What has already been done in health reform

What data does is improve care and drive down costs. The medical profession has systems for using such data, procedures going back decades, but this use is often hampered by the small numbers of people under study.

While the Senate debates health reform with itself (and perhaps later the House) it's a good time to look at what has already been done regarding health reform. (The picture is from pro-Administration blogger Tim Foley.)

There are two important acts worth looking at:

  1. ARRA, or the Obama Stimulus, included $19.2 billion in funding called the HITECH Act, aimed at getting doctors and hospitals to use electronic health records (EHRs).
  2. GINA, the Genetic Information Nondiscrimination Act, becomes the law of the land this weekend.

Both these laws are important for unexpected reasons.


The most important medical research being done today is based on data. Groups like the Framingham Heart Study continue to offer insights, 60 years after the study was begun.

Imagine what researchers can do with this firehose of data. Want to compare treatments of acne in 12 year olds? You'll have data on millions to look at. Want to look at a relatively rare form of cancer? Thousands of case studies will be on file.

This has the potential to revolutionize medical research. We can learn which treatments work, and which don't, with the high accuracy of large numbers. We can learn precisely how drugs are doing in the field, get solid numbers of specific side-effects, and adjust medical practice to try what works first.

Even though this kind of science, called comparative effectiveness, can't be used to drive specific decisions (thanks to a compromise made by Congress) it can still deliver gross data that can advise doctors precisely on what is working and what isn't.

Medical societies of all types, who already use such "population studies" to advise professionals on what to do, will be able to make those calls with much greater precision than ever before.

We will also be able to compare what high-cost areas are doing with what low-cost areas are doing, based on hard data, as well as compare the effectiveness of each approach. Insurance companies are bound to use this to push for decisions based on data rather than gut feel, saving billions of dollars without putting patients at risk.


GINA purports to be about limits on the use of data, but is actually designed to facilitate the collection of it.

Before the law was passed, in 2008, most Americans were afraid to get genetic testing because their employers or insurers might use the data against them. This not only stops that cold, but prevents discrimination in hiring, insurance rates, or promotion based on your family's medical history.

This gives the go-ahead for the whole genetic testing industry. And when genetic testing becomes a mass market, we then have data that does just what ARRA data does, only at a much deeper level.

We'll be able to trace, over time, the chances that specific genetic abnormalities will result in specific diseases. We can also use genetic markers to drive personal care, and to create new types of therapy based on genetic research.

What data does is improve care and drive down costs, assuming the data is used properly. The medical profession has systems for using such data, procedures going back decades, but this use is often hampered by the small numbers of people under study.

Take the recent study linking niacin to low cholesterol, and to better results than with Merck's Zetia anti-cholesterol drug in terms of unblocking arteries. Doctors, pharmacists and drug companies may argue that too few people were studied, and thus the results should be thrown out.

No more. Now population studies can begin using data from tens of millions of us. And when you're doing population studies of that size, even small differences in percentages can drive solid decision-making.

Take last year's Accelerate study, which indicated that one combination of hypertension drugs was better than what is commonly prescribed. The study was ended when it was found that two more in every hundred people within the 11,000-person study group was having an "adverse event," like a heart attack or stroke.

Do the math. Figure 11% of 11,000 is 1,200, and 9% of 11,000 is about 1,000. That's a pretty small margin, driving a big decision impacting millions.

Now you can eliminate the uncertainty, because you will have data on tens of millions of people to look at.

This is a revolution in health care, one that starts now and will impact us for decades. And it doesn't matter what the Senate does -- it's already baked-in.

This post was originally published on Smartplanet.com