Lay summary
This study examines the obstacles clinicians face due to inadequate clinical decision support and the fragmentation of hospital information systems. Employing a co-design and design science with clinical partners, we will apply a system integration architecture to facilitate the development of a clinical decision support system based on machine learning techniques for Te Whatu Ora. Our initial target will be using the Diabetes Electronic Health Records from the Waikato region to identify the subsequent diagnosis and treatments and to build a machine learning model embedded in Te Whatu Ora data in Waikato. The validity of the machine learning model will be tested to ensure the architecture meets the current workflow, then we will perform a process simulation to estimate the performance of the design by measuring the potential savings in clinical costs. The project outcomes will contribute to Te Whatu Ora to help facilitate clinical decision-making for diagnosis and treatment.