Preventing human error: The impact of data entry methods on data accuracy and statistical results

Barchard, Kimberly A.; Pace, Larry A.

doi:10.1016/j.chb.2011.04.004

Cited by 106 publications

(80 citation statements)

References 17 publications

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“…However, not all data entry tasks can rely upon checksums. In such situations, entering numbers twice has been shown to significantly reduce the errors made (Barchard & Pace, 2011). However, this may not be an optimal solution as it requires the user to enter values twice, and this takes time.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Interface Type on Visual Error Checking Behavior

Wiseman

Borghouts

Grgić

et al. 2015

Proceedings of the Human Factors and Ergonomics Society Annual

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During data entry tasks, small errors can result in catastrophe, for instance adding an extra zero to a drug dose when programming an infusion in a hospital. For this reason understanding users' error checking behavior is highly important. One aspect that can affect error checking is the interface that a user must interact with to enter data. Often user interaction with interfaces is evaluated based on speed or error rate. In this paper, in addition to this, we also explore how different types of interface can affect a user's error checking behavior in a multitasking environment. We show that a fast to use and familiar interface discourages users from carrying out thorough visual checking in a number transcription task. We also found that having participants perform an additional secondary task while doing the number entry task made participants less likely to check the inputted numbers for errors.

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Section: Introductionmentioning

confidence: 99%

The Effect of Interface Type on Visual Error Checking Behavior

Wiseman

Borghouts

Grgić

et al. 2015

Proceedings of the Human Factors and Ergonomics Society Annual

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show abstract

“…Unintentional data errors can be caused by mistaken data entry by humans and information system failures. Even with visual checking, human data entry can introduce errors in up to 10% of the data [1]. In addition, linguistic translation errors and phonetic errors can occur during data entry, typically via verbal communication.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Efficient identity matching using static pruning q-gram indexing approach

Nizam

Azman

2015

Decision Support Systems

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“…These types of errors include typographic errors, miscoding, data merged into the wrong field(s), and other factors that may lead to misinformation even before the data are evaluated for analysis and conclusions. [6][7][8] Data entry errors can have substantial effects on the outcome(s) measures and can change the magnitude and direction of associations between a risk factor and the outcome of interest. 6,9 Although computerized methods are used to capture and store feedlot data, compiling the data into formats for appropriately assessing health outcomes can still require additional effort.…”

Section: Quantity and Quality Of Operational Datamentioning

confidence: 99%