Objectives When low back pain is managed in the emergency department overdiagnosis and overtreatment are common. Measuring this is usually cumbersome. An online data analytics and visualisation tool was designed and developed to capture, store, analyse and visually present ED care data of patients presenting with low back pain.
Method This project was conducted in collaboration with the Performance Monitoring, System Improvement and Innovation Unit of the Sydney Local Health District (SLHD). An online data analytics and visualisation tool was designed and created using Qlik Sense® by a multidisciplinary team of researchers, clinicians, and information technology experts
Results The online data analytics and visualisation tool (STARS Back Pain App) was developed within the SLHD Targeted Activity and Reporting System (STARS). It displays the total number of presentations for low back pain at the three SLHD’s EDs, as well as subsequent admissions to hospital. Data displayed in the app reflect ED practice for low back pain management, such as proportion of patients receiving: i) laboratory tests, ii) imaging, and iii) pain medications. The app also displays demographics and characteristics of patients, including age, gender, days and hours presenting, mode of arrival, and emergency triage category. The app allows interactive analysis using innovative visualisation techniques.
Conclusions The STARS Back Pain App will provide emergency clinicians with a summary of their clinical performance. It will also allow us to efficiently measure unwarranted clinical variation and drive practice change using and audit and feedback approach to avoid inappropriate use of tests and treatments for low back pain.
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