Question

Complexity of Integration

Data integration appears simple in theory but in fact it can be a very complex process, particularly in organizations where sensitive or personal information is used, such as health care. Based on this information, why is data integration important in a data management process? How critical is it to have a comprehensive integration plan, particularly in today’s world of health care? Provide examples to support your thoughts.

Answer 1

Data is one of the most valuable assets of any company. It is nothing more than information.

Data integrity is nothing but the process of aiming to prevent unintentional changes to information.

Data integrity is classified as two;

1. Physical integrity: This refers to the process of storing and collecting data in the most correct way, maintaining its accuracy and reliability.

2. Logical integrity: The logical integrity of data, on the other hand, checks whether data is correct and accurate in a specific context.

Preserving data integrity should be the top priority of your organization.

• Data cleaning and maintenance: make sure to do this on a regular basis, and implement a regular routine to ensure it is consistently done.
• Data entry training: Train your users on how to enter and maintain data
• Data validation rules: Data validation rules will validate, control and restrict the values that users can enter into their system.

As a strategy, integration is the first step toward transforming data into meaningful and valuable information

The benefits of data integration are;

1.Data integration will improve decision making

2. It will improve customer experience

3. From procurement and supply chain to manufacturing and product management, real-time access is useful for improving processes, increasing production, and lowering costs across various departments, including sales, production, distribution and more.

4. With automatic data integration, your data from all the different sources are pooled into a single customer view, allowing you to be more productive.

5. Combine historical data with sales pipeline information to predict customer demands.

Data integrity in health care

• All the patient data should be clear and accurate and demonstrate who observed and recorded it. It will be helpful for future reference.
• Patient records should be clear, easy to understand, and preserved securely.
• Record patient notes and data in real-time, as observed, and at the time any consult, test, or procedure was executed.
• Health data should be accurate, free from errors, and conform to the latest industry regulatory policies and procedures.

"Integrity is shown by the medical assistant checking in with the patient letting them know the physician is running behind, and assuring the patient the physician will be with them as soon as possible." This is just one of many examples of integrity in medical practice.