"electronic health record" entries
Finding the Meaning in “Meaningful Use”
The 30,000-foot view and the nitty gritty details of working with electronic health data
Ever wonder what the heck “meaningful use” really means? By now, you’ve probably heard it come up in discussions of healthcare data. You might even know that it specifically pertains to electronic health records (EHRs). But what is it really about, and why should you care?
If you’ve ever had to carry a large folder of paper between specialists, or fill out the same medical history form in different offices over and over—with whatever details you happen to remember off the top of your head that day—then you already have some idea of why EHRs are a desirable thing. The idea is that EHRs will lead to better care—and better research data—through more complete and accurate record-keeping, and will eventually become part of health information exchanges (HIEs) with features like trend analysis and push-notifications. However, the mere installation of EHR software isn’t enough; we need not just cursory use but meaningful use of EHRs, and we need to ensure that the software being used meets certain standards of efficiency and security.
When data disrupts health care
The convergence of data, privacy and cost have created a unique opportunity to reshape health care.
Health care appears immune to disruption. It’s a space where the stakes are high, the incumbents are entrenched, and lessons from other industries don’t always apply.
Yet, in a recent conversation between Tim O’Reilly and Roger Magoulas it became evident that we’re approaching an unparalleled opportunity for health care change. O’Reilly and Magoulas explained how the convergence of data access, changing perspectives on privacy, and the enormous expense of care are pushing the health space toward disruption.
As always, the primary catalyst is money. The United States is facing what Magoulas called an “existential crisis in health care costs” [discussed at the 3:43 mark]. Everyone can see that the current model is unsustainable. It simply doesn’t scale. And that means we’ve arrived at a place where party lines are irrelevant and tough solutions are the only options.
“Who is it that said change happens when the pain of not changing is greater than the pain of changing?” O’Reilly asked. “We’re now reaching that point.” [3:55]
(Note: The source of that quote is hard to pin down, but the sentiment certainly applies.)
This willingness to change is shifting perspectives on health data. Some patients are making their personal data available so they and others can benefit. Magoulas noted that even health companies, which have long guarded their data, are warming to collaboration.
At the same time there’s a growing understanding that health data must be contextualized. Simply having genomic information and patient histories isn’t good enough. True insight — the kind that can improve quality of life — is only possible when datasets are combined.
Solving the Wanamaker problem for health care
Data science and technology give us the tools to revolutionize health care. Now we have to put them to use.
By Tim O’Reilly, Julie Steele, Mike Loukides and Colin Hill
“The best minds of my generation are thinking about how to make people click ads.” — Jeff Hammerbacher, early Facebook employee
“Work on stuff that matters.” — Tim O’Reilly
In the early days of the 20th century, department store magnate John Wanamaker famously said, “I know that half of my advertising doesn’t work. The problem is that I don’t know which half.”
The consumer Internet revolution was fueled by a search for the answer to Wanamaker’s question. Google AdWords and the pay-per-click model began the transformation of a business in which advertisers paid for ad impressions into one in which they pay for results. “Cost per thousand impressions” (CPM) was outperformed by “cost per click” (CPC), and a new industry was born. It’s important to understand why CPC outperformed CPM, though. Superficially, it’s because Google was able to track when a user clicked on a link, and was therefore able to bill based on success. But billing based on success doesn’t fundamentally change anything unless you can also change the success rate, and that’s what Google was able to do. By using data to understand each user’s behavior, Google was able to place advertisements that an individual was likely to click. They knew “which half” of their advertising was more likely to be effective, and didn’t bother with the rest.
Since then, data and predictive analytics have driven ever deeper insight into user behavior such that companies like Google, Facebook, Twitter, and LinkedIn are fundamentally data companies. And data isn’t just transforming the consumer Internet. It is transforming finance, design, and manufacturing — and perhaps most importantly, health care.
How is data science transforming health care? There are many ways in which health care is changing, and needs to change. We’re focusing on one particular issue: the problem Wanamaker described when talking about his advertising. How do you make sure you’re spending money effectively? Is it possible to know what will work in advance?
The state of Health Information Exchange in Massachusetts
Health IT and HIE advances in Massachusetts may lead to national shifts.
Although health information exchange should be identified as a process, having the structures and organizations to facilitate exchange is a challenge facing health care. A recent conference articulated these issues, and presented clear plans on how Massachusetts is addressing them.
Are EHRs safe?
Electronic health records are fundamentally dangerous. They're also safer than the current model.
As a society, we need to get comfortable with the notion that Electronic Healthcare Records will both help and hurt people. On balance, they will do far more good than harm.