Talk Description
Institution: Australian and New Zealand Emergency Laparotomy Audit - South Australia, Australia
Purpose
To describe the development of near real time state based Quality Improvement (QI) reports by the Australian and New Zealand Emergency Laparotomy Audit (ANZELA).
Methodology
ANZELA is a Clinical Quality Registry (CQR) that collects data on evidence-based care for Emergency Laparotomy (EL). Data is entered into REDCap in near real time, cleaned and analysed monthly using funnel plots and Statistical Process Control (SPC) charts that show identifiable hospital participation. Hospitals and health departments now receive a state-based report that show these and additional data each month.
Results
Of the estimated 120 hospitals undertaking ELs, 51 (43%) participate. There is no EL classification code so a SPC chart of ELs undertaken is used as a surrogate measure of case ascertainment. Fully engaged hospitals showing less monthly variation so likely more complete case ascertainment. The funnel plots show wide inter-hospital variation in care compliance and data completeness. There is also variation within individual hospitals for different care standards. Some hospitals have embraced the feedback and improved both their compliance and data completeness.
Conclusion
ANZELA is now providing near real time state based QI data each month. This can be used by hospitals and health departments to address inter-hospital variation and will meet the requirements of the EL Clinical Care Standards being developed. However, participation and data completeness falls far below the recommended 95% minimal standard. This will challenge interpretation, a problem common to all Australian CQRs. There is an urgent need to address the very poor participation in Australian CQRs. This will likely require mandatory participation in priority CQRs.
Presenters
Authors
Authors
Mr Robert Aitken - , Dr Lettie Pule - , Mr Wentao Wang - , Mr Peter Li - , Mr Richard Gillett - , Ms Denise Mcmahon - , Dr Wendy Babidge - , Dr Helena Kopunic -