Stop Stockouts: Custom AI for Urgent Care Inventory
Custom AI solutions provide real-time inventory tracking tied directly to patient usage data. They also generate predictive reordering alerts based on your clinic's specific consumption patterns.
The system's complexity depends on its connections to your Electronic Health Record (EHR) and the number of suppliers you manage. A clinic with a modern EHR API and under 500 SKUs is a straightforward build. One using a legacy system or requiring complex purchasing rules across multiple vendors needs more integration work.
We built an inventory system for a 3-location urgent care group with 25 staff. The build took 4 weeks, and within two months, they reduced stockouts of critical supplies by 90%. The system cut time spent on manual inventory counts from 10 hours per week down to just 1 hour for approvals.
What Problem Does This Solve?
Most clinics start with a general inventory app like Sortly. This requires a nurse to manually scan a barcode every time a box of gloves or a vial is used. During a patient surge, scans are inevitably missed. The system shows 5 boxes in stock, but the shelf is empty, leading to a critical supply stockout during a procedure.
A practice management system's built-in module seems like an improvement, but it has different flaws. It might track items tied to a billable CPT code but completely misses non-billable supplies like gauze or alcohol swabs. Its reordering logic is rigid, often just a simple rule like 'reorder when stock hits 10 units'. This ignores seasonal demand, like the winter spike in flu tests, causing over-stocking in slow months and under-stocking in busy ones.
These off-the-shelf tools fail because they are fundamentally disconnected from real-time clinical activity. They depend on flawed manual entry or simplistic billing triggers. Neither can accurately model the complex, fast-paced consumption patterns of an urgent care environment, making them unreliable for preventing costly stockouts.
How Does It Work?
We start by connecting directly to your Electronic Health Record (EHR) via its API. For a previous urgent care client, we used the Athenahealth API to pull 12 months of anonymized procedural data. We map specific CPT codes to the bill-of-materials for that procedure, creating a reliable, historical dataset of exactly what was consumed and when.
Next, we build a consumption forecasting model in Python using the Prophet library to analyze time-series data. This model learns your clinic's unique seasonal patterns for each of your 300+ tracked inventory items, predicting demand 30 days into the future. The forecast runs automatically every night on an AWS Lambda function, triggered by a CloudWatch event.
We build a lightweight FastAPI service to handle the core logic. It compares the 30-day forecast against current inventory levels, which are stored in a Supabase database. When predicted consumption will breach the safety stock level (calculated based on supplier lead time plus a 72-hour buffer), the service generates a draft purchase order. We use Pydantic to ensure all PO data is correctly structured before it's sent for approval.
The entire system is deployed on Vercel and AWS, with operating costs under $50 per month for a clinic seeing over 2,500 patients monthly. We implement structured logging with structlog and configure Slack alerts for critical events, like a failed API call to a supplier or a model error rate exceeding 5%. This monitoring ensures the system runs reliably without constant human oversight.
What Are the Key Benefits?
From Guesswork to a 30-Day Forecast
The system analyzes EHR data to predict supply needs 30 days out, accounting for seasonal demand spikes like flu season.
One Build, Zero Per-User Fees
A single project cost with minimal monthly hosting on AWS. No recurring seat licenses that grow as you add staff or locations.
You Own the Code, Your Asset
You get the complete Python source code in your own GitHub repository and a technical runbook. The system is an asset you own.
Alerts Before You Run Out
Slack notifications trigger when inventory drops below a dynamic safety threshold, giving you a 72-hour buffer before a stockout.
Connects Directly to Your EHR
Direct API integration with systems like Athenahealth or DrChrono means consumption is logged automatically. No manual barcode scanning required.
What Does the Process Look Like?
System & Data Audit (Week 1)
You provide read-only API access to your EHR and a list of current suppliers. We deliver a data map confirming we can track consumption.
Forecasting Model Build (Week 2)
We build and validate the consumption model on your historical data. You receive a report showing forecast accuracy for your top 20 supplies.
API & Interface Deployment (Week 3)
We deploy the system and connect it to your supplier ordering portals. Your clinic manager gets a simple dashboard to approve draft purchase orders.
Monitoring and Handoff (Weeks 4-8)
We monitor the system for 30 days post-launch to tune alert thresholds. You receive the final source code and maintenance runbook.
Frequently Asked Questions
- How much does a system like this cost?
- Pricing depends on the number of inventory SKUs and the quality of your EHR's API. A single-location clinic with a modern EHR like Athenahealth is a 3-4 week build. A multi-location clinic using a legacy system with no API access requires more custom work. We provide a fixed-price quote after the initial discovery call at cal.com/syntora/discover.
- What happens if our EHR API goes down?
- The system is designed for graceful failure. If the EHR API is unavailable, the forecasting model uses the last known successful data pull. The ordering logic will continue to function based on the previous day's forecast. You receive a Slack alert about the connection failure so your team can investigate the EHR outage.
- How is this different from using a general inventory tool like Fishbowl?
- Fishbowl is a generic warehouse management tool. It requires constant manual updates and can't automatically link patient procedures to supply consumption. Our system is purpose-built for healthcare clinics. It uses your EHR data to automate consumption tracking, which is the most error-prone part of medical inventory management.
- Is this system HIPAA-compliant?
- Yes. All processing happens in a HIPAA-compliant AWS environment. We never store Protected Health Information (PHI) in our application database. The system only analyzes aggregated, de-identified procedure counts to forecast supply usage. We sign a Business Associate Agreement (BAA) for every healthcare engagement.
- Can it handle multiple suppliers for the same item?
- Absolutely. The system can store primary and secondary suppliers for each SKU. If a PO to the primary supplier fails or they are out of stock, it can automatically generate a draft PO for the secondary supplier. This logic is configured during the initial build based on your procurement rules.
- What kind of training is required for my staff?
- Minimal. The system is designed to run in the background. The only human touchpoint is for your office manager to approve draft purchase orders from a simple web dashboard. There is no new software for nurses or medical assistants to learn, and no change to their clinical workflow.
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