Medical Appointment Scheduling System

This project is a RESTful API for managing medical appointments across multiple countries using DynamoDB and Dynamoose. It includes endpoints for managing patients, doctors, and appointments, ensuring scalability and efficiency by leveraging NoSQL technology.

Features

• Multi-country appointment scheduling: Supports multiple countries for both doctors and patients.
• RESTful API: Endpoints for creating, reading, updating, and deleting appointments.
• DynamoDB with Dynamoose: Utilizes DynamoDB's NoSQL capabilities with Dynamoose as a schema modeler.
• Global Secondary Index (GSI): For efficient querying by countryId, doctorId, patientId.

Prerequisites

• Node.js (v18 or higher)
• Docker (if running DynamoDB locally)
• Serverless Framework (v3)
• AWS Services (Lambda, APIGateway, DynamoDB, AIM, SQS and SNS)
• Postman (for testing API requests)

Disign and Architecture

This project implements a serverless architecture using AWS Lambda, API Gateway, DynamoDB, Amazon SQS, and Amazon SNS, following a REST architectural style. The system is designed to manage medical appointments, patients, and doctors with support for multiple countries. To handle thousands of requests and prevent bottlenecks, Amazon SNS and SQS are integrated to provide an optimized asynchronous messaging mechanism for notifications and background task processing. Additionally, design patterns such as Singleton and dependency injection have been applied, along with a layered architecture, which contributes to the system's modularity and scalability.

    +------------------------+
    |  Amazon API Gateway     |
    |  (Gestiona las APIs)    |
    +------------------------+
                |
                v
    +------------------------+             +------------------------+
    | AWS Lambda Functions    |            |  AWS DynamoDB          |
    | (Lógica de negocio)     |<---------->|  (Base de Datos NoSQL) |
    +------------------------+             +------------------------+
                |
                v
    +------------------------+
    | Amazon SNS             |
    | (Notificaciones)    |
    +------------------------+
                |
                v
    +------------------------+
    | AWS Lambda (Consumer)  |
    | (Procesa mensajes SQS) |
    +------------------------+
                |
                v
    +--------------------------+            +----------------------+
    | Amazon SQS               |            |  Amazon CloudWatch   |
    | (Colas de Mensaje)       |            | (Monitoreo y Logs)   |
    +--------------------------+            +----------------------+

Processing by country

The country-based processing involves receiving appointment requests through a service, which are then sent to an SQS queue. An SQS consumer, implemented in a Lambda function, processes these messages and extracts the appointment information, allowing for the management of requests based on the associated country. This optimizes system load by handling large volumes of data asynchronously and at scale.

Scalability and performance

To optimize appointment processing by country, it's essential to address bottlenecks like high incoming request volumes, SQS processing delays, and database write performance. Solutions include implementing auto-scaling, batch processing, caching, and dead-letter queues to enhance efficiency. Additionally, using monitoring tools and multi-region deployment can improve visibility and reduce latency.

Security measures

To ensure security in appointment processing, it is essential to implement robust authentication and authorization, encrypt sensitive data in transit and at rest, and validate user inputs to prevent attacks. Additionally, audit logs should be maintained, regular code reviews conducted, and DDoS protection measures applied. Finally, ongoing staff training in security best practices is crucial to protect sensitive information.

Setup

1. Install Dependencies

npm install

2. Run DynamoDB Locally (Optional)

If you want to run DynamoDB locally using Docker, execute the following command:

docker run -d -p 4200:8000 amazon/dynamodb-local

3. Environment Configuration

Create a .env´ file based on .env.example and configure the following:

AWS_REGION=us-west-2
DYNAMODB_ENDPOINT=http://localhost:4200
AWS_ACCESS_KEY_ID=j4sb5n
AWS_SECRET_ACCESS_KEY=ja0e54
STAGE=dev

DYNAMODB_PATIENTS_TABLE=appointment-scheduler-dev-patients
DYNAMODB_DOCTORS_TABLE=appointment-scheduler-dev-doctors
DYNAMODB_APPOINTMENTS_TABLE=appointment-scheduler-dev-appointments
DYNAMODB_USERS_TABLE=appointment-scheduler-dev-users
DYNAMODB_COUNTRIES_TABLE=appointment-scheduler-dev-countries
# .env.development
SNS_TOPIC_ARN=arn:aws:sns:us-east-1:123456789012:dev-appointments-topic
SQS_QUEUE_URL=https://sqs.us-east-1.amazonaws.com/123456789012/dev-appointments-queue

4. Running the Application

To start the application, run:

npm run build

The API will be available at http://localhost:3000.

API Endpoints

1. Create a Country

POST /countries

Body (JSON)

{
    "countryId": "002",
    "name":  "CHILE",
    "code": "CL"
}

2. Create a Doctor

POST /doctors

Body (JSON)

{
  "doctorId": "doctor001",
  "name": "Dr. Lorea",
  "speciality": "Estomatolog",
  "countryId": "002",
  "availableTimes": ["Monday 10am-4pm", "Wednesday 1pm-5pm"]
}

3. Create a Patient

POST /patients

Body (JSON)

{
  "patientId": "0315",
  "name": "Jorge Moros ",
  "age": 85,
  "address": "123 Main St, Anytown, USA",
  "email": "johndoe@example.com",
  "phoneNumber": "+1-555-555-5555",
  "countryId": "001"
}

4. Create a Appointment

POST /appointments

Body (JSON)

{
  "appointmentId": "appointment124",
  "patientId": "0315",
  "doctorId": "doctor001",
  "appointmentDate": "2024-10-25T10:00:00Z",
  "countryId": "US",
  "state": "scheduled"
}

5. Get Doctor by countryId

POST /appointments/country/{countryId}/doctor/{doctorId}

Body (JSON)

{
  "appointmentId": "appointment124",
  "patientId": "0315",
  "doctorId": "doctor001",
  "appointmentDate": "2024-10-25T10:00:00Z",
  "countryId": "US",
  "state": "scheduled"
}

Key Points of the README:

• Introduction: Explains the project's purpose.
• Prerequisites: Lists necessary software like Node.js and Docker.
• Setup: Instructions for setting up the project locally.
• API Endpoints: Sample requests for creating doctors and appointments.
• Database Schema: Describes the Dynamoose schemas for Doctor and Appointment.
• Testing: How to test the API using Postman or cURL.
• Docker with DynamoDB: Instructions for running DynamoDB locally with Docker.

This README should provide clear guidance for setting up and using your medical appointment scheduling system.