Object-Oriented Oncology: Making Sense of Complex Patient Journeys @PyConAU
Object-Oriented Oncology: Making Sense of Complex Patient Journeys  @PyConAU
Uploaded September 2025 | Updated September 2026, 3 hours ago
(Georgie Kennedy, Ghazaleh Niknam) Clinical data harmonisation efforts are an extraordinarily powerful tool in the world of observational research. When your data model is designed to do everything, however, there is a necessary trade-off in design principles. The requirement to support every possible use-case across all clinical domains means that they can tend to favour flexibility over clarity, storing events, measurements, treatments, and outcomes in highly normalised, loosely typed schemas. For domain experts like oncology researchers or clinicians, this makes even basic questions (say, “what happened to this patient, when, and why?”) frustratingly opaque.

Using Python’s ORM paradigm, we created a more intuitive, opinionated view of oncology data. By surfacing richly connected objects like CancerPatient, CancerDiagnosis, Regimen, or Cycle, we move away from brittle SQL scripts and toward a model that reflects how clinical experts already think. These ORM-backed tools not only support reproducible ETL and visualisation workflows, but also allow non-developers to explore complex patient journeys in a hands-on, object-based way. We’re building out a library of reusable object maps that encode domain knowledge directly, letting researchers focus on clinical questions and not worry about the nuanced query logic.

pretalx.com/pycon-au-2025/talk/DQUCMW

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Object-Oriented Oncology: Making Sense of Complex Patient Journeys

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