Comparing ICD-Data Across Countries: A Case for Visualization?

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  • Lucia Otero Varela
  • Søren Knudsen
  • Sheelagh Carpendale
  • Catherine Eastwood
  • Hude Quan

We present our preliminary results of an international survey on the practical adoption and use of the International Classification of Diseases (ICD) from a visualization and visual analytics perspective. The ICD system, in different versions, is globally used for coding morbidity and mortality statistics, however, coding practices vary across countries. Our survey includes questions about hospital data collection systems, use of features in ICD, and training of ICD coding specialists. Variations in ICD could hinder comparability and limit generalizability of observed findings. Our preliminary results establish the current state of ICD use and training internationally, and will ultimately be valuable to the World Health Organization to further research on how to improve ICD coding, and enhance international comparisons of health data. From a visualization and visual analytics perspective, the current differences in adoption and use of ICD poses challenges and opportunities. For example, when morbidity-data from two countries differ in their coding, can we still compare data from these countries, and if so, then under which circumstances? We discuss how visualization and visual analytics might help in these situations.

Original languageEnglish
Title of host publication2019 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019
Number of pages2
PublisherIEEE
Publication dateOct 2019
Pages60-61
Article number8945033
ISBN (Electronic)9781728124230
DOIs
Publication statusPublished - Oct 2019
Event10th IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019 - Vancouver, Canada
Duration: 20 Oct 2019 → …

Conference

Conference10th IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019
LandCanada
ByVancouver
Periode20/10/2019 → …

    Research areas

  • Administrative health data, data collection, data provenance, ICD, information visualization, international comparability

ID: 255052314