Factors influencing digital review of pathology test results in an inpatient setting: A cross-sectional study

Robert Challen, Krasimira Tsaneva-Atanasova, Tom Edwards, Luke Gompels, Mark Dayer, Martin Pitt, Leon Danon

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Background: Delay or failure to view test results in a hospital setting can lead to delayed diagnosis, risk of patient harm, and represents inefficiency. Factors influencing this were investigated to identify how timeliness and completeness of test review could be improved through an evidence-based redesign of the use of clinical test review software. Methods: A cross-section of all abnormal hematology and biochemistry results which were published on a digital test review platform over a 3-year period were investigated. The time it took for clinicians to view these results, and the results that were not viewed within 30 days, were analyzed relative to time of the week, the detailed type of test, and an indicator of patient record data quality. Results: The majority of results were viewed within 90 min, and 93.9% of these results viewed on the digital platform within 30 days. There was significant variation in results review throughout the week, shown to be due to an interplay between technical and clinical workflow factors. Routine results were less likely to be reviewed, as were those with patient record data quality issues. Conclusion: The evidence suggests that test result review would be improved by stream-lining access to the result platform, differentiating between urgent and routine results, improving handover of responsibility for result review, and improving search for temporary patient records. Altering the timing of phlebotomy rounds and a review of the appropriateness of routine test requests at the weekend may also improve result review rates.

Original languageEnglish
Pages (from-to)290-298
Number of pages9
JournalJAMIA Open
Issue number2
StatePublished - 1 Jul 2020
Externally publishedYes


  • Clinical workflow
  • Data quality
  • Laboratory informatics
  • Quality improvement
  • Test result follow-up


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