To build and validate digital templates for the routine assessment of clinical phenotypes at low or negligible incremental cost. Phenotypes will include clinical disease states of interest and selective digital algorithms as specified by relevant clinical experts. Furthermore, data mining algorithms will define patient co-morbidity and frailty using electronic pathology, radiology, and administrative disposition data. Such templates will also be used to evaluate patient outcomes.

In the later iterations of this clinical quality initiative, prospective data provided with opt-out consent will be used for ongoing validation and improvement of the templates, as a vehicle for further quality assurance activities, and for research with appropriate HREC / governance / patient approvals as required and described in the opt-out consent form.

The electronic phenotype templates established will exemplify a low-cost or negligible incremental cost clinical quality registry of disease or condition with long-term outcome evaluation. This will allow near-complete patient capture with a focus on care and outcome, while at the same time reducing data fragmentation. The initiative will also define the technical and governance requirements to extend this capacity across the Australian health system, and form a foundation for enhancing decision-making and limiting unwarranted variation, providing the groundwork for evaluating impacts of health policy and service redesign. Such a repository will also feed back into routinely collected data, increasing data integrity, reducing data missingness, improving data interfaces, and further standardising data definitions and workflows. The overall aim of this project is the development of validated data specifications that will enable the implementation of low cost, yet high fidelity, routine clinical quality registries in clinical care.