Development, implementation, and evaluation of the Australian Stroke Data Tool (AuSDaT): Comprehensive data capturing for multiple uses

Olivia Ryan, Jot Ghuliani, Brenda Grabsch, Kelvin Hill, Geoffrey C Cloud, Sibilah Breen, Monique F. Kilkenny, Dominique A. Cadilhac

Research output: Contribution to journalArticleResearchpeer-review

2 Citations (Scopus)


Background: Historically, national programs for collecting stroke data in Australia required the use of multiple online tools. Clinicians were required to enter overlapping variables for the same patient in the different databases. From 2013 to 2016, the Australian Stroke Data Tool (AuSDaT) was built as an integrated data management solution. Objective: In this article, we have described the development, implementation, and evaluation phases of establishing the AuSDaT. Method: In the development phase, a governance structure with representatives from different data collection programs was established. Harmonisation of data variables, drawn from six programs used in hospitals for monitoring stroke care, was facilitated through creating a National Stroke Data Dictionary. The implementation phase involved a staged deployment for two national programs over 12 months. The evaluation included an online survey of people who had used the AuSDaT between March 2018 and May 2018. Results: By July 2016, data entered for an individual patient was, for the first time, shared between national programs. Overall, 119/422 users (90% female, 61% aged 30–49 years, 57% nurses) completed the online evaluation survey. The two most positive features reported about the AuSDaT were (i) accessibility of the system (including simultaneous user access), and (ii) the ability to download reports to benchmark local data against peer hospitals or national performance. More than three quarters of respondents (n = 92, 77%) reported overall satisfaction with the data collection tool. Conclusion: The AuSDaT reduces duplication and enables users from different national programs for stroke to enter standardised data into a single system. Implications: This example may assist others who seek to establish a harmonised data management solution for different disease areas where multiple programs of data collection exist. The importance of undertaking continuous evaluation of end-users to identify preferences and aspects of the tool that are not meeting current requirements were illustrated. We also highlighted the opportunities to increase interoperability, utility, and facilitate the exchange of accurate and meaningful data.

Original languageEnglish
Number of pages9
JournalHealth Information Management Journal
Publication statusAccepted/In press - 2022


  • clinical registries
  • data collection
  • health information management
  • population health
  • quality of care
  • stroke

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