Can prospective usability evaluation predict data errors?

Constance M. Johnson, Meredith Nahm, Ryan J. Shaw, Ashley Dunham, Kristin Newby, Rowena Dolor, Michelle Smerek, Guilherme Del Fiol, Jiajie Zhang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Increasing amounts of clinical research data are collected by manual data entry into electronic source systems and directly from research subjects. For this manual entered source data, common methods of data cleaning such as post-entry identification and resolution of discrepancies and double data entry are not feasible. However data accuracy rates achieved without these mechanisms may be higher than desired for a particular research use. We evaluated a heuristic usability method for utility as a tool to independently and prospectively identify data collection form questions associated with data errors. The method evaluated had a promising sensitivity of 64% and a specificity of 67%. The method was used as described in the literature for usability with no further adaptations or specialization for predicting data errors. We conclude that usability evaluation methodology should be further investigated for use in data quality assurance.

Original languageEnglish (US)
Pages (from-to)346-350
Number of pages5
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
Volume2010
StatePublished - 2010
Externally publishedYes

ASJC Scopus subject areas

  • Medicine(all)

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