] T. A. Bekele, L. D. Gezie, H. Willems, J. Metzger, B, Abere, B. Seyoum, L. Abraham, N. Wendrad, S. Meressa, B. Desta & T. N. Bogale. Barriers and facilitators of the electronic medical record adoption among healthcare providers in Addis Ababa, Ethiopia. Digital Health, 2024. 10, 20552076241301946. https://doi.org/10.1177/20552076241301946

[13] H. Alzghaibi & H. A. Hutchings. (2025). Barriers to the implementation of large-scale electronic health record systems in primary healthcare centers: A mixed-methods study in Saudi Arabia. Frontiers in Medicine, 2025: 12, Article 1516714. https://doi.org/10.3389/fmed.2025.1516714

[14] N. N. Onyemarin, H. I. Ojarikre & J. N. Igabari. An ARMA modelling approach on infant mortality rate in Nigeria. Nigerian Journal of Science and Environment, 2023: 21(1), 94–114.

[15] H. S. F. Fraser, P. Biondich, D. Moodley, S. Choi, B. W. Mamlin & P. Szolovits. Implementing electronic medical record systems in developing countries. Informatics in Primary Care, 2005: 13(2), 83–95. https://doi.org/10.14236/jhi.v13i2.585

[16] R. Dhakal. Case study on open source tools used for healthcare systems. Course project, 2023: Kathmandu University. ResearchGate. https://www.researchgate.net/publication/391047459_ CASE_STUDY_ON_OPEN_SOURCE_TOOLS_USED_FOR_HEALTHCARE_SYSTEMS

[17] S. S. Yisa, T. J. Ogunniyi & R. D. Dine. (2025). Strengthening primary health care in Nigeria: A means to achieve universal health coverage. BMJ Global Health, 2025: 10(10), e018486. https://doi.org/10.1136/bmjgh-2024-018486

[18] C. Ajaegbu, S. O. Okikiola, O. O. Ajaegbu & O. Adediran. Transforming healthcare in Nigeria through ICT: An in-depth analysis at Federal Medical Centre Idi-Aba, Abeokuta. International Journal of Modeling and Applied Science Research, 2024: 3(9). https://cambridgeresearchpub.com/ijmasr/article/view/193

[19] O. Iroju, A. Soriyan, I. Gambo & J. Olaleke. Interoperability in healthcare: Benefits, challenges and resolutions. International Journal of Innovation and Applied Studies, 2013: 3(1), 262–270. http://www.ijias.issr-journals.org/abstract.php?article=IJIAS-13-090-01

[20] T. Adedeji, H. Fraser & P. Scott. Implementing electronic health records in primary care using the theory of change: Nigerian case study. JMIR Medical Informatics, 2022: 10(8), e33491. https://doi.org/10.2196/33491

[21] A. M. Kuo. Opportunities and challenges of cloud computing to improve health care services. Journal of Medical Internet Research, 2011: 13(3), e67. https://doi.org/10.2196/jmir.1867

[22] S. Sachdeva, S. Bhatia, A. Al Harrasi, Y. A. Shah, K. Anwer, A. K. Philip, S. F. A. Shah, A. Khan & S. A. Halim. Unraveling the role of cloud computing in health care system and biomedical sciences. Heliyon, 2024: 10(7), e29044. https://doi.org/10.1016/j.heliyon.2024.e29044

[23] M. M. Alhaji,M. R. Balarabe, D. Atama, A. Okafor, D. Solana, F. Meyo, C. J. Okoye, U. Okafor, B. Oyelana & J. Anyanti. Motivators and barriers to the uptake of digital health platforms for family planning services in Lagos, Nigeria: A mixed-methods study. Digital Health, 2025: 11, 20552076251349624. https://doi.org/10.1177/20552076251349624

[24] T. C. Lee, N. U. Shah, A. Haack & S. I. Baxter. Clinical implementation of predictive models embedded within electronic health record systems: A systematic review. Informatics, 2020:7(3), 25. https://doi.org/10.3390/informatics7030025

[25] H. D. Mugauri, M. Chimsimbe, G. Shambira, S. Shamhu, J. Nyamasve, M. Munyanyi, R. Gongora, S. Zizhou, M. Gabida & R. Makurumidze. A decade of designing and implementing electronic health records in Sub-Saharan Africa: A scoping review. Global Health Action, 2025: 18(1), 2492913. https://doi.org/10.1080/16549716.2025.2492913

@article{1719811,
      author = {Enoriuwa N. Jimade , Israel Otito Igabari },
      title = {Design and Implementation of an Intelligent Automated Medical Record Management System with Cloud Integration for Primary Health Care in a Typical Nigerian Local Government Area },
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {1},
      pages = {1656-1664},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1719811.pdf},
      abstract = {Reliable medical record management sits at the centre of clinical decision-making, continuity of care, and health reporting in primary health care (PHC). Across Local Government Areas in Nigeria, most facilities still run on paper files or basic spreadsheets, and the consequences are predictable: records fragment, retrieval drags, files go missing, and little of the data ever reaches the national systems meant to use it. Electronic Medical Record (EMR) systems and Cloud Computing are hardly new, but the versions that reach low-resource settings tend to fall short in a few identifiable ways. They assume constant connectivity, they do not synchronise in real time, and they leave data quality to the user. This study is intended to address this gap through the design , building and field-testing an Intelligent Automated Medical Record Management System (IAMRMS) with cloud integration, shaped around the conditions PHC facilities available in a Nigerian Local Government Area. The system was designed to run a web interface against a local cache so that it keeps working when the network drops, and it adds intelligent entry validation, role-based access, and automated cloud backup. Development followed an iterative Agile process, while evaluation was experimental. The IAMRMS was compared against the manual and semi-digital methods already in use, drawing on a survey of 169 respondents (a 91.4% response rate). The gains were substantial because average record retrieval time fell from 8.6 minutes on paper and 3.4 minutes on spreadsheets to 0.9 minutes, while data-entry accuracy rose from 85.2% on paper and 90.5% on spreadsheet to 97.8% on IAMRSMS, with a 99.2% functional uptime. A chi-square test confirmed the improvement was statistically significant at p < 0.05 rather than incidental. Thus, the study upholds that pairing intelligent automation with cloud integration and an offline-first design offers a workable and scalable route to better record-keeping in settings where infrastructure cannot be assumed.},
      keywords = {Electronic Medical Records; Cloud Computing; Offline-First Architecture; Primary Health Care; Local Government Area.},
      month = {July},
      doi = {https://doi.org/10.64388/IREV10I1-1719811}
  }