Simplifying Healthcare through Digital Technology: d3's Integration Process

Table of Contents

• Introduction
• Vision and Mission of d3
• Overview of the Chamini Afya Project
• Use Cases Covered by the Project
• Integration Process Overview
• Why the Integration with Germany Afia?
• Use Case: Pushing Aggregate Data for Under-five Children
• Step 1: Creating Organization Units, Data Elements, and Category Option Combination
• Step 2: Creating SQL Queries to Fetch Data Values
• Step 3: Mapping between DHIS2 and Chd
• Step 4: Converting Data into Suitable Format
• Challenges Faced during the Integration
• Next Steps and Future Improvements

Integration Process: Simplifying Healthcare through Digital Technology

In this article, we will explore the integration process of d3, an organization committed to improving lives by strengthening health systems through digital technology. We will delve into their vision and mission, as well as the specific project they are currently focusing on. Additionally, we will discuss the challenges they faced during the integration process and their plans for future improvements. So, let's get started!

🔹 Introduction: Before we dive into the integration process, let's take a moment to understand the vision and mission of d3. They envision a future where everyone has access to high-quality healthcare. Their mission is to achieve this vision by leveraging digital technology to strengthen health systems. With this overarching goal in mind, they have undertaken various initiatives, with the Chamini Afya project being the main focus.

🔹 Vision and Mission of d3: The vision of d3 is to ensure that every individual has access to high-quality healthcare. They firmly believe that improved healthcare can significantly improve lives and contribute to the overall well-being of communities. To achieve this vision, their mission is to strengthen health systems through the strategic use of digital technology. By leveraging the power of technology, they strive to optimize healthcare delivery and enhance patient outcomes.

🔹 Overview of the Chamini Afya Project: The Chamini Afya project is a cornerstone of d3's efforts to improve healthcare outcomes. Chamini Afya, a Swahili phrase meaning "community is health," is powered by the Community Health Toolkit (CHT). The project has been successfully deployed in Zanzibar, covering 50% of the population in 11 districts. Its primary objective is to provide access to essential healthcare services, such as ANC (Antenatal Care), PNT (Postnatal Care), child immunization, early childhood development (ICCM), and COVID-19 response.

🔹 Use Cases Covered by the Project: The Chamini Afya project encompasses various critical use cases that address the healthcare needs of the community. These include ANC (Antenatal Care), PNT (Postnatal Care), child immunization, early childhood development (ICCM), and COVID-19 response. By integrating digital technology with these use cases, d3 is able to enhance the efficiency and effectiveness of healthcare delivery. The project aims to empower community health workers (CHVs) to deliver comprehensive healthcare services and ensure the well-being of individuals.

🔹 Integration Process Overview: The integration process between d3 and Germany Afia plays a pivotal role in achieving the project's objectives. The Ministry of Health (MOH) collects data at the health facility level, while Germany Afia collects data at the community level. The integration aims to consolidate data at both levels to facilitate better healthcare delivery. By combining and analyzing data from different sources, the MOH can gain in-depth insights into the community's health status and make data-driven decisions.

🔹 Why the Integration with Germany Afia? The integration between d3 and Germany Afia was initiated to address the need for comprehensive and consolidated healthcare data. The MOH understood the importance of integrating data collected at both the health facility and community levels to gain a holistic view of healthcare delivery. By merging data from Germany Afia into the MOH's existing systems, they could streamline data management and utilize the insights gained to improve health services and outcomes.

🔹 Use Case: Pushing Aggregate Data for Under-five Children: To better understand the integration process, let's consider a specific use case. Imagine the goal is to push aggregated data about the number of under-five children visited by CHVs, categorized by sex. The aim is to push this data at the Shahia level on a monthly basis. The process involves collecting data from CHVs, syncing the data, converting it into a suitable format, and pushing it to DHIS2 (District Health Information System 2) using a cron job.

🔹 Step 1: Creating Organization Units, Data Elements, and Category Option Combination: Before pushing the data, it is essential to create the necessary organization units, data elements, and category option combinations in DHIS2. These entities provide the required structure and categorization for the data to be pushed. By mapping the data element names with their corresponding IDs, d3 ensures seamless data transfer and synchronization between the systems.

🔹 Step 2: Creating SQL Queries to Fetch Data Values: Once the organizational framework is in place, the next step involves creating SQL queries to fetch the required data values. These queries are designed to extract specific information, such as the number of under-five children enrolled by CHVs. The queries also include filters based on the Shahia, district, and gender to segment the data accurately.

🔹 Step 3: Mapping between DHIS2 and Chd: To establish a connection between DHIS2 and the data collected through the Chamini Afya project, mapping between the two systems is required. This mapping ensures that the corresponding data element names, IDs, and category option combinations are aligned. By effectively mapping the entities, the data integration process becomes seamless and efficient.

🔹 Step 4: Converting Data into Suitable Format: Once the data is fetched and mapped, it needs to be converted into a format suitable for pushing to DHIS2. This conversion process is facilitated by a script developed by d3. The script transforms the data into a data value set file, which includes essential information such as the data element ID, period, organization unit ID, category option combination, and corresponding value. This final format ensures compatibility with DHIS2.

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