HIS MODULE 8-9 QUIZ

What does "accuracy" in data quality refer to?

• Data that is complete and timely

• Error-free records that can be used as a reliable source of information

• Data that is easy to present and interpret

• Records that are consistent across systems

At the service delivery point, what does completeness mean?

• All records must be error-free

• All patient/client data elements in a register must be filled

• All data should be reported on time

• All data must be consistent across platforms

Why is relevant data important in reporting?

• Because it ensures data is comprehensive

• Because it guarantees data is error-free

• Because correctly reported relevant data is indisputable

• Because it makes data more accessible

When is data considered consistent in healthcare systems?

• When it is collected within the prescribed time frame

• When all relevant data elements are filled in registers

• When the value of data is the same across applications and systems, such as the patient's medical record number

• When data is relevant to the user's area of interest

When data is described as "comprehensive," what does it mean?

• The dataset contains all the necessary information for a given purpose

• The dataset is free from duplication and errors

• The dataset is always updated in real time

• The dataset is accessible only to authorized personnel

What is the main function of a data quality tool?

• To store large volumes of data

• To analyze information and identify incomplete or incorrect data

• To design data visualizations

• To encrypt sensitive data

What does data cleansing (also known as data scrubbing) involve?

• Removing duplicate files only

• Removing corrupt, inaccurate, or inconsistent data and correcting records with formatting or typographical errors

• Encrypting sensitive datasets for security purposes

• Compressing data to reduce storage size

What does parsing and standardization in data quality tools involve?

• Encrypting data for security

• Decomposition of fields into component parts and formatting values into consistent layouts

• Removing duplicate or redundant records

• Compressing large datasets for faster processing

Which of the following is an example of parsing?

• Collecting patient records from multiple facilities

• Transforming raw HTML into a more readable and standardized data format

• Checking for typographical errors in reports

• Storing data in cloud systems

What does generalized "cleansing" in data quality tools refer to?

• Removing duplicate datasets

• Modification of data values to meet domain restrictions, integrity constraints, or organizational rules

• Encrypting data for security

• Converting raw data into visual formats