Approximately six out of every 10 countries lack adequate systems for counting births and deaths. Every misclassified or unrecorded [maternal or neonatal] death is a lost opportunity to ensure other mothers and babies don’t die in the same way. Lwala Community Alliance is on a mission to build the capacity of rural communities to advance their own comprehensive wellbeing.
Lwala works to achieve its goals by empowering Community Health Workers (CHWs) with digital data collection tools to track at-risk patients, better understand their needs, and treat them faster. Every month, Lwala’s CHWs log thousands of patient interactions on the CommCare platform, the most widely used digital case management platform for frontline health workers in the world, and many types of inconsistent or problematic data can find their way into mission-critical datasets.
Lwala has partnered with us to surface inconsistent or problematic data and improve its data quality, so that all frontline health workers can make trusted, data-driven decisions to support Lwala’s “all-out effort” to achieve health for all.
Our team of volunteer technical experts will develop and deploy a machine-scale data integrity solution that will help automatically find, categorize, and summarize errors and help Lwala benchmark the data quality issues and develop remediation strategies.
This solution will promote responsible data collection and result in increased confidence in CHW generated data, enabling community health system stakeholders to make decisions backed by trusted data. Health workers will be able to optimize their care delivery and provide the right care at the right time -- which are the most significant actions CHWs can take to reduce preventable maternal and child deaths.
High quality data is vital when it comes to amplifying the impact of community health worker programs,” said Julia Higgins, Lwala’s Monitoring & Evaluation Consultant. “By building a tool that will assist Lwala in its efforts to routinely monitor and improve the quality of our programmatic data, DataKind is supporting our organizational transition to a more effective and sustainable digital health system. Being able to identify and resolve data issues in a timely manner will help us better respond to the needs of our frontline workers and will enable our staff to center data-driven decision making in their work, which will ultimately lead to better service provision.
When it comes to health, better data can be a matter of life and death. We’re thrilled to kick off our partnership with Lwala to help accelerate its mission and improve their data quality, so that frontline health providers can offer timely and appropriate care.
Lwala DataCorps Team: John McCambridge (Data Ambassador), Anastasia Golubeva (Project Manager), Ben Crittenden (Data Engineer), Roberta Evangelista (Data Engineer) Lorenzo Rubio (Data Engineer), Alexandra Wörner (Data Engineer)
Frontline Health Systems Impact Practice: We’re honored to work with Lwala Community Alliance under our Frontline Health Systems Impact Practice. We’ve evolved our long-term projects into a program to drive sector-wide change called Impact Practices. The first of its kind, our Impact Practices position DataKind to meet the needs of multiple organizations within a sector, which give our solutions a pathway to scale and support systems change efforts.
Image above courtesy of Lwala Community Alliance.
Support for this project was provided by the Johnson & Johnson Foundation.
- How Data Empowers Health Workers - and Powers Health Systems
- Engineering Scalable Data Quality Assessments for Frontline Health with Medic
- Strengthening Frontline Health Systems with Data Science & AI: Updates From Our First Cohort of Projects
- Using Data Science & AI in the Service of Community Health Workers
- Creating a Systems Change Approach to Data Science & AI Solutions
If you want to see health systems transformed, join us in advancing the use of data science and AI to support causes that can help make the world a better place.