B. As a healthcare provider, I want to capture and maintain patient details like name, date of birth, contact information, address, and other relevant demographics in the EHR system so that I can quickly access and verify essential patient information during medical encounters.

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Frontend Acceptance Criteria:

User Interface for Data Entry:

Field Arrangement and Categorization:

Arrange fields logically, grouping related information (e.g., personal details, contact information) for ease of use and quick navigation.

Input Field Validation:

Implement validation rules specific to each field (e.g., date of birth format, phone number structure) to ensure accuracy at the point of entry.

Dynamic Form Handling:

Enable dynamic form handling (e.g., autofill for address using zip code) to streamline data entry and reduce errors.

User Guidance and Assistance:

Include tooltips, inline hints, or help icons to assist users in understanding the type of information required for each field.

Real-time Data Validation:

Mandatory Field Validation:

Ensure mandatory fields are clearly marked and validated in real-time to prompt users if any required information is missing before submission.

Format and Range Validation:

Validate data format and acceptable ranges for fields (e.g., date of birth within a plausible range) to minimize data entry errors.

Feedback Mechanism:

Provide immediate visual feedback (e.g., color changes, icons) alongside input fields to indicate successful entry or errors needing correction.

Error Messages and Corrections:

Display concise and clear error messages beside respective fields, guiding users on how to rectify input errors.

[ramilsalihar]

Backend Acceptance Criteria:

API Endpoints for Data Operations:

Endpoint Design:

Design RESTful API endpoints following industry best practices (e.g., using HTTP methods - POST, PUT, GET) for creating, updating, and retrieving patient details.

Data Payload Handling:

Define clear structures for data payloads sent and received by API endpoints, ensuring consistency and clarity in data transmission.

Input Data Sanitization:

Implement data sanitization methods (e.g., input validation libraries, escaping characters) to prevent injection attacks and ensure database safety.

Data Validation and Sanitization:

Validation Logic Implementation:

Apply robust validation rules on the backend for each field received from the frontend to recheck data integrity and conformity to defined standards.

Sanitization Procedures:

Use sanitation methods to cleanse data of potentially harmful or unwanted elements before storing it in the database (e.g., removing HTML tags from user inputs).

Error Handling and Responses:

Define consistent error response formats for various validation scenarios, providing descriptive error messages to guide frontend interactions for necessary corrections.