AI Discharge Meal Plan Dispatch and Prepared Meal Delivery - Monthly Revenue 24k RMB
Workflow: Daily import of summary data of discharged patients from the previous day (images/PDF/structured text). AI extracts core
Key Fields
FIELD STAMPS🔧 Workflow
Daily import of summary data of discharged patients from the previous day (images/PDF/structured text). AI extracts core information such as diagnosis, surgery, and allergy history via OCR, matches clinical nutrition guidelines to generate 7-day customized meal plans, automatically splits them into processing instructions and dispatch lists synchronized to the prepared meal factory, which are then portioned and cold-chain delivered to patients. After meals, patients provide feedback on intake via a mini-program, and AI automatically iterates the next week's recipes and generates nutrition reports synchronized with the attending physician.
🛠 Setup Requirements
Requires basic large model API calling capabilities, and the ability to use low-code tools like n8n to build automated processes, completing full-link automation for discharge summary structuring, meal plan generation, dispatching, and reconciliation. The first step is to connect with 1 local prepared meal OEM factory with SC qualifications, confirming cold chain and food safety qualifications. The overall setup cycle is about 2 weeks, and the full process can be run through after 1 week of trial operation, with no complex code development required.
🧰 Toolchain
- 🔧 Claude API
- 🔧 n8n Low-code Automation Tool
- 🔧 Tongyi Qianwen OCR
- 🔧 WeChat Mini-Program Order Management System
- 🔧 WeChat Work Group Dispatch Robot
💰 Revenue
① Price difference in discharged patient meals (main revenue): Patients pay per order/time/quantity. Selling price 32 RMB minus cost 12 RMB = unit price difference 20 RMB × 40 orders/day × 26 days/month = monthly gross profit 20,800 RMB. After deducting platform commissions and delivery subsidies, net profit is approximately 18,000-24,000 RMB, contributing about 100% of that month's revenue (single model estimate, from merchant self-statements, unverified independently); ② Multi-hospital replication: After cooperating with 3 community hospitals, order volume doubles, and monthly revenue can exceed 30,000 RMB. The exact proportion of this expansion in total revenue is unclear (expansion figures from the same source); ③ Doctor recommendation commission: Doctors receive commissions based on recommended orders. There are no public data on the commission rate or recommended order volume, making the proportion unjudgeable; ④ Opportunity items: Post-operative nutrition monthly card subscription, where patients pay a monthly subscription fee. Currently, there is no basis for the monthly card pricing or the number of convertible patients.
💸 Cost
Large model API calls (including discharge summary structuring, meal plan generation, report output) cost about 800 RMB/month. Prepared meal packaging, label stickers, and cold chain insulation bags cost about 500 RMB/month. Third-party delivery subsidy is 2 RMB per order, resulting in a monthly delivery cost of about 2,080 RMB. There are no other fixed costs. Settlements with the prepared meal factory are based on a commission model, requiring no advance payment for goods.
⏱ Time Investment
About 3 hours invested daily, including 1 hour for handling abnormal orders and patient feedback, and 2 hours every Sunday for reconciling accounts with the prepared meal factory, updating the recipe database, and connecting with new partner hospitals; about 5 hours per day are invested during the trial operation period to run the process, and no more than 5 hours per week are needed after stabilization.
🚀 Getting Started
Step 1: Contact doctors in the rehabilitation departments of 2-3 local community hospitals and private rehabilitation institutions to discuss cooperation commissions and obtain authorization for the list of discharged patients; Step 2: Connect with a local prepared meal factory with SC qualifications, negotiate OEM pricing and delivery timeliness, provide 10 discharged patients with free 1-week trial meals, collect feedback to optimize recipe accuracy, and officially charge for promotion only after running through the full process.
🔑 Keys to Success
- ✅ The structuring accuracy of the discharge summary directly determines meal plan compliance and patient safety. A mapping database of diagnosis-contraindicated ingredients-nutritional needs must be established to avoid conflicts between meal plans and medical advice.
- ✅ The cooperation level of the prepared meal factory is more important than the price. Its food safety qualifications, cold chain delivery capabilities, and flexible production capacity must be confirmed to prevent substandard meals or delayed deliveries.
- ✅ The trust relationship with doctors in hospital rehabilitation departments is the core of customer acquisition. The conversion rate of patients recommended by doctors is more than 5 times that of public domain customer acquisition, and a clear doctor commission mechanism needs to be established.
- ✅ The iteration speed of patient meal feedback determines the repurchase rate. A 24-hour response channel needs to be established to quickly adjust plans for issues raised by patients such as food allergies and mismatched tastes.
⚠️ 风险
- ⚠️ Food safety liability risk: If quality issues arise with the meals, the individual as the service provider bears primary responsibility. Product liability insurance with a coverage of 500,000 RMB per order must be purchased, and a disclaimer agreement with clear rights and responsibilities must be signed with the OEM factory.
- ⚠️ Medical compliance risk: If the meal plan conflicts with the discharge medical advice and causes recurrence of the patient's condition, medical disputes may arise. A liability division agreement must be signed with partner hospitals to clarify that AI-generated meal plans are for dietary advice only and do not replace clinical diagnosis.
- ⚠️ Supply chain fluctuation risk: Increases in raw material prices for prepared meals or insufficient OEM production capacity may lead to increased meal costs or delayed deliveries. More than 2 backup OEM factories should be prepared, and ingredient procurement prices for 1 month should be locked in advance.
- ⚠️ Customer acquisition channel concentration risk: If cooperation with the hospital terminates, customer acquisition will be directly interrupted. Private domain customer acquisition channels such as short video platforms and rehabilitation communities should be expanded simultaneously to reduce dependence on a single channel.
📌 Real Cases
- 📌 Shenzhen launched the government-led 'Smart Meal Recipe' in November 2025, covering discharged patients from 3 tertiary Grade-A hospitals, with a monthly delivery volume of over 12,000 portions, validating the market demand for post-discharge meal preparation.
- 📌 Shanghai's Yangpu District rolled out the AI Nutrition Butler project in March 2026. After discharged patients bound the service, AI generated personalized dietary plans based on discharge summaries, paired with prepared meal delivery. During the trial operation, patients' dietary adherence rate increased from 32% to 78%.
- 📌 Hao Huoshi launched a hospital nutrition and dietary system in 2026, completing the full-link service from clinical medical advice extraction and AI recipe generation to prepared meal delivery. It has been connected to 17 domestic hospitals, with monthly revenue exceeding 800,000 RMB.