This happens all the time. Example A, ripped from the headlines, is the kerfluffle over mammograms.
Let's go back to where this started. It was a population study, done on behalf of the U.S. Preventive Services Task Force, which concluded that the risk of unnecessary treatment exceeds the risk of death from annual screenings for the disease.
It was a science paper, and it was complicated, couched in the words scientists use to describe their work with precision.
Every profession has its version of this language. Engineers do, lawyers do, even software developers do. Learning the language gives a journalist entree into these professional worlds, but it's not an exercise most of us will, or should, go through.
Thus this study, like so many, was filtered through the lens of journalism. A flood of words failed to answer the questions women wanted answered
- What are the chances I will die from a late diagnosis?
- What are the chances I will suffer from over-diagnosis and over-treatment?
Calculate the threat to me so I can make a rational choice.
This is where technology comes into play. An Electronic Health Record (EHRs) can show you your own history, we can take your family history, we can analyze your genetic history, and we can estimate based on that.
If, that is, we have access to the larger pool of data. That's our baseline. It's what we need to compare your own data to before we can give you the answer you seek.
In scientific studies like this one we don't have access. The data is locked away somewhere. Mass adoption of EHRs is going to unleash a firehose of data, and the question should occur, very soon, what to do with it.
I'm not talking here about your record. I'm talking about the gross data, this warehouse of numbers describing everyone's condition, what is being done for us, and what the results are.
An open source attitude toward that data, within the realm of science and throughout the medical community, can help patients gain access to the benefits of that data and answer the question they ask -- what should I do?
Unfortunately medicine, health IT, and medical data all suffer from a proprietary attitude born of paranoia, the fear that you may be identified in this data mountain, that your needle will appear in this haystack, and that giving everyone access to data means giving them access to you.
A database, stripped of personal information, consisting of millions of records, is safe for use by software code. The data, and the code, are what we need to provide real answers.
We are collecting the data. We need to unlock it. We are writing the code. We need to share it.
This is what open source can teach the practice of medicine.