Investigating links between severe mental illness and dementia using primary and secondary electronic health records.

Lead Supervisor
TBC

Co-supervisor
Dr Rebecca Bendayan, Professor Robert Stewart
Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London

Project Details

Background:

There is an ongoing debate on the nature of the progression of cognitive changes in individuals with severe mental illness (e.g., bipolar disorder and schizophrenia) and it is yet not clear whether these are associated with a neurodevelopmental or neurodegenerative process such as dementia. There is a need for research to detangle the complex inter-relationships between severe mental illness and dementia, specially give that individuals with this comorbidity pattern are at increased risk of psychiatric hospitalizations. The main barrier for research in this topic is the limited access to samples that have large sub-samples with both diagnoses. The South London and Maudsley (SLaM) Biomedical Research Centre (BRC), one of the largest mental health care provider in Europe, provides us a unique opportunity for this as an on-going study has identified 475 patients which can be matched with individuals with none of these diagnoses or only one. The main aim of this project is to explore progression from one condition to another one and examine potential underlying shared explanatory mechanisms such as alcohol and substance abuse, medication or other co-existent health conditions. 

Novelty and Importance: 

From a clinical point of view, this project would allow to identify potential shared mechanisms between both conditions (e.g., medication) and identify individuals at higher risk of psychiatric hospitalization in SLaM, which could allow to develop targeted interventions earlier in time. From a methodological perspective, tools developed would be directly relevant and applicable to electronic health records collected by CRIS SLaM, Lambeth DataNet and other CRIS resources.

Primary aim(s):

To identify the patterns of progression of both diagnoses and potential shared mechanisms.  This will provide an overview of their progression patterns from SMI to dementia or from dementia to SMI and from primary to secondary health care. Moreover, will help us identify whether these are associated with key factors such as medication, co-existent health conditions, health behaviour and social and environmental factors. 

Planned research methods and training provided: BHI training and KCL early career training opportunities. Specific training on NLP and predictive statistical modelling (including machine learning techniques).

Objectives / project plan:

Year 1: Literature review. CRIS and Lambeth DataNet data retrieval and preparation. 

Year 2 : Data analysis to identify the most common patterns of progression and exploratory analyses on potential shared mechanisms. Paper submissions. 

Year 3 : Follow up of Year 2 and additional data analysis to identify individuals at higher risk psychiatric hospitalization. Thesis and BRC report on potential clinical implications write up.

Scientific themes : 1) Learning from Big Data for Health. This project uses large, distributed, heterogeneous data sources such as CRIS EHRs to address major public health challenges such as dementia. Moreover, potential findings on shared mechanisms could be key to improve treatments and/or interventions.

Datasets

CRIS system enables access to anonymised electronic patient records for secondary analysis from SLaM and has full ethical approvals. CRIS was developed with extensive involvement from service users and adheres to strict governance frameworks managed by service users. It has passed a robust ethics approval process acutely attentive to the use of patient data. Specifically, this system was approved as a dataset for secondary data analysis on this basis by Oxfordshire Research Ethics Committee C (08/H06060/71). The data is de-identified and used in a data-secure format and all patients have the choice to opt-out of their anonymized data being used. The CRIS Oversight Committee is responsible for ensuring all research applications comply with ethical and legal guidelines. Linkages with Lambeth DataNet have also all approvals.

Keywords

Severe Mental Illness, Dementia, Electronic Health Records