Wolfram|Alpha Medical Test Data
One of Wolfram|Alpha’s primary sources for medical test data is the National Health and Nutritional Examination Survey (NHANES), an annual survey of thousands of people, from throughout the United States, conducted by the National Center for Health Statistics (NCHS). Wolfram|Alpha’s presentation of this data is unique in that it doesn’t just report reference ranges, but allows you to see where your own measurements and test numbers fall within the survey’s distribution of results. (Wolfram|Alpha does not give advice, medical or otherwise.)
At the most basic level, an input of “cholesterol test” returns the survey’s distribution of total cholesterol values:
If you add your own test results, e.g., “cholesterol test 160,” Wolfram|Alpha creates a plot line marking your test results within the overall distribution:
You can fine-tune the results even more by adding additional personal attributes. For example, entering “cholesterol tests age 65” filters the general population distribution to return only values from individuals 60–70 years old:
By adding more filters such as smoking status, diabetic status, pregnancy status, and other individual characteristics, you can find out more about how your test results compare to other populations covered by NHANES.
For physicians, Wolfram|Alpha an be a useful aid in explaining test results, making it easy to visualize how a patient’s test values compare not only to the general population, but more importantly, to specific subpopulations. For example, describing a low-density lipoprotein (LDL) cholesterol level of 150 as “higher than normal” may or may not influence a patient to make changes to improve their health:
When the same patient’s value is shown to be higher than the average for a population composed entirely of smokers or morbidly obese individuals, or obese smokers, the visualization of those test results may have a greater impact.
Wolfram|Alpha’s medical test data also serves as an excellent ready reference for anyone interested in general health issues in the U.S., or in understanding the relative health risks confronted by people with different lifestyle habits or physical characteristics. For example, simple queries can highlight the difference in reference ranges between men and women for high-density lipoprotein (HDL) cholesterol levels or other blood constituents, such as serum sodium.
These examples demonstrate just a few ways you can use Wolfram|Alpha as a resource to help assess your own health, and to better understand the significance of medical test results. We welcome your suggestions and requests for additional data, and encourage you to check back periodically for new and improved features. If you are interested in contributing to Wolfram|Alpha’s medical data, we encourage you to join our growing team of advisers, experts, and volunteer curators.