Scaling Up Simprints: Mobile Biometrics for MNCH Care in Bangladesh

Organization: 
SimPrints Technology Limited
Organization Location: 
Cambridge, United Kingdom
Project Location: 
Bangladesh

Reliable patient identification is a huge obstacle to the delivery of MNCH services by health workers. Patient names overlap or are spelled in multiple ways, and the poorest often lack formal identification like birth certificates. This leads to duplicate records, misidentification, and weak continuity of care essential to MNCH care. As mothers ‘fall through the cracks’ and lack follow-up, they miss critical care for themselves and their children during the vulnerable perinatal period, leading to a sixfold increased chance of mortality (Yego et al., 2014). With support from a Saving Lives at Birth Round IV Seed Grant, Simprints collected over 135,000 fingerprint images to develop a mobile biometric scanner that is 228% more accurate and four times cheaper than existing tools. With the touch of a finger, frontline community health workers (CHWs) can pull up patient records, and managers can verify MNCH services have been delivered. The technology is open-source, low-cost, and seamlessly plugs into existing mobile health tools like Dimagi, ODK, Magpi, and Medic Mobile. Piloting this technology for 22,000 patients with BRAC in Dhaka’s slums showed an 83% increase in CHWs reaching ANC visit targets and a 33.7% decrease in complications (such as severe bleeding, jaundice, or miscarriage). In partnership with BRAC, Simprints proposes to scale up this solution to improve MNCH care for 2.56M expectant mothers and newborns across Bangladesh over 3 years. BRAC has committed $850k to scale and sustain the project after the grant period.

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