Receiving a patient for the first time in a clinic requires significant time and effort from medical staff and can often be a scattered, chaotic, and overwhelming experience for patients. As a result, critical patient information is often collected incompletely or inconsistently.
For clinicians to treat patients holistically, they need a structured, accessible, and comprehensive view of the patient’s medical background — including insurance information, basic measurements (e.g., height, weight), lifestyle, family history, chronic conditions, prior lab results, wearable health data, medication plans, vaccination certificates, and more.
Your goal is to, on the one hand, transform the patient intake experience: make it fast, simple and all-encompassing. On the other hand, empower medical staff with a clear, compact, actionable and ‘full picture’ to treat them better and faster.
For avi, the patient intake workflow is one of the most important, yet underserved steps in the patient journey that takes place in a scattered manner at the moment. Some data collection happens in the booking flow digitally (e.g. insurance information, chronic conditions), some is provided by the patient with a questionnaire (e.g. lifestyle, family history), some information is collected directly at the practice by the doctor, some is handed to a nurse to digitalize (e.g. lab results). And currently a holistic summary or cockpit for patient information doesn’t exist. Information is as scattered as it is when collecting it.
Primary users of the solution are healthcare providers, including doctors and medical assistants, who need fast and reliable access to complete patient histories before starting diagnosis and treatment. The job to be done is to automate and streamline patient onboarding, ensuring that all relevant information (demographics, past medical history, medication lists, vaccination status, wearable health data, etc.) is collected and structured in a clear and accessible way — with the option to use voice input and various import methods (e.g., QR code scans, insurance card scans, wearable sync, OCR for documents).
In the real world, clinics, hospitals, and healthcare systems would invest in such a solution to:
- Improve clinical efficiency and reduce administrative workload
- Minimize medical errors caused by incomplete information
- Enhance patient satisfaction by offering a more seamless, less repetitive admission experience
- Support accessibility for diverse patient groups (e.g., elderly, visually impaired)
Potential customers include hospitals, outpatient clinics, insurance companies (interested in quality of care improvements), and digital health platforms looking to integrate smarter admission modules into their services.
We will provide you with the following data points:
- Vaccination Cards (please also bring yours if possible)
- Access to Demo Accounts on Apple Health, Withings and Omron
- Blood pressure and EKG devices, smart watches, Continuous Blood Glucose monitors
- Sample Lab reports and Doctor letters (paper copies, like in real life)
- Special program eligibility criteria that patients can sign up for (Disease Management Program & Hausarztprogramm)
Additionally, you will receive:
- Access to own project in GCP
- You can use services from any region, but try to use europe-west3 or europe-west4 wherever possible
- The project will have access to Gemini (all models) and VertexAI
- You can request your project with this Google form: https://forms.gle/sC18uA5SZPAQyfwf7
- Access to a handful of measurement devices and wearables (Blood Pressure, ECG, Blood Sugar)
- Gematik Specs (available publicly under https://github.com/gematik/ref-OpenHealthCardKit)
- KBV Specs (available publicly under https://www.kbv.de/html/mio.php)
Our core-stack (where we can help best):
- Expo / React Native (TypeScript): -- Recommended Starter: https://github.com/avimedical/avi-react-native-starter
- Django / Flask (Python)
- Quarkus (Java EE)
- Kubernetes
- PostgreSQL
- Redis
| Criteria | Description |
|---|---|
| Innovation | How creative and novel is the team's approach? |
| User experience (patient & staff) | How effectively does it solve the problem for the users? |
| Diversity of data collected and presented | How diverse is the patient information collected (in terms of types and formats) and presented to the doctor |
| Data quality | How well is the collected data structured? |
| Technical implementation | How well does the technology work? (speed, performance, reliability) |
| Presentation & storytelling | How clear and engaging is the demo/presentation? |
Keke, Patrick, Nils, and Pedro will be glad to answer your questions during the Deep Dive. We’ll also be available on Discord.