Success Story
About the Client
Shifo is a Sweden-based non-profit on a mission to ensure no child suffers from preventable diseases. Using data-driven technology and transparent health information, Shifo collaborates with governments and partners to identify gaps in healthcare delivery and strengthen preventive services. Its solutions streamline child registration, empower parents with actionable insights, and support frontline health workers with efficient tools for care. By providing accurate, real-time data, Shifo enables evidence-based decision-making, enhances service quality, and drives initiatives that protect vulnerable children, ultimately building healthier communities and shaping a future where every child has access to essential healthcare.
Challenges and Requirements
Across the healthcare data collection industry, rapid growth in digital health records, connected devices, and regulatory reporting has placed unprecedented demands on legacy data platforms. Many organizations rely on architectures built for lower data volumes and simpler compliance, making them ill-equipped to handle today’s scale, real-time processing, and strict security standards.
As Shifo’s data volume and reporting requirements increased, the limitations of its existing Python-based platform became more apparent. To ensure scalability, performance, and secure data handling, the foundation sought to modernize its web application architecture and augment its internal team with experienced Python developers capable of delivering continuous technical improvements.
Shifo Foundation operated an in-house reporting platform responsible for process orchestration, KPI computation, analytics generation, and storing sensitive health data. The legacy Python stack faced architectural and functional constraints, impacting performance and user experience.
To support its modernization goals, the foundation partnered with Unthinkable, leveraging its Python expertise and healthcare domain knowledge.
Their key requirements included:
The application can handle increasing numbers of users patients, doctors, nurses, and administrators.
Protection of sensitive patient health information (PHI) in compliance with regulations.
Fast load times and smooth user experience, even under high traffic or during critical emergencies.
Easy-to-use interfaces for different user roles.
Efficient processing of real-time patient data, analytics, or notifications.
Support for growth in features, modules, or integrated systems over time.
The Solution
The modernization journey for Shifo Foundation’s reporting platform began with an in-depth evaluation of the existing application, its workflows, and data management processes. This phase focused on identifying technical limitations, uncovering scalability bottlenecks, and highlighting opportunities to improve performance, security, and automation across the platform. With rapidly growing volumes of health data and complex reporting requirements, the goal was to deliver a solution capable of handling high data throughput while providing accurate, actionable insights for decision-makers.
Based on these insights, our team at Unthinkable designed a comprehensive technical roadmap to modernize the platform and deliver improvements across multiple areas:
Optimized Python Code for Performance: Refactored Python code improved memory management, runtime efficiency, and processing of large datasets using generator functions and intelligent iteration patterns.
Efficient Data Handling Pipelines: Custom pipelines streamlined large-scale health data ingestion, ensuring accuracy and consistency for child health cards, vaccination tracking, and country-specific immunization schedules.
Automation of Reports and Workflows: Manual reporting processes were automated, reducing errors, accelerating timelines, and enabling timely sharing of Excel-based reports with state authorities for decision-making.
Integration of Modern Libraries and Tools: Tools such as pandas and NumPy for analytics, Redis for caching, RQ for asynchronous task management, and PostgreSQL as the database enhanced scalability, performance, and reliability.
The development followed an iterative, agile methodology, integrating Unthinkable’s Python developers directly into Shifo’s IT team to provide ongoing support, implement enhancements, and enable knowledge transfer.
Core Features of the Platform
Data Loading & Management: Automates transfer of paper-based health records into the platform, ensuring systematic, accurate, and efficient processing of large datasets.
Report Generation & Automation: Reduces administrative burden, accelerates reporting, and supports data-driven decision-making for health programs.
Performance & Scalability Enhancements: Optimized code and memory-efficient processes ensure smooth operation even with high-volume data.
Ongoing Development Support: Continuous technical expertise from Unthinkable allows Shifo to maintain and expand the platform as requirements evolve.
The Impact
Shifo Foundation’s technology upgrade transformed its platform into a scalable, high-performance solution, closing skill gaps and boosting impact across African healthcare, especially child health. Modernized data pipelines, optimized Python code, and automated workflows now deliver 99% accurate, WHO-approved data, reducing frontline administrative workloads by 60% and allowing health workers to focus on patient care.
Custom modules for child health cards, vaccination tracking, and country-specific reporting ensure efficient, consistent data management. The solution strengthens preventive care, improves decision-making, and protects children from preventable diseases.
60%
Reduction In Manual Administration Time
95%
Improvement In Data Quality
141,000+
Automated Follow-Ups
