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An Application of Item Response Theory to Scoring Patient Safety Culture Survey Data.

Heon-Jae JeongHsun-Hsiang LiaoSu Ha HanWui-Chiang Lee
Published in: International journal of environmental research and public health (2020)
Patient safety culture is important in preventing medical errors. Thus, many instruments have been developed to measure it. Yet, few studies focus on the data processing step. This study, by analyzing the Chinese version of the Safety Attitudes Questionnaire dataset that contained 37,163 questionnaires collected in Taiwan, found critical issues related to the currently used mean scoring method: The instrument, like other popular ones, uses a 5-point Likert scale, and because it is an ordinal scale, the mean scores cannot be calculated. Instead, Item Response Theory (IRT) was applied. The construct validity was satisfactory and the item properties of the instrument were estimated from confirmatory factor analysis. The IRT-based domain scores and mean domain scores of each respondent were estimated and compared. As for resolution, the mean approach yielded only around 20 unique values on a 0 to 100 scale for each domain; the IRT method yielded at least 440 unique values. Meanwhile, IRT scores ranged widely at each unique mean score, meaning that the precision of the mean approach was less reliable. The theoretical soundness and empirical strength of IRT suggest that healthcare institutions should adopt IRT as a new scoring method, which is the core step of processing collected data.
Keyphrases
  • patient safety
  • psychometric properties
  • healthcare
  • quality improvement
  • electronic health record
  • big data
  • cross sectional
  • patient reported outcomes
  • data analysis
  • mental health
  • social media
  • artificial intelligence