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Understanding care pathways and clinical outcomes in neurological disorders at King’s College Hospital, using CogStack, a novel data analytics infrastructure applied to electronic health records.

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  • Full or part time
    Prof M Richardson
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

In this studentship, the PhD student will have the opportunity to use state-of-the-art data analytics applied to electronic health records, in order to develop a comprehensive understanding of care pathways and outcomes for patients with neurological disorders in Kings’ College Hospital Foundation Trust (KCH). KCL and KCH has recently deployed a state-of-the-art clinical analytics system (Cogstack) with algorithmic semantic processing of unstructured text. This technology has been mentioned in the Chief Medical Officer’s 2017 report ‘Generation Genome’ as a key technology to enable systematic extraction of information from diverse text records. KCL and KCH are core applicants for the London site of Health Data Research (HDR UK).
The PhD candidate will use CogStack to perform a detailed analysis of patient pathways and outcomes of patients with neurological disorders. The candidate will explore the correlation of patient care pathways with specific outcomes using graph mathematics, network analysis and time series analysis. The range and diversity of neurological disorders may require bundling of diagnoses and outcome measurements together into streamlined pathways while simultaneously recognising the heterogeneity of neurological disorders. This work will run in parallel to ongoing transformation and redesign of clinical tertiary and secondary neurological services which will provide an important opportunity to explore causal factors for patient outcome. The candidate’s work will inform the design of data-driven healthcare delivery as well as a formulation of a common data model and architecture for both disease-agnostic outcomes and disease-specific outcomes.
The student will acquire the latest data science and research skills in partnership with King’s Health Partners Neurosciences Institute, with support from South London and Maudsley Biomedical Research Centre for Translational Informatics and Health Data Research (HDR UK) courses and skills.

References:
1) Bean DM, Stringer C, Beeknoo N, Teo J, Dobson RJB (2017) Network analysis of patient flow in two UK acute care hospitals identifies key sub-networks for A&E performance. PLoS ONE 12(10): e0185912 http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0185912
2) Chief Medical officer Annual Report: Generation Genome, July 2017 https://www.gov.uk/government/publications/chief-medical-officer-annual-report-2016-generation-genome


Eligibility:
Applicants should have Bachelor’s degree with 2:1 honours. A 2:2 degree may be considered only where applicants also offer a Masters with Merit. A research Masters would be a strong advantage. Degrees in the following subject areas are relevant:
- Biomedical or health-related degree
- Computer science or engineering degree
- Data science or mathematics degree
Applicants must be familiar with basic office software especially spreadsheet software.

Familiarity with any of the following programming languages (R, Python, Matlab, Tensorflow) is strongly desirable.

Funding Notes

The award covers home (UK/EU) fees, basic stipend (£17,000 per year) and some limited research and travel costs. The studentship cannot consider applicants that are not eligible for UK/EU student fees.


References

For further details on the application process, please visit: https://www.kcl.ac.uk/ioppn/study/prospective-students/programmes-of-study/pgr/fundedresearchopportunities/RICHTEO-1801.aspx

Closing date: Mon 23 April 2018 (23:59 GMT)
Interviews: Week commencing: 30 April 2018


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