Big & Routine Data-Based Palliative & End of Life Care Research
The big data research projects include a range of research studies that use large-scale routinely collected datasets (including structured and unstructured datasets) to explore various end-of-life outcomes and to generate evidence to enable policymakers, commissioners, and healthcare professionals to use them directly in their decisions to improve palliative and end-of-life care. These research studies include:
- Geographical variations in multimorbidity clusters and their impact on health, services and costs using the National Death Registration database
- End of life care for patients with serious mental disorders using the Mental Health Services Data set
- The impact of COVID-19 pandemic on health and social care services using the Clinical Practice Research DataLink (CPRD-COVID Project)
- Identifying avoidable hospitalisations at the end of life using electronic health records
Aims
CPRD-COVID
The project aims to evaluate the impact of the COVID-19 pandemic on the General Practice service use in end-of-life patients using existing dataset from the Clinical Practice Research Datalink (CPRD) – A database containing over 50 million anonymised patients’ records. Statistical methods will be used test association and compare the frequency of GP service use before and during the COVID-19 pandemic to see whether there are changes in terms of consultations, referrals and prescribing and whether patients demographic characteristics are associated with changes. This project also aims to inform national policy development in helping recovery from the COVID-19 crisis, mitigating its consequences, and better preparing for future public health crises.
Applied Research Collaborative (ARC) Routine Data
The project uses patient-level linked with area level service utilisation data to explore geographical patterns of multimorbidity and it impacts on service utilisation and health and social care costs.
The KERRI Project
Recognising avoidable hospitalisations is an important first step to transforming hospital end-of-life care and reducing the current and projected future strain on hospitals. The KERRI project explores the potential of using patient Electronic Health Records from the King's College Hospital Electronic Patient Record Interface (KERRI) combined with techniques from a branch of data science known as natural language processing (NLP) to identify and predict avoidable end-of-life hospitalisations.
Publications
Johnson H, Davies JM, Leniz J, Chukwusa E, Markham S, Sleeman KE. Opportunities for public involvement in big data research in palliative and end-of-life care. Palliat Med. 2021 Mar 24:2692163211002101. doi: 10.1177/02692163211002101
Gao W, Gulliford M, Morgan M, Higginson IJ. Primary care service use by end-of-life cancer patients: a nationwide population-based cohort study in the United Kingdom. BMC Fam Pract. 2020 Apr 29;21(1):76. doi: 10.1186/s12875-020-01127-8
Wilson R, Gaughran F, Whitburn T, Higginson IJ, Gao W. Acute care utilisation towards the end of life and the place of death for patients with serious mental disorders: a register-based cohort study in South London. Public Health. 2021 Apr 15;194:79-85. doi: 10.1016/j.puhe.2021.02.032
Chukwusa E, Yu P, Verne J, Taylor R, Higginson IJ, Wei G. Regional variations in geographic access to inpatient hospices and Place of death: A Population-based study in England, UK. PLoS One. 2020 Apr 17;15(4):e0231666. doi: 10.1371/journal.pone.0231666
CPRD-COVID
The project aims to evaluate the impact of the COVID-19 pandemic on the General Practice service use in end-of-life patients using existing dataset from the Clinical Practice Research Datalink (CPRD) – A database containing over 50 million anonymised patients’ records. Statistical methods will be used test association and compare the frequency of GP service use before and during the COVID-19 pandemic to see whether there are changes in terms of consultations, referrals and prescribing and whether patients demographic characteristics are associated with changes. This project also aims to inform national policy development in helping recovery from the COVID-19 crisis, mitigating its consequences, and better preparing for future public health crises.
Applied Research Collaborative (ARC) Routine Data
The project uses patient-level linked with area level service utilisation data to explore geographical patterns of multimorbidity and it impacts on service utilisation and health and social care costs.
The KERRI Project
Recognising avoidable hospitalisations is an important first step to transforming hospital end-of-life care and reducing the current and projected future strain on hospitals. The KERRI project explores the potential of using patient Electronic Health Records from the King's College Hospital Electronic Patient Record Interface (KERRI) combined with techniques from a branch of data science known as natural language processing (NLP) to identify and predict avoidable end-of-life hospitalisations.
Publications
Johnson H, Davies JM, Leniz J, Chukwusa E, Markham S, Sleeman KE. Opportunities for public involvement in big data research in palliative and end-of-life care. Palliat Med. 2021 Mar 24:2692163211002101. doi: 10.1177/02692163211002101
Gao W, Gulliford M, Morgan M, Higginson IJ. Primary care service use by end-of-life cancer patients: a nationwide population-based cohort study in the United Kingdom. BMC Fam Pract. 2020 Apr 29;21(1):76. doi: 10.1186/s12875-020-01127-8
Wilson R, Gaughran F, Whitburn T, Higginson IJ, Gao W. Acute care utilisation towards the end of life and the place of death for patients with serious mental disorders: a register-based cohort study in South London. Public Health. 2021 Apr 15;194:79-85. doi: 10.1016/j.puhe.2021.02.032
Chukwusa E, Yu P, Verne J, Taylor R, Higginson IJ, Wei G. Regional variations in geographic access to inpatient hospices and Place of death: A Population-based study in England, UK. PLoS One. 2020 Apr 17;15(4):e0231666. doi: 10.1371/journal.pone.0231666
Our Partners
Public Health England
Care Quality Commission (CQC)
Investigators
Emeka Chukwusa
Research Associate
Martin Gulliford
Professor of Public Health
Irene Higginson
Executive Dean, Florence Nightingale Faculty of Nursing, Midwifery & Palliative Care