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dc.contributor.authorKhor, Richard
dc.date.accessioned2018-12-03T02:04:47Z
dc.date.available2018-12-03T02:04:47Z
dc.date.issued2018en_US
dc.identifier.urihttp://hdl.handle.net/11343/219188
dc.description© 2018 Dr Richard Khor
dc.description.abstractIn 2007, the concept of rapid learning healthcare was proposed in the United States of America health system in a response to increasing healthcare costs. Its aim was to accelerate knowledge discovery through a systematic approach to integrating electronic medical records design with analysis infrastructure to rapidly and continuously assess health system performance. The delivery of healthcare is becoming increasingly performed and documented within the electronic domain, and large databases of healthcare-related information being created as a by-product. This has led to an unprecedented level of access to detailed and structured clinical data that could be used to accelerate research. In a rapid learning healthcare system, the high level of integration from electronic record to policy would ensure that each patient and each click of the mouse would drive innovation. The attraction of rapid learning was not to supplant the traditional clinical trial paradigm, but to augment its effectiveness with accelerated analysis of real-world outcomes. The rapid learning concept relied heavily on electronic medical records, administrative systems and disease registries as data sources to power analyses. Electronic health record penetrance in Australia has lagged that achieved in the USA, primarily because of financial assistance provided as part of the HITECH act in the USA. However, one exception is seen in oncology, where radiotherapy is exclusively prescribed electronically. Additionally, there has been a significant shift toward electronic chemotherapy prescribing due to the clinical risk associated with manual systems. Perhaps in oncology there is an opportunity to replicate the successes of data-driven health research achieved elsewhere. The objective of the work contained in this thesis is to develop practical methods to expand and discover the infrastructure required to implement rapid learning health care in the Australian oncology context. Ultimately, the aim is to increase the quality and efficiency of medical care and research by harnessing novel information technology (IT) methods. In addition to leveraging existing secondary databases for health services research and creating high impact linkages with state-level cancer registries, advanced IT methods could also be used to automate manual data extraction tasks in a timely and cost-effective fashion. The integration of these methods into routine clinical practice has enormous implications for tracking patient care quality, and accelerating research by utilising all data by-products of health care.  en_US
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dc.subjectoncologyen_US
dc.subjecthealth services researchen_US
dc.subjectcanceren_US
dc.subjectradiation oncologyen_US
dc.subjectnatural language processingen_US
dc.subjectcancer registryen_US
dc.subjectmachine learningen_US
dc.titleHow information technology improves the quality and efficiency of medical care and researchen_US
dc.typeDoctorateen_US
dc.typethesis
melbourne.affiliation.departmentSir Peter MacCallum Department of Oncology
melbourne.affiliation.facultyMedicine, Dentistry & Health Sciences
melbourne.thesis.supervisornameDuchesne, Gillian
melbourne.contributor.authorKhor, Richard
melbourne.accessrightsOpen Access


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