The Digital Health Agency has floated tenders for what it’s calling Taifa Care, an AI system meant to track pregnancy, birth, and child health from the first antenatal visit through to a child’s immunization record.
Taifa Care combines several services under one platform:
- Care before and after birth
- Family planning
- Immunization tracking
- Health monitoring for teenagers
- Emergency care for mothers
- Tracking of maternal deaths
- An AI-managed blood bank
- Data quality checks
- A registry for births and deaths that connects to disease tracking and civil registration
That is not one app. It consists of six interconnected systems that share a single brand name, and this distinction is important for anyone assessing its potential effectiveness.
What It’s Trying To Do
The pitch proposes following a woman from pregnancy through delivery and her child’s early years.
It aims to identify missed antenatal visits and warning signs before they become emergencies, speed up referrals and blood matching, and ensure births and deaths are recorded by both health authorities and the civil registry.
This could help prevent more children from growing up without a legal identity. On paper, it addresses a real gap.
Kenya isn’t building the Digital Health Agency from nothing. The Digital Health Act of 2023 already created the Digital Health Agency, a national integrated health-information system, and county-level health data banks.
The Data Protection Act 2019 and 2025 health information regulations set out requirements for encryption, role-based access, 48-hour breach notifications, and correcting inaccurate health data within 72 hours.
That gives a system of this size a strong legal framework, and it is more developed than what many countries have in place for similar systems.
Where the Risk Sits
The privacy concern here isn’t just about hackers. Although hacking is part of the risk, the bigger issue is scale.
A single, well-managed record could be safer than the current mix of paper registers, spreadsheets, and WhatsApp groups spread across different facilities, as long as access is logged and the data is encrypted.
But bringing together pregnancy records, adolescent health information, fertility data, and family details also creates a single point of failure.
If the system is misused, the impact could be widespread, whether through political targeting, discrimination by insurers, or abuse by someone with authorised access.
There is also the quieter risk of function creep. The system is intended to support research, planning, and disease surveillance, all legitimate purposes. Still, those uses could gradually expand into commercial profiling or punitive enforcement unless clear limits are actively enforced.
Since the platform connects a woman’s identity, her newborn’s identity, and a civil registration event, even one incorrect record could follow a family across multiple systems.
Kenya’s regulations provide a process for correcting such errors, but access to healthcare should not depend on having a perfect match with a national ID.
What AI Can and Cannot Fix
The real value of AI here is coordination, not diagnosis. It can flag a missed antenatal visit, forecast blood demand, identify duplicate records, and help nurses decide which cases need attention first.
READ: Kenya Pushes Clinical-Level Oversight for AI Tools in Healthcare
However, it cannot create an ambulance, provide a skilled birth attendant, or fix an unreliable blood supply. An algorithm can identify a high-risk pregnancy, but it cannot guarantee a safe referral.
Poorly labeled data can also introduce bias based on factors such as county, ethnicity, or disability, affecting who gets flagged and who does not.
What Other Countries Learned
| Country/Project | What It Did | What Happened |
| Rwanda, RapidSMS | Connected community health workers, ambulances and facilities by mobile phone, scaled nationally | No statistically significant gain in antenatal care, facility delivery or vaccination rates, largely because coverage was already high before the system arrived |
| India, RCH Portal | Tracks women and children by name across the reproductive lifecycle, with alerts to frontline workers | Closest architectural blueprint for Taifa Care, though official descriptions aren’t independent proof of impact on mortality |
| South Africa, MomConnect | National messaging service sending pregnancy and postpartum information, with a feedback channel back to mothers | Strong reach and engagement, but also registration failures and thin evidence linking messages to actual changes in care-seeking |
None of these examples prove that digitizing records reduces maternal deaths on its own.
The Real Test
The lesson from all three is the same, and it is one Kenya should apply to Taifa Care: data only matters when it leads to a properly staffed and funded response.
A dashboard that flags a missed visit is useless if there is no nurse to follow up, no ambulance to send, or no blood available for a transfusion.
If Taifa Care launches with a clear, published record of how data flows, human review of every AI alert, and independent evaluation of outcomes rather than just uptake, it could improve how Kenya tracks and responds to maternal and child health needs.
Without those safeguards, it risks becoming an expensive way to collect some of the country’s most sensitive data without making anyone safer.
