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Fred Trotter:Data,damn data,and statistics–Kathleen O’Malley

Why does this blog use the word “damn”so often? A search produces a whopping 38 hits,such as:

These and other “damning”articles deal with statistics,so no wonder our normally polite bloggers would resort to swearing. How our health care data is used and by whom is incredibly important to e-patients,and the fact that much of this is out of our hands rouses a lot of emotion.

This post by guest blogger Fred Trotter originated in an SPM members’listserv thread that debated which is scarier:the theft or loss of data or the intentional use of health care data by third parties?

There is a lot of danger in “legal but unethical”secondary data use. It is a far greater threat than hackers who steal health care data,IMHO.

I do want to point out,however,that there may be some benefits to a well-managed and ethical “health credit score”concept.

Consider how fundamentally unfair and inaccurate the current credit score system is (the normal one). But that system has created a backbone where normal people in the United States have real-time access to credit decisions. In practical life,this means that if you have decent credit but no money,and you need a sofa,you can get a sofa now. You can use that data liquidity to buy a boat or you can use it to buy a laptop for your new business.

In other countries,personal credit is unworkable because they do not have an effective system for ensuring that people will pay back debt (i.e.,not paying it back will hurt their credit scores and limit future purchasing options).

From a health care perspective,that is where we are in the US;we are paralyzed. Without a health credit score,people who are disciplined about their health (i.e.,e-patients) end up paying for people who are less disciplined. This creates a crazy incentive where healthy people have strong financial motivation to not get health insurance at all. Which of course makes it more expensive for everyone.

The individual mandate is an alternative approach to a “health credit score,”but it may not survive politically. If it does not,a health credit score might be an important enabler for ensuring that healthy people participate in insurance pools,which is a critical issue.

The real problem here is that the distance between an unethical system which penalizes the sick for just being sick (which is what we have now in any case) and an innovative system where being an e-patient pays off is just a hair’s breadth …and may in fact require the use of precisely the same data.

I do not want to pretend that I have a deep understanding of these issues. I certainly do not. But as a community,e-patients really need to begin grappling with these delicate data-use-balance issues.

The e-patient community is really one of the few that has a tractable notion of what a “high performing patient”might look like. But insurance companies,economists,policy makers,doctors,congresspeople,and lobbyists are all using other models to make assumptions about what patients might be capable of. I am convinced that many of these assumptions are untenable even for high-functioning patients,much less patients of average education and motivation.

Given the scientific approach that I and other “N=1/Quantified Self”e-patients have taken in trying to improve our personal health or wellbeing,I submit that if none of us can vouch for an assumption being made about patients,it is probably a bad assumption. How do we communicate this sort of correction to policy makers? How do we continue to discharge the “patient scientist”portion of the e-patient philosophy in a way that helps policy makers make good decisions? How do we ensure that patient data is used fairly?

Hell if I know.


e-Patients.net

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