Data Entry error - Epidemiology

What is Data Entry Error?

Data entry error refers to inaccuracies or mistakes made while recording data into a system. These errors can arise from various sources such as manual entry, software glitches, or misinterpretation of the data. In the context of epidemiology, data entry errors can significantly affect the outcomes and interpretations of research studies, as well as public health decisions.

Types of Data Entry Errors

Typographical Errors: Simple mistakes made during manual data entry, such as misspellings or incorrect numerical entries.
Transcription Errors: Mistakes that occur when data is transferred from one source to another, such as from a paper form to a digital database.
Misclassification Errors: Incorrectly categorizing information, such as coding a disease under the wrong classification.
Omission Errors: Failing to record certain data points entirely, leading to incomplete datasets.
Duplication Errors: Entering the same data point multiple times, which can skew statistical analyses.

Causes of Data Entry Errors

Several factors can contribute to data entry errors in epidemiological studies:

Human Factors: Fatigue, lack of training, or misunderstanding of the data collection protocols can lead to errors.