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Data Quality Issues

When there are mistakes in data entering, it translates into problems in patient care, reimbursement, and research. The problem of poor data crosses departments and organizations, filtering into decisions that are made based on the data.
What are some examples (real or fictitious) of data entry issues that could compromise data quality?
What implications are there compromised data?
What can be done to mitigate mistakes associated with entering data?

Solution Preview

What are some examples (real or fictitious) of data entry issues that could compromise data quality?

There's a wide range of both real and fictitious data entry issues both with technology and hand written. The most common is human error whether it's insufficient information, illegible entries or mistyped entries, misinterpretations by doctors, nurses, and patients. (Example: Handwriting mistakes: A doctor's rushed attempt to write down a dose could lead to a wrong prescription dosage.)

Another data entry issue is the inability to collect information in a timely and well organized manner. This came up in the recent Ebola epidemic, as misinformation was collected, panic spread, and inaccurate information was recorded. Another example is oral transcription issues. Many health care institutions will use transcribers of doctor's oral notes, which can be misinterpreted.

Another real example of data entry ...

Solution Summary

This essay goes into some data entry issues, implications of compromised data, and what can be done to mitigate mistakes in the future. It details examples, and gives 2 references.

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