Imperial College Healthcare NHS Trust

Government Agency (Health and Adult Social Care)

Deidre Lyons

Unknown

No

NIBDAPC_2021_0007

Ovarian cancer is the most lethal gynaecological malignancy, diagnosed in over 7000 patients each year in the UK and prognosis remains poor. The recent national ovarian cancer pilot audit has clearly revealed significant inequalities in the management of patients on a national level. We do not yet understand the reasons underlying these differences and the full impact of these inequalities on outcome. There is therefore a significant unmet need to understand treatment pathways for all women with ovarian cancer level and correlate these data with outcome. It is only by ensuring accurate, correct records, fully analysing and reviewing our data that we can really understand the challenges that are faced when treating patients with ovarian cancer. We propose to develop methods to utilise the wealth of routine data held in NHS records. We will develop the processes that allow robust, relevant and comprehensive data collection and analysis to be performed automatically to assess the care given to all patients. This data will be used to identify any inequalities in care of patients with ovarian cancer (e.g. variations with age, ethnicity or region) and develop methods to feedback this information to the clinical teams. Once this is understood we can begin to effect change and improve care for patients.

The results from the ovarian cancer feasibility pilot audit1 have clearly revealed inequalities in the management of patients with ovarian cancer on a national level. We are yet to appreciate fully the reasons underlying these differences and the full impact of these inequalities on outcome. There is therefore a significant unmet need to be able to understand treatment pathways for all women with ovarian cancer on a local and national level and correlate these data with outcome. There is a wealth of data held across NHS systems that could help understand the management of patients with ovarian cancer. Curation of these data on the scale needed to effect change is near impossible using the current methods of manual data collection. This project proposes to address this problem by creating a collaboration with clinicians, informatics teams and data analysts. This project aims to design innovative programmatic linkage, curation and analysis pipelines for data using text analysis. This will enable us to: 1. Answer important clinical relevant questions regarding the management of patients with ovarian cancer 2. Identify areas of inequality of care (e.g. inequalities with age, ethnicity, region). To use this knowledge to develop ways to improve this and improve direct care (for example, engagement with local GPs, cultural groups, patients’ groups, addressing the needs of the older women). 3. Identify ways to improve efficacy of the service to benefit both patients and healthcare professionals 4. Provide evidence of accuracy of the text analysis and explore how it can be used with clinician validation to improve the quality of the clinical record Once developed, we will share our learning and techniques with other tumour sites and also other Trusts across the UK so that collection and analysis of relevant data is possible on a national level and healthcare professionals can have access to the data to drive ongoing improvement.

Public Health Research

14/01/2022

14/01/2022

De-Personalised

Not applicable

Not applicable

One-off

14/01/2022

TRE