Predixion service could signal a trend for smaller health facilities.
Analytics are expensive and labor intensive; we need them to be routine and ubiquitous. I complained earlier this year that analytics are hard for health care providers to muster because there’s a shortage of analysts and because every data-driven decision takes huge expertise.
Currently, only major health care institutions such as Geisinger, the Mayo Clinic, and Kaiser Permanente incorporate analytics into day-to-day decisions. Research facilities employ analytics teams for clinical research, but perhaps not so much for day-to-day operations. Large health care providers can afford departments of analysts, but most facilities — including those forming accountable care organizations — cannot.
Imagine that you are running a large hospital and are awake nights worrying about the Medicare penalty for readmitting patients within 30 days of their discharge. Now imagine you have access to analytics that can identify about 40 measures that combine to predict a readmission, and a convenient interface is available to tell clinicians in a simple way which patients are most at risk of readmission. Better still, the interface suggests specific interventions to reduce readmissions risk: giving the patient a 30-day supply of medication, arranging transportation to rehab appointments, etc. Read more…
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.
Impressions from Strata Rx bolster different philosophies
Everyone seems to agree that health care is the next big industry waiting to be disrupted. But who will force that change on a massive system full of conservative players? Three possibilities present themselves:
Report from the Health Data Forum
Computing practices that used to be religated to experimental outposts are now taking up residence at the center of the health care field. From natural language processing to machine learning to predictive modeling, you see people promising at the health data forum (Health Datapalooza IV) to do it in production environments.
Harvard Medical School conference lays out uses for a health data platform
This week has been teaming with health care conferences, particularly in Boston, and was declared by President Obama to be National Health IT Week as well. I chose to spend my time at the second ITdotHealth conference, where I enjoyed many intense conversations with some of the leaders in the health care field, along with news about the SMART Platform at the center of the conference, the excitement of a Clayton Christiansen talk, and the general panache of hanging out at the Harvard Medical School.
SMART, funded by the Office of the National Coordinator in Health and Human Services, is an attempt to slice through the Babel of EHR formats that prevent useful applications from being developed for patient data. Imagine if something like the wealth of mash-ups built on Google Maps (crime sites, disaster markers, restaurant locations) existed for your own health data. This is what SMART hopes to do. They can already showcase some working apps, such as overviews of patient data for doctors, and a real-life implementation of the heart disease user interface proposed by David McCandless in WIRED magazine.
In the age of big data, Deven McGraw emphasizes trust, education and transparency in assuring health privacy.
Society is now faced with how to balance the privacy of the individual patient with the immense social good that could come through great health data sharing. Making health data more open and fluid holds both the potential to be hugely beneficial for patients and enormously harmful. As my colleague Alistair Croll put it this summer, big data may well be a civil rights issue that much of the world doesn’t know about yet.
This will likely be a tension that persists throughout my lifetime as technology spreads around the world. While big data breaches are likely to make headlines, more subtle uses of health data have the potential to enable employers, insurers or governments to discriminate — or worse. Figuring out shopping habits can also allow a company to determine a teenager was pregnant before her father did. People simply don’t realize how much about their lives can be intuited through analysis of their data exhaust.
To unlock the potential of health data for the public good, informed consent must mean something. Patients must be given the information and context for how and why their health data will be used in clear, transparent ways. To do otherwise is to duck the responsibility that comes with the immense power of big data.
In search of an informed opinion on all of these issues, I called up Deven McGraw (@HealthPrivacy), the director of the Health Privacy Project at the Center for Democracy and Technology (CDT). Our interview, lightly edited for content and clarity, follows. Read more…
Data science and technology give us the tools to revolutionize health care. Now we have to put them to use.
“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?
Copyright and intellectual disobedience, improving health IT integration, and pushing the envelope on digital images.
This week on O'Reilly: Artist Nina Paley explained her "intellectual disobedience" stance on copyright, Shahid Shah looked at the future of health IT integration, and illustrator Laura Maaske discussed the next generation of digital imagery.
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.
The future of desktops, ethics and big data, narrative vs spreadsheets.
This week on O'Reilly: Josh Marinacci predicted that 90% of computer users will rely on mobile, but 10% will still need desktops; the authors of "Ethics of Big Data" explored data's trickiest issues; and Narrative Science CTO Kris Hammond discussed narrative's role in data analytics.