Tag: Real-time measurement

A Crystal Ball for Medicine

HamlinB_SON_DMG_2010_9143_150x200 (1)Twenty years is a long time to rely on one measurement approach. Imagine if in this technology-centric world we still relied on dial-up to connect to the internet. That’s basically where we are on quality assessment today. But we don’t need to be.

Predictive risk calculations allow doctors to look into the future. A risk score tells doctors how likely their patient is to develop heart disease or have a stroke. Working with their patients, doctors can discuss options for lowering this risk with the goal of preventing such events from happening.

With data from electronic health records, we should be able to create risk profiles for individual patients that actually take into account the different factors affecting their personal health—not just their age and gender, but their family history, whether or not they smoke, what medications and treatments they are receiving, and their own perspective on how they feel.

But right now, a 50 year old woman’s risk of developing heart disease is determined by a threshold set for the entire population of women aged 50-65 across the country. That’s a crude science. Everyone is not built the same. We should create risk profiles that change as patients change: as they reduce their risk by losing weight, quit smoking, or lowering their high blood pressure, thus reducing their chances of a heart attack or other adverse event.

That’s the vision of NCQA’s Global Cardiovascular Risk Score (GCVR). Leveraging the pioneering risk prediction work of Archimedes, it extracts data from electronic health records and uses a sophisticated algorithm to generate a highly sensitive, patient-centric risk profile for each clinician. It works like this: the higher the score the less likely a clinician’s patient will develop heart problems in the next five years.

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