Data analysis to help improve diagnosis of ovarian cancer

Imperial College Healthcare NHS Trust has received an Imperial Health Charity grant that will allow a team of doctors to explore a new approach to data analysis that could lead to more effective diagnosis and treatment for people suffering from ovarian cancer.

The new methods will aim to analyze the data already held on the system, to establish a trend that could be essential in providing vital information on how patient care journeys can be improved.

Ovarian cancer is the sixth most common cancer in women in the UK and sees 7,500 new diagnoses each year.

Currently, the prognosis for women with ovarian cancer is relatively poor, this is due to patients presenting at a late stage when the cancer is advanced or, in some cases, incurable.

Although there is data on women with this particular type of cancer, analysis can be difficult to derive because different doctors enter data in different ways.

The new iCARE (NHS Imperial Clinical analytics, Research and Evaluation) system will ‘clean’ existing current data and make it anonymous, ready to be stored in the NHS system.

Through the new data analysis, the NHS Trust hopes to improve health inequalities among cancer patients in different geographical areas across England and better understand why these inequalities exist.

The team of doctors involved in the program is led by Dr Laura Tookman who said: ‘There is a wealth of patient data already captured in NHS systems which has the potential to give us hugely important insights into a variety of health problems. In the case of ovarian cancer, where symptoms can be difficult to distinguish from other diseases and therefore diagnosis can come very late, this data has the real potential to make a difference.

“Our project will take a dataset that is currently quite difficult to sift through and make it useful for clinicians, who we hope can then improve outcomes and reduce inequities for their patients through our findings.”

The results of the data analysis will be applied to clinical pathways to improve patient experience and outcomes.


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