MediLinkUp: eHEALTH SYSTEM FOR DETECTION, DIAGNOSIS, AND ANALYSIS.
Maximizing digital health technology to improve quality and patient safety in Africa
What specific problem MediLinkUp solving?Sub-Saharan Africa is a resource-constrained region that suffers a top-heavy share of the world’s burden of disease.
According to the World Health Organization (WHO), about 12% of the world’s population lives in sub-Saharan Africa, yet the region suffers 27% of the world’s total burden of disease.
Timely as well as accurate patient information is essential to meet the health-care needs of any patient in any population.
Physicians and other care providers require high-quality information to make sound clinical decisions; however, their information needs are often not met.
The first three challenges identified were inadequate human resources (34.29%), inadequate budgetary allocation to health (30%), and poor leadership and management (8.45%). The leading solutions suggested included training and capacity building for health workers (29.69%), increased budgetary allocation to health (20.31%), and advocacy for political support and commitment (12.31%).The critical need for good health information systems in sub-Saharan Africa has become the current focus of attention.
Many studies conducted in different health-care settings have indicated that EHRs will assist health professionals to reduce medical errors, achieve better effective care coordination, improve safety and quality, and also, it can reduce health-care costs.
MediLinkUp :eHEALTH SYSTEM FOR DETECTION, DIAGNOSIS, AND ANALYSIS.
Solution: medical records (EMRs) or electronic health records (EHR)
MediLinkUp is an innovative cost effective e-health software involving the use of AI, Electronic Medical Records (EMRs), Electronic Health Records (EHRs) and Personal Health Records for early disease and symptom prediction and detection. This solution features an innovative system that integrates digital health technology to bridge the health information technology (HIT) gap in Sub-Saharan Africa.
MediLinkUp provides a radical improvement for health professionals & patients, changing the approach in which healthcare is delivered. It is built to assist health professionals manage disease burdens while delivering quality patient care.
Unique qualities include:
Resonance: MediLinkUp solves the issue of lack of high-quality information for health professionals to make sound clinical decisions and in doing so, it shows its ability to have an impact/positive influence on health information technology (HIT) in Sub-Saharan Africa. Possessing a deep understanding of the problem provides MediLinkUp with an advantage of resonance (identifying, analysing & eradicating).
Adaptability: Our technology paves the way to improvements in data management, training of health workers and making referrals. Our solution assists health professionals to reduce medical errors, achieve more effective care coordination, improve safety & quality, and finally, reduce health-care costs. Our adaptability feature enables the easy use of our software in urban, rural & hard-to-reach areas.
Accessibility: MediLinkUp makes health information accessible by the inclusion of a multilingual feature in our software. This enables the easy use and accessibility of our software & health information in different local languages. This gives us a cutting edge.
Core technology that powers your solution.
MediLinkUp offers eHaaS MediLinkUp, a new innovative digital health systems solution, which operates on a new efficient technological infrastructure, designed to adapt to external systems that will interface.
Its deployment is done by interfacing via a webservices to health information systems hosted in hospitals, clinics and other public or private health centers.
The eHaaS MediLinkUp application environment (the web server, the application server and the database) communicates with all of types of health information systems.
Customers devices (Smartphone, Tablet, Computer) connect to the web server via URL (Web Portal) and Mobile App (Mobile Application) in the most secure manner possible.
It is a modular solution deployed on the following technological infrastructure:
- a Database server for securing and storing data;
- an application server necessary for the execution of the eHaaS MediLinkUp applications;
- a web server for managing http / https sessions;
It requires the establishment of an IT platform for:
- production;
- test and integration;
- training;
- backup.
Features include Data collection, Machine learning, eHealth, disease, symptoms, detection, prediction, early detection using AI,EMRs,EHRs, Personal Health Records, eHealth-as-a-Service (eHaaS).
The system will allow an authenticated user to signup and create patient data. The patient data will include their biodata, anthropometrics data, and disease symptoms related data.
The system will apply Machine learning and Data Analytics (on the data collected) to predict disease outbreak in specific geographical areas and also for early detection of diseases in individuals. Health officials can then take steps to prevent further spread of certain diseases and/or apply early treatments.
Organization NameMediLinkUp: eHEALTH SYSTEM FOR DETECTION, DIAGNOSIS, AND ANALYSIS.
Organization WebsiteMVP : https://sites.google.com/view/medilinkup/home
Organization TypeEarly-stage startup (e.g., idea stage looking to build a prototype)
What is the product?A simple, user-friendly, and cost-effective software to assist African medical and healthcare professionals to manage diseases, analyze data, and to provide quality patient care across Africa.
Fig. 1: MedilinkUP technical architecture.
Is there an existing software?The software is still being developed. A first prototype can be found here: https://sites.google.com/view/medilinkup/home
Who will use the product?Researchers center
- Health centers
- Ministries of Health
- Private clinics
– Center for disease control
–NGOs
What are the key functionalities to be built?Features include Data collection, Machine learning, eHealth, COVID-19, disease, symptoms, detection, prediction, early detection using AI, Electronic Medical Records (EMRs), Electronic Health Records (EHRs), Personal Health Records, eHealth-as-a-Service (eHaaS).
Fig. 2: MedilinkUP Use Case diagram
Fig. 2 shows the use case diagram above captures (at a high level) the system functionalities. It shows the system actors (i.e. authenticated and non-authenticated users) and the actions (or functions e.g. create patient, update patient, view health analytic data) the system provides them.
The system will allow an authenticated user (e.g. medical doctors and other health workers) to signup and create patient data. The patient data will include their biodata, anthropometrics data, and disease symptoms related data (e.g. COVID 19, Ebola, Malaria, etc).
The system will apply Machine learning and Data Analytics (on the data collected) to predict disease outbreak in specific geographical areas and also for early detection of diseases in individuals. Health officials can then take steps to prevent further spread of certain diseases and/or apply early treatments.
MediLinkUp data modelling
Fig. 3: MedilinkUP database schema
The Fig. 3 shows the database schema for the MediLinkUp health system. Although this document shows the relationship database schema (for simplicity), the actual database is implemented using MongoDB (NoSQL approach). The NoSQL is preferred for our application because it provides more flexibility as it allows unstructured data storage and the use of objects in the database design. This also allows for better performance (database operations).
Each table (collection in MongoDB terminology) shows the data fields that will be stored in it and how they relate with the other table(s). This database schema will allow us to collect relevant data (bio, anthropometrics, diseases, and external data) data that will be analyzed for early disease detection and outbreaks.
Fig. 4: MedilinkUP deployment diagram
Fig. 4 above shows the deployment diagram for the MediLinkUp system. As discussed earlier, the data collected will be stored in a MongoDB database hosted on the cloud. A web server will host the RESTful API that provides stateless data to the web application and mobile application. The web application will be accessible via web browsers, while the mobile version will be available on IOS and Android devices.
What value does this project bring to your organization?Our main focus is to provide scalable and intelligent applications in Africa's health space. This project will enable us to achieve that through the use of data science and machine learning in health.
Fig. 5: MediLinkUp Product
Prototype
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