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Digital health interventions and data science are increasingly used to address health challenges through a myriad of solutions from apps, augmented interfaces, clinician-facing decision-support systems, and new models of care such as telehealth. Candidates will work on a substantial research project in an area of specific interest applicable to digital health, health, or clinical data science. The project may include the analysis of an existing health related data set, a systematic review, a case study, health technology evaluation, clinical re-design, survey, or other projects deemed acceptable to the project partner and supervisor. Listed projects may be available for students to select if they fulfill the skills, pre-requisites, and interview requirements. Candidates with a current workplace-based project may apply for project partner approval if learning outcomes criteria are met. The candidate will enter a group or individual learning contract. The development of suitable methodologies and a substantive literature review will be the primary focus for Project A. This supports the focus for Project B; a scholarly work which may be a paper for publication or industry report, culminating in a presentation or seminar suitable for academic and/or professional audiences. Implementation science and modern project management techniques should be used where appropriate in projects.
Code | BIDH5001 |
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Academic unit | Department of Medical Sciences |
Credit points | 6 |
Prerequisites:
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24 credit points of (HTIN5006 or HTIN5005 or HSBH5003 or BIDH5003 or BIDH5000 or COMP9001 or INFO5306 or HTIN5003 or COMP9103 or COMP5046 or COMP5048 or COMP5318 or COMP5424 or STAT5002 or STAT5003 or BMET9925 or BMET5933 or BMET5992 or IDEA9106 or CEPI5100 or BETH5204 or HPOL5014 or HPOL5012 or COMP5427) |
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Corequisites:
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None |
Prohibitions:
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None |
Assumed knowledge:
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Assumed library information systems research skills and basic knowledge of health, health care and associated ethics and governance systems are required. Students must complete a pre-capstone knowledge screening quiz or interview which will identify recommended modules for their capstone. Please check the Canvas site for this unit for any information on further recommended resources, mandatory sessions and modules |
At the completion of this unit, you should be able to:
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