An investigation of data entry methods with a personal computer

Crombie, Iain K.; Irving, J. M.

doi:10.1016/0010-4809(86)90028-5

Cited by 22 publications

(6 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Indeed, the relevance of a medical survey is largely dependent on two main steps: the quality of data collection in the medical-charts and the fidelity of data transferring from the charts to the electronic system. Any weakness in these two stages will invalidate the study [ 3 - 7 ].…”

Section: Introductionmentioning

confidence: 99%

Double–blind control of the data manager doesn't have any impact on data entry reliability and should be considered as an avoidable cost

Mauri¹,

Karampoiki²,

J³

et al. 2008

BMC Med Res Methodol

View full text Add to dashboard Cite

Background: Database systems have been developed to store data from large medical trials and survey studies. However, a reliable data storage system does not guarantee data entering reliability.We aimed to evaluate if double-blind control of the data manager might have any effect on datareliability. Our secondary aim was to assess the influence of the inserting position in the insertionsheet on data-entry accuracy and the effectiveness of electronic controls in identifying dataentering mistakes. Methods:A cross-sectional survey and single data-manager data entry.Data from PACMeR_02 survey, which had been conducted within a framework of the SESy-Europe project (PACMeR_01.4), were used as substrate for this study. We analyzed the electronic storage of 6446 medical charts. We structured data insertion in four sequential phases. After each phase, the data stored in the database were tested in order to detect unreliable entries through both computerized and manual random control. Control was provided in a double blind fashion.Results: Double-blind control of the data manager didn't improve data entry reliability. Entries near the end of the insertion sheet were correlated with a larger number of mistakes. Data entry monitoring by electronic-control was statistically more effective than hand-searching of randomly selected medical records.Conclusion: Double-blind control of the data manager should be considered an avoidable cost. Electronic-control for monitoring of data-entry reliability is suggested.

show abstract

Section: Introductionmentioning

confidence: 99%

Double–blind control of the data manager doesn't have any impact on data entry reliability and should be considered as an avoidable cost

Mauri¹,

Karampoiki²,

J³

et al. 2008

BMC Med Res Methodol

View full text Add to dashboard Cite

show abstract

“…The entry of data into database systems is critical and often involves high error rates [1]; this has also been our experience. In constructing a pharmacokinetic database we recorded, for historical reasons, the data using two different systems [2].…”

Section: Introductionmentioning

confidence: 84%

“…The frequencies of erroneous data had 95% confidence intervals between 1 and 10%. In other evaluation protocols the error frequency was 9 to 16% [1,7].…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Structured Data Entry for Reliable Acquisition of Pharmacokinetic Data

Zellner¹,

Schromm²,

Frankewitsch³

et al. 1996

Methods Inf Med

View full text Add to dashboard Cite

Abstract:A pharmacokinetic database was constructed that is as free of errors as possible. Pharmacokinetic parameters were derived from the literature using a text-processing system and a database system. A random data sample from each system was compared with the original literature. The estimated error frequencies using statistical methods differed significantly between the two systems. The estimated error frequency in the text-processing system was 7.2%, that in the database system 2.7%. Compared with the original values in the literature, the estimated probability of error for identical pharmacokinetic parameters recorded in both systems is 2.4% and is not significantly different from the error frequency in the database. Parallel data entry with a text-processing system and a database system is, therefore, not significantly better than structured data entry for reducing the error frequency.

show abstract

“…As NICE guidance on environmental interventions [7] was produced before publication of the methodological guidance discussed above (under 'Type 2 evidence'), we sought clarification from the authors. We were informed by the lead analyst [30] that both the review team and the programme development group considered and discussed issues including the country in which the research was conducted, the date, cultural differences and urban/rural variation in population attribute and the environment. Judgements were made based on these discussions and the expertise within the programme development group.…”

Section: Introductionmentioning

confidence: 99%

The influence of environmental factors on the generalisability of public health research evidence: physical activity as a worked example

Watts

Phillips

Petticrew

et al. 2011

Int J Behav Nutr Phys Act

View full text Add to dashboard Cite

BackgroundIt is rare that decisions about investing in public health interventions in a city, town or other location can be informed by research generated in that specific place. It is therefore necessary to base decisions on evidence generated elsewhere and to make inferences about the extent to which this evidence is generalisable to the place of interest. In this paper we discuss the issues involved in making such inferences, using physical activity as an example. We discuss the ways in which elements of the structural, physical, social and/or cultural environment (environmental factors [EFs]) can shape physical activity (PA) and also how EFs may influence the effectiveness of interventions that aim to promote PA. We then highlight the ways in which EFs may impact on the generalisability of different types of evidence.DiscussionWe present a framework for thinking about the influence of EFs when assessing the generalisability of evidence from the location in which the evidence was generated (place A) to the location to which the evidence is to be applied (place B). The framework relates to similarities and differences between place A and place B with respect to: a) the distributions of EFs; b) the causal pathways through which EFs or interventions are thought to exert their effect on PA and c) the ways in which EFs interact with each other. We suggest, using examples, how this scheme can be used by public health professionals who are designing, executing, reporting and synthesising research on PA; or designing/implementing interventions.SummaryOur analysis and scheme, although developed for physical activity, may potentially be adapted and applied to other evidence and interventions which are likely to be sensitive to influence by elements of the structural, physical, social and/or cultural environment such as the epidemiology of obesity and healthy weight promotion.

show abstract

An investigation of data entry methods with a personal computer

Cited by 22 publications

References 8 publications

Double–blind control of the data manager doesn't have any impact on data entry reliability and should be considered as an avoidable cost

Double–blind control of the data manager doesn't have any impact on data entry reliability and should be considered as an avoidable cost

Structured Data Entry for Reliable Acquisition of Pharmacokinetic Data

The influence of environmental factors on the generalisability of public health research evidence: physical activity as a worked example

Contact Info

Product

Resources

About