Inequalities and guideline-concordant care in breast cancer surgery and radiotherapy

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This multi-disciplinary project addresses four key practices in breast cancer care: breast conserving surgery, radiotherapy after breast conserving surgery, sentinel node biopsy, and breast reconstruction. We will integrate all NSW and Commonwealth health datasets for 75,000 cases. This big data platform is the most comprehensive internationally. We will quantify the rate of guideline-discordant care, including trends over time in relation to clinical guidelines and macro policies such as regional cancer centres. We will use innovative methods to identify the patient-, clinician-, hospital-, and health system-level factors independently associated with this care. We will identify levers for policy and practice change.

The ideal candidate will have the following skills:

  • A degree in clinical medicine, public health, health data science, biostatistics or a related discipline
  • Competency in statistical programming
  • Excellent written and oral communication skills
  • Ability to work effectively as a member of a large inter-disciplinary team
  • Familiarity with cancer and health system terminology
  • Ability to rapidly learn new concepts and health data science approaches
  • Ability to work independently and to deadlines

And the following experience:

  • Work, study or volunteer experience with health data, preferably large datasets
  • First author on published manuscript(s) or reports
Supervisory team
Claire
Vajdic

Medicine
Centre for Big Data Research in Health
Michael
Barton

Medicine
Ingham Institute
Marina
van Leeuwen

Medicine
Centre for Big Data Research in Health
claire.vajdic@unsw.edu.au