In one of many health sector Big Data projects, Matogen Applied Insights (MAI) performed oncology data modelling for an international client.
Big Data in healthcare
The benefits and prevalence of Big Data in the healthcare sector are well-known, but it has been said that Big Data analytics can be considered a potential game-changer in the fight against cancer in particular. Previously, medical researchers had to rely on small sample sizes, case studies and relatively sparse tumour DNA or genetic analyses.
In contrast, the current availability of enormous publicly available databases containing a mind-boggling range of data on different types of cancers, across a spectrum of demographics, regions and genetic profiles, have rendered traditional analytics tools defunct. The advanced computer modelling and wrangling provided by data scientists make it possible to construct better predictive models for improved diagnosis and tailor-made treatment.
Oncological data modelling
In this project, oncological data was extracted from a large, publicly available, all-payer, inpatient healthcare database designed to produce regional and national estimates of inpatient utilisation, access, charges, quality, and outcomes for the United States.
The oncological data modelling determined which outcome was most probable in patients (based on their attributes) with breast cancer and what route of intervention to follow based on the result. For example, this aided oncologists in deciding whether to administer neoadjuvant chemotherapy or perform invasive surgery on the patient before administering chemo.
This study also interrogated the possibility of predicting the downstaging of a tumour and the level of lymphovascular invasion after neoadjuvant chemotherapy.