I read with interest yesterday’s report in the Lancet highlighting the spiralling global costs of cancer treatment, with 12 million people diagnosed with cancer worldwide costing £185bn ($295bn) per year. The report goes on to say that most developed countries are spending between 4% and 7% of their healthcare budgets just on treating cancer.
The complexity of the market is partially to blame for this growing expense – there were 35 approved cancer drugs in 1970, now there are nearly 100, not to mention the additional imaging and biomarker options that are increasingly available to better diagnose disease and monitor treatment efficacy.
We all know that successful, affordable treatment of cancer requires analysis of patient data to compare treatments, side effects and outcomes. What this takes is access to high quality data about a patient’s medical history, treatments and lab results. This is a significant data integration challenge requiring data extraction from multiple systems and clinically orientated integration of that data. Importantly appropriate pseudonymisation of patient records is also vital in using such information for research purposes.
This is still a major problem for Healthcare organisations, governments, payers and providers. Here’s a typical question we need to be able to answer today:
“How many patients with Triple Negative Breast Cancer were treated with Cytoxan and Taxol and what are their outcomes, ethnicity, exercise, drinking, smoking, and dietary profiles? And then let’s look at their genomic profiles.”
Access to this type of data and analytics, such as Kaplan Meier survival curves, is essential to improved outcomes for cancer patients.
Too often though this is just too hard, because it is a task of epic proportions, pulling data together from files and basic spreadsheets.
We can all celebrate the success of HER2 tests for Herceptin and KRAS for Vectibix, in fact the report mentions a Japanese KRAS study that showed a £32m ($51m) per year saving for treatment of colorectal cancer using this test. However, Personalised Medicine is still a long way off, and while IDBS is helping advance these capabilities, we are also able to support more immediate needs to improve treatment selection and outcomes.
Here at IDBS we are actively supporting the integration and analysis of patient data with many of the leaders in this field of study, including King’s Health Partners in the UK and Windber Medical Center in the USA. Our systems enable clinicians and clinical researchers to quickly select groups (or cohorts) of patients and see a timeline of their diagnosis, treatment, risks and outcomes. This is enabling technology for clinicians worldwide and more importantly for today’s and tomorrow’s cancer patients.