Revolutionizing Healthcare: Integrating MOH and Germany Afia for Better Data Consolidation

Table of Contents

1. Introduction
2. Our Vision and Mission
3. About D3 and Chamini Afya Project
4. Integration Process Overview
5. Why Did We Integrate?
6. The Use Case: Pushing Aggregate Data
7. Step 1: Creating Organization Units, Data Elements, and Category Option Combination
8. Step 2: Creating SQL Queries to Fetch Data Values
9. Step 3: Mapping between DHIS2 and CHD
10. Step 4: Converting Data into a Suitable Format
11. Challenges Faced
12. Next Steps
13. Conclusion

🌟Highlights🌟

• D3's vision and mission to improve healthcare through digital technology.
• The Chamini Afya project and its impact on Zanzibar.
• Integration process between MOH and Germany Afia.
• Importance of consolidating data at both health facility and community levels.
• Use case example of pushing aggregate data.
• Creating organization units, data elements, and SQL queries.
• Mapping between DHIS2 and CHD.
• Challenges faced during integration.
• Future plans for automation and database restructuring.

Introduction

Welcome to this article, where we will dive into the integration process between the Ministry of Health (MOH) and Germany Afia. Before we go into the details, let's start with an overview of our organization's vision and mission.

Our Vision and Mission

At D3, our vision is to create a future where everyone has access to high-quality healthcare. To achieve this, our mission is to improve lives by strengthening health systems through digital technology. We believe that leveraging technology can revolutionize healthcare, making it more accessible and efficient.

About D3 and Chamini Afya Project

D3 primarily focuses on the Chamini Afya project in Jamini Afya. For those unfamiliar, Jamini Afya is a Swahili word that translates to "community is health." Powered by CHT (Community Health Toolkit), the Chamini Afya app has been successfully deployed in Zanzibar, covering 50% of the population in 11 districts.

The Chamini Afya project covers various use cases, including ANC (Antenatal Care), PNT (Postnatal Care), child immunization, early childhood development, ICCM (Integrated Community Case Management), and COVID-19. In addition to the CHV (Community Health Volunteer) CHT application, there are plans underway with Medic to design and develop a dedicated Supervisor Reference Application.

The Chamini Afya app provides comprehensive features such as a task list for CHVs, a people's tab showing registered households, and targets for CHVs to achieve on a monthly basis.

Integration Process Overview

Now, let's focus on the integration process itself. Before we delve into the "how," let's first understand the "why." Why did MOH decide to integrate with Germany Afia? The answer lies in the need to consolidate data at both the health facility and community levels.

MOH collects data at the health facility level, while Germany Afia collects data at the community level, which is one level below district level. By integrating these two systems, MOH aims to gain a more in-depth coverage of data to facilitate better healthcare delivery.

To illustrate the integration process, let's walk through a use case scenario.

The Use Case: Pushing Aggregate Data

Imagine that we want to push aggregate data about the number of under-five children visited by CHVs, categorized by sex. Our goal is to push this data at the Shahia level on a monthly basis.

The integration process begins with CHVs collecting the data and then syncing it. Once the data is synced, it is stored in our database. At this point, a script pulls the data from the database, converts it into a suitable format for pushing to DHIS2 (District Health Information System 2), and then pushes the data on a monthly basis using a cron job.

Now, let's break down the steps involved in the integration process.

Step 1: Creating Organization Units, Data Elements, and Category Option Combination

In order to push the data to DHIS2, we first need to create the necessary organization units, data elements, and category option combinations. For our use case, we are pushing aggregate data for under-five children visited by CHVs.

To do this, we create an organization unit for the Shahia (e.g., Chachanisha) and assign a corresponding ID. Then, we create a data element for the under-five children enrolled by CHVs, along with its ID and the category option combination for male and female. These IDs are crucial for mapping the data between DHIS2 and CHD.

Step 2: Creating SQL Queries to Fetch Data Values

Next, we create SQL queries to fetch the data values we need. In our use case, we want to retrieve the number of under-five children enrolled by CHVs, categorized by gender.

The SQL query defines columns for the data element name, value, Shahia, district, and gender. Running this query gives us a table with the corresponding data values.

Step 3: Mapping between DHIS2 and CHD

With the data elements and queries in place, the next step is to establish a mapping between DHIS2 and CHD. This mapping is crucial for correctly pushing the data to DHIS2.

A mapping file is created, which contains the Shahia mapping for location and the mapping of Jamini Afya Shahia names with their corresponding IDs from DHIS2. The mapping file ensures that the data is correctly associated with the respective data elements in DHIS2.

Step 4: Converting Data into a Suitable Format

Once the mapping is established, the data is converted into a format suitable for pushing to DHIS2. This conversion is done by a script, which generates a final file called the data value set file.

The data value set file contains the data element ID, the period for which the data is being sent, the organization unit ID, the category option combination for male or female, and the corresponding value. This file is then ready to be pushed into DHIS2, where it will be associated with the respective data elements for the designated period.

Challenges Faced

Throughout the integration process, we encountered several challenges. One of the main challenges was sinking issues reported by CHVs. This was often due to broken or lost devices, as well as connectivity issues in some areas. To overcome this, we implemented a strategy of pushing not only the current month's data but also the data for the previous two months to fill the gaps.

Another challenge was occasional server connectivity issues. If the CouchDB to PostgreSQL (pg) server was down, it hindered the relay of data and resulted in gaps. However, we have now implemented notifications for server failures, which enables us to take prompt action.

Additionally, changes in indicator or data element requirements posed challenges. As requirements for indicators change over time, we have to ensure that historical records are correctly pushed alongside current data. This also necessitates adjusting our queries to accommodate the new requirements.

Next Steps

Looking ahead, we have identified a few areas for improvement in the integration process. One of our next steps is to work on a notification system for errors and failures in scripts. Currently, we rely on manual monitoring of logs, but we aim to automate this process to ensure timely identification of issues.

Furthermore, we plan to restructure our database to simplify queries. Some of our current queries suffer from complexity, and we are not satisfied with the efficiency. By restructuring the database, we anticipate streamlining the integration process and improving overall performance.

Conclusion

In conclusion, the integration between MOH and Germany Afia plays a pivotal role in strengthening the healthcare system. By consolidating data at both health facility and community levels, we can achieve better healthcare delivery and improve lives.

Through the use case example, we have explored the step-by-step process of pushing aggregate data and the challenges faced along the way. With future plans for automation and database restructuring, we are committed to continuously improving the integration process and ensuring the seamless flow of data between systems.

Thank you for taking the time to read this article. If you have any further questions or require more information, please feel free to reach out to us.

FAQ

Q1: What is the Chamini Afya project? The Chamini Afya project is a digital health initiative implemented in Zanzibar. It focuses on improving healthcare delivery by leveraging digital technology and the Community Health Toolkit (CHT). The project covers various use cases, including antenatal care, postnatal care, child immunization, early childhood development, ICCM, and COVID-19.

Q2: How does the integration process work? The integration process involves syncing data collected by CHVs and pushing it to DHIS2. The data is stored in a database, from which a script pulls and converts it into a suitable format. The data is then pushed to DHIS2 on a monthly basis. The process also includes creating organization units, data elements, and SQL queries, as well as mapping between DHIS2 and CHD.

Q3: What challenges were faced during the integration process? Some of the challenges faced during the integration process included sinking issues reported by CHVs, server connectivity issues, and changes in indicator or data element requirements. These challenges were addressed by implementing strategies such as pushing historical data to fill gaps, setting up server failure notifications, and adapting queries to accommodate changes.

Q4: What are the next steps in the integration process? The next steps in the integration process include establishing a notification system for errors and failures in scripts and restructuring the database to simplify queries. These improvements aim to enhance the efficiency and reliability of the integration process.

Q5: How does the Chamini Afya project benefit healthcare in Zanzibar? The Chamini Afya project brings significant benefits to healthcare in Zanzibar. By leveraging digital technology and the Community Health Toolkit, the project improves access to high-quality healthcare services. The project covers various use cases, enhancing antenatal and postnatal care, child immunization, early childhood development, ICCM, and COVID-19 management.