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How many people are diagnosed with diabetes in a given year? Is hypertension more common in men than in women? What drugs are most commonly prescribed for anemia?
In order to address questions like these and many more, Wolfram|Alpha has now assimilated data from two different surveys conducted by the CDC: the national ambulatory medical care survey (NAMCS) and its hospital-focused counterpart, the national hospital ambulatory medical care survey (NHAMCS). Together, these surveys provide information on common reasons why people visit the doctor’s office, drug treatments that are highly correlated with a particular disease, and which diseases are most commonly diagnosed within specific races, ethnicities, and genders.
Through Wolfram|Alpha, you can investigate data on thousands of diseases and medical conditions, such as these:
Instead of looking at all the information at once, you can also try more targeted inputs, such as “fraction of US population affected by lung cancer”:
From this output, we can see that approximately .21% of all U.S. patients are diagnosed with lung cancer each year.
Wolfram|Alpha also has data on patient-reported symptoms and other reasons for which patients visit their health care providers. These “reasons for visits” illustrate the wide variety of health complaints and co-occurring conditions that may be correlated with specific diagnoses. Some of these may be obvious, like “broken bone symptoms”:
However, you may be somewhat surprised to learn about some symptoms reported by patients with other conditions:
Besides symptoms, other reasons a person may have for visiting a health care provider can also be explored, such as diabetes patient lab test results, injuries suffered by asthma patients, and diseases that co-occur with hypertension.
The primary purposes of NAMCS and NHAMCS are to aid in the creation of public policy, track healthcare utilization, and allocate federal funds. The data is rich, extremely granular, and monumentally complex in structure, and at Wolfram|Alpha we want to make all such health-related data exploration easy. In the context of public health data sets, this goal involves applying various processing steps to convert the data from its raw format into a clean and logical structure that makes sense to the widest range of users. This involves not only consulting with health experts, but also with enthusiasts having little to no medical background who are interested in medically related issues and information.
Wolfram|Alpha contains a two-year chunk of data from the CDC, but we are working on loading data from more years. Since the release of this dataset on the site a few weeks ago, our feedback forms have been buzzing. We love suggestions, and would be thrilled to continue to hear how we can improve upon all the features for exploring the details of disease and patient populations through Wolfram|Alpha.
(Wolfram|Alpha does not give advice, medical or otherwise.)
Are you removing seasonality and/or displaying data at a per 1,000 patients per month annualized rate? Is that already taken into account in your source data?
Shifts in population and seasons can account for great fluctuations that are not taken into account by the common layperson.
Great step in providing some useful healthcare data to the general public!
At this time Wolfram|Alpha does not take into account shifts in population and seasons. We have shared your comments with the Development Team for further review. Thank you for the great feedback
I got “O” in every field when opening your first six links on diabetes, asthma
I’d love to be able to do “incidence Grave’s disease” and “prevalence Grave’s disease” — right now you only provide incidence data.
I can see that the folks at Wolfram Alpha have been busy improving their engine. I asked how much wood could a woodchuck chuck if a woodchuck could chuck wood perhaps a month or two ago, and the response was quite unsatisfactory. I am glad to see that this question has now been definitively answered, and that the developers have been paying attention to their customers’ need for woodchuck-related knowledge.
[…] diagnosis or drug treatment can often leave us with more questions than answers. A few weeks ago we introduced a disease dataset within Wolfram|Alpha that can be helpful for those wondering how their condition […]