Accelerator Use Case
Using WhatsApp as core patient engagement channel to improve access and care delivery
Type:
Health tech start-up
Program:
Turn.io Accelerator
Focus:
Patient engagement
Location:
Nigeria/ Middle East
Serving 330K+ patients across 100+ clinics in Africa and the Middle East
A key barrier to improved outcomes and efficiency was missed appointments, with only 49% of patients attending booked visits.
Work through the Accelerator focused on building end-to-end patient visit support on WhatsApp to improve attendance, retention, user experience and enable improved data quality.
Helium built an Appointment Manager on WhatsApp using Turn.io and saw strong adoption. Specifically, In one month, the system drove over 5,500 new engagements and interactions linked to appointments. Currently, 38% of daily appointments are booked through WhatsApp.
One in three patients confirmed their appointments through chat, 18.6 % rescheduled in advance, thus improving retention. Moreover, 11.5% proactively cancelled before the visit, reducing no-shows. 62% shared cancellation reasons, improving operational insight.
Work through the Accelerator focused on building end-to-end patient visit support on WhatsApp to improve attendance, retention, user experience and enable improved data quality.
Helium built an Appointment Manager on WhatsApp using Turn.io and saw strong adoption. Specifically, In one month, the system drove over 5,500 new engagements and interactions linked to appointments. Currently, 38% of daily appointments are booked through WhatsApp.
One in three patients confirmed their appointments through chat, 18.6 % rescheduled in advance, thus improving retention. Moreover, 11.5% proactively cancelled before the visit, reducing no-shows. 62% shared cancellation reasons, improving operational insight.
Impact
330K+
Patients
served
38%
Appointments via
WhatsApp
49%
Attendance
baseline
Demo:
Watch Helium Health in action
Post-visit engagement also improved: 30% of patients shared attendance status after appointments and 6% were rescheduled after a no-show.
Helium also launched a Book a Doctor via WhatsApp flow. 81% percent of users showed initial interest, 73% selected a speciality, and 31% completed booking directly in chat.
To address uncertainty about clinical care pathways, the team built a WhatsApp symptom checker AI bot that interprets symptoms, recommends the most appropriate specialty healthcare provider, and supports booking. 94% of users who engaged with the bot received guidance and proceeded to book.
These services integrate where possible with EMRs and also work in standalone settings, allowing use across different levels of facility digital maturity.
Next steps include expanding AI-driven follow-ups after consultations, medication adherence support, and deeper automation of registration and booking inside WhatsApp, further reducing clinical workload while improving continuity of care.
These services integrate where possible with EMRs and also work in standalone settings, allowing use across different levels of facility digital maturity.
Next steps include expanding AI-driven follow-ups after consultations, medication adherence support, and deeper automation of registration and booking inside WhatsApp, further reducing clinical workload while improving continuity of care.
LLM Models
used
Chat GPT 4.1 Mini
AI
Built through the Chat for Impact Accelerator
This project was developed through the Chat for Impact Accelerator, a global programme supporting organisations to design, test, and scale impactful conversational services on WhatsApp.
Through the programme, teams work closely with product and technical experts to prototype, launch, and iterate on AI-powered chat solutions that expand access to health, education, and essential services for communities around the world.
Through the programme, teams work closely with product and technical experts to prototype, launch, and iterate on AI-powered chat solutions that expand access to health, education, and essential services for communities around the world.
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