Assessment and development of robust clinical quality indicators

Assessment and development of robust clinical quality indicators

Centre for health informatics

Research stream

Computable Evidence Lab

A graph showing clinical quality indicators

Project members - Macquarie University

Dr Guy Tsafnat - Senior Research Fellow

Professor Enrico Coiera - Professor and Director

Mr Peter Hibbert - Program Manager

Project contact

Dr Guy Tsafnat
T: +612 9850 2430
E: guy.tsafnat@mq.edu.au

Project main description

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.

Opportunities (Scholarships, Grants and Research Positions)

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.

References

  1. Tsafnat, G., et al. (2014). "Systematic review automation technologies." Syst Rev 3(1): 74.
  2. Choong, M. K., et al. (2014). "Automatic Evidence Retrieval for Systematic Reviews." Journal of medical Internet research 16(10).
  3. Tsafnat, G., et al. (2013). "The automation of systematic reviews." BMJ 346: f139.

Project sponsors

NHMRC Program grant on patient safety, NHMRC CRE in eHealth

Collaborative partners

Professor Bill Runciman, University of South Australia

Related projects

The Automation of Systematic Reviews

Project status

Current

Centres related to this project

Centre for Health Informatics

Content owner: Australian Institute of Health Innovation Last updated: 11 Jul 2018 2:25pm

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