Data Update

Making changes to existing data records to keep information up-to-date and relevant.

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🧩 Overview

Data Update workflows are responsible for modifying existing records in the system. These updates may reflect changes in user inputs, process corrections, business rule adjustments, or synchronization with external systems.

This process must ensure:

• Data integrity and auditability
• Minimal disruption to related workflows
• Controlled access and validation

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🔄 Common Update Scenarios

Use Case	Description
Update patient contact info	Phone/email changed
Change billing status	Mark as paid, refunded, or canceled
Modify test result values	Correction after review
Adjust user permissions	Promote or demote access roles

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⚙️ SQL-Based Update Example

UPDATE patients
SET mobile = '9876543210', updated_at = NOW()
WHERE id = 105;

Always include updated_at and, optionally, updated_by to track changes.

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🧪 Example: Status Transition for Lab Test

Scenario:

A lab test result moves from pending to approved after review.

UPDATE lab_results
SET status = 'approved', reviewed_by = 'Dr. Smith', reviewed_at = NOW()
WHERE id = 200 AND status = 'pending';

This ensures valid state transition (no redundant or invalid changes).

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🚦 API Update Pattern (Express.js)

router.put("/patients/:id", async (req, res) => {
  const id = req.params.id;
  const { name, mobile } = req.body;

  await db.query(
    "UPDATE patients SET name = ?, mobile = ?, updated_at = NOW() WHERE id = ?",
    [name, mobile, id]
  );

  res.json({ status: "updated" });
});

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✅ Validation Considerations

• Check that the record exists before updating
• Validate incoming data types and formats
• Enforce business rules (e.g., no downgrading paid status)
• Prevent updates to restricted fields (e.g., ID, email after verification)

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🔐 Access Control

Field	Access Rule Example
is_admin flag	Only super admins can update
salary	Only HR roles can modify
test_results	Only doctors or lab admins can edit

Use role-based control to restrict editing capabilities.

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🧠 Best Practices

• Use PATCH for partial updates, PUT for full object replacement
• Always log what was changed, by whom, and when
• Perform updates in transactions if multiple tables are involved
• Add confirmation dialogs for UI-based changes
• Allow undo where applicable (versioning, history tables)

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🧾 Auditing and Logging

Change Log Table Example:

{
  "table": "patients",
  "record_id": 105,
  "changed_by": "admin_user",
  "timestamp": "2025-05-22T10:15:00Z",
  "changes": {
    "mobile": {
      "from": "9123456789",
      "to": "9876543210"
    }
  }
}

Store this log separately or in a JSON column in the main table.

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🔄 UI Considerations

• Inline editable fields for quick updates
• Save & Cancel buttons for user control
• Show change preview or summary before committing
• Disable fields that should not be edited
• Provide success/failure notifications

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📚 Applications of Data Update

Domain	Use Case
Healthcare	Update diagnosis or doctor assigned
Finance	Correct transaction amount or category
Logistics	Update delivery status or package location
HR	Modify employee records or job title

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🔚 Summary

The Data Update workflow ensures that information remains accurate, relevant, and traceable. It should be implemented with validation, access control, and logging to maintain system trustworthiness and regulatory compliance.

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