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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
Subject area: Science,Engineering and Technology · Area of research: Information Technology
DOI: https://doi.org/10.64388/IREV10I1-1719811
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.
How to cite this paper
@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}
}