Finalist
Future Health Challenge: Building Anticipatory Health Systems through Population Sensing

ThinkMD

Team Leader
Ben Russell
Delivering better frontline care and real-time intelligence for public health action
What is the name of your organization?
ThinkMD
What is the name of your solution?
ThinkMD
Provide a one-line summary or tagline for your solution.
Delivering better frontline care and real-time intelligence for public health action
In what city, town, or region is your solution team headquartered?
Sydney NSW, Australia
In what country is your solution team headquartered?
Australia
What type of organization is your solution team?
For-profit, including B-Corp or similar models
Film your elevator pitch.
What specific problem are you solving?
There is a projected global shortage of 15 million healthcare workers. In many low-resource settings, care is delivered by nurses, pharmacists, and community health workers rather than medical doctors. In some regions, doctor-to-population ratios fall to 1:10,000, far below the WHO benchmark of 1:1,000. In many low- and middle-income countries, the majority of the population relies on these frontline providers as their primary access to care. Without specialist support, frontline providers must diagnose and treat patients using limited tools. Diagnostic accuracy in low-resource settings can be up to 50 percent lower than in high-income systems. As a result, illness is often identified late and treated imprecisely. More than 8,000 children die each day from preventable causes, and maternal mortality remains over 40 times higher in low-income countries than in high-income countries. Ministries of health cannot see emerging disease patterns or rising risks until they escalate into outbreaks or system strain. Most public health surveillance relies on delayed reporting rather than real-time signals from care delivery. Frontline clinical encounters generate little usable data for population health monitoring.
What is your solution?
Product demo: https://www.loom.com/share/d885cd97fb2e492a9b8567c1e4c022dd ThinkMD is a digital, device-agnostic, offline capable clinical decision support platform that helps frontline health workers deliver safe, medical-doctor-grade care in low-resource settings. The platform translates complex clinical knowledge into guided digital workflows. Nurses, teachers, and community volunteers are guided through structured assessments covering more than 260 conditions, supporting more accurate diagnoses. The system filters symptoms through multiple clinical pathways. It tests for overlapping conditions and flags meaningful risks, helping prevent missed or incorrect diagnoses and ensuring that serious conditions are identified early. Each assessment generates triage and treatment guidance. The software works fully offline, allowing it to function in areas without reliable connectivity. ThinkMD’s clinical logic is grounded in WHO and IMNCI standards, and localised against country-specific diagnostic and treatment protocols. This ensures standardisation of care against best practice guidelines. ThinkMD uses an offline-first mobile platform powered by an on-device clinical engine. Each encounter generates structured data. These signals create an early warning layer for disease risks, showing trends at local and system levels. Decision-makers can identify unusual patterns, investigate areas of concern, and direct resources appropriately.
Who does your solution serve, and in what ways will the solution impact their lives?
ThinkMD serves frontline health workers and the patients who rely on them in low-resource and last mile care delivery settings. In many of the communities where we operate, care is delivered not by medical doctors but by nurses, pharmacists, community health workers, and teachers. These providers often work with limited training, supervision, and diagnostic support. As a result, illness is frequently missed, identified late, or treated inconsistently. Our primary beneficiaries are the patients in these settings, including children and families who depend on frontline providers as their main point of care. ThinkMD supports these workers with step-by-step clinical guidance during consultations. This helps them assess symptoms more consistently, identify serious conditions earlier, and determine when escalation or referral is needed. For patients, this translates into: earlier detection of severe illness, more appropriate treatment decisions, appropriate, timely referral and more consistent care across providers. As the system collects structured data, the platform also enables health system managers to identify patterns in symptoms and service demand. This improves resource allocation and helps detect emerging risks before they escalate.
Solution Team:
Ben Russell
Ben Russell
Commercial Analyst
Jacqueline Rabec
Jacqueline Rabec
Dr