
HIS MODULE 8-9 QUIZ
Quiz
•
Science
•
University
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Practice Problem
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Easy
Belma Dumangeng
Used 3+ times
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60 questions
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1.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
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
2.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
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
3.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
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
4.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
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
5.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
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
6.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
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
7.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
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
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