Plaiatech
Replacing paper intake and hallway assessments with AI-powered pre-surgical screening
The Setup
Before any surgery, an anesthesiologist needs to evaluate the patient — airway anatomy, cardiac history, current medications, allergies, prior reactions to anesthesia. It's a detailed clinical assessment that determines how safe it is to proceed.
The problem is timing. In most clinics, this evaluation happens the day of surgery or requires a separate in-person visit days before. If something unexpected shows up — a drug interaction, an uncontrolled condition — the surgery gets postponed. Same-day cancellations waste operating room time, stress patients, and cost the clinic money.
A professional with experience in the field approached me to fix this: move the entire pre-anesthesia evaluation to the patient's phone. No app download, no account creation — just a link that gets them through a clinically valid assessment from home.
The Constraints
Three constraints shaped every technical decision:
Clinical accuracy is non-negotiable
The system scores patients on established medical scales used in clinical practice. These aren't suggestions; they're the same standards anesthesiologists use in person. Getting them wrong means patient safety is compromised.
Patients aren't tech-savvy
The typical user is a 65-year-old facing surgery, not a digital native. They get an SMS link, tap it, and need to complete everything in their phone browser. No app store, no login, no second chances to figure out confusing UI.
Every clinic does it differently
An orthopedic clinic asks different questions than a cardiac surgery center. Each specialty has its own protocols, and clinics need to customize intake flows without calling a developer every time.
What I Built
Each piece of the system maps back to a constraint. Here's how the solution came together.
Solving for: patients aren't tech-savvy
Patient Experience
The patient receives an SMS with a link. No app to download, no account to create. They tap the link and land on an adaptive questionnaire organized into blocks — each screen presents multiple related questions, with dependent questions that show or hide based on previous answers. The entire experience is optimized for a phone screen — large touch targets, clear language, and a logical flow that guides patients through sections like medical history, medications, and document uploads.
Cardiovascular
Does the patient have any cardiovascular history?
Solving for: clinical accuracy is non-negotiable
AI-Powered Clinical Assessment
As the patient works through the questionnaire, each answer is tagged with a specific clinical score. The system collects responses across many dimensions — medical history, current conditions, previous surgeries, and more — and an algorithm evaluates all answers together to produce a clinical risk assessment. One input among many is a photo analyzed by a computer vision model to determine a clinical classification relevant to the procedure.
The algorithm combines all these scored inputs to compute an overall risk classification. The anesthesiologist receives a pre-filled risk assessment instead of starting from scratch — with every contributing factor traceable back to a specific patient answer.
Solving for: every clinic does it differently
Questionnaire Builder
Each clinic configures its own intake flow through a visual builder. Questions can be reordered, branching logic connects blocks so different patient profiles trigger different follow-up paths — and none of it requires a developer. A cardiac clinic can add deep questions about pacemakers while an orthopedic clinic focuses on joint replacement history.
Medical Staff Dashboard
Everything consolidates into a single dashboard for the anesthesiologist. Patient responses, AI-generated risk scores, parsed medications, uploaded documents — all reviewed before the patient ever arrives. The system auto-generates a structured pre-anesthesia report that would have taken 30 minutes to compile manually.
| Patient | Date | Status |
|---|---|---|
| María García | 2024-11-18 | Completed |
| Carlos López | 2024-11-19 | In Progress |
| Ana Rodríguez | 2024-11-20 | Pending |
| Jorge Martínez | 2024-11-20 | Completed |
Architecture
Fully serverless. Patient requests hit API Gateway, which routes to Lambda functions handling questionnaire logic, AI assessment, and document processing. DynamoDB stores patient data with strict tenant isolation — shared DynamoDB tables use clinic-scoped partition keys, with access control enforced at the API layer. S3 handles document storage with pre-signed URLs for secure upload and retrieval.
Results & Impact
The MVP has been delivered and is entering its first round of real-world testing with clinics. The next iteration will be shaped by how medical staff and patients respond to the system in practice.
Tech Stack
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