Assessment and development of robust clinical quality indicators
CENTRE FOR HEALTH INFORMATICS
Research Stream: Computable Evidence Lab
How do we know if clinical practice delivered really complies with evidence of best practice? Clinical quality indicators (CQI) are measures designed to answer that question, but CQI themselves are not always developed through a rigorous and evidence-based process.
This project aims to understand the current quality of CQI, best practices and so that we can efficiently create robust and effective CQI that dierctly improve patient safety and quality of healthcare.
Our postgraduate programs allow candidates to undertake advanced research leading to a Master's or PhD degree under the supervision of experienced senior research staff in one of AIHI’s research areas. Current research opportunities at AIHI.
- Tsafnat, G., et al. (2014). "Systematic review automation technologies." Syst Rev 3(1): 74.
- Choong, M. K., et al. (2014). "Automatic Evidence Retrieval for Systematic Reviews." Journal of medical Internet research 16(10).
- Tsafnat, G., et al. (2013). "The automation of systematic reviews." BMJ 346: f139.
NHMRC Program grant on patient safety, NHMRC CRE in eHealth
Project contacts
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Senior Research Fellow+612 9850 2430
