ENTRIES TAGGED "healthcare"
How do we motivate sustained behavior change when the external motivation disappears—like it's supposed to?
If you’ve ever tried to count calories, go on a diet, start a new exercise program, change your sleep patterns, spend less time sitting, or make any other type of positive health change, then you know how difficult it is to form new habits. New habits usually require a bit of willpower to get going, and we all know that that’s a scarce resource. (Or at least, a limited one.)
Change is hard. But the real challenge comes after you’ve got a new routine going—because now you’ve got to keep it going, even though your original motivations to change may no longer apply. Why keep dieting when you no longer need to lose weight? We’ve all had the idea at some point that we really should reward ourselves for that five-pound weight loss with a cupcake, right?
When the death of trust meets the birth of BYOD
Dr. Andrew Litt, Chief Medical Officer at Dell, made a thoughtful blog post last week about the trade-offs inherent in designing for both the security and accessibility of medical data, especially in an era of BYOD (bring your own device) and the IoT (internet of things). As we begin to see more internet-enabled diagnostic and monitoring devices, Litt writes, “The Internet of Things (no matter what you think of the moniker), is related to BYOD in that it could, depending on how hospitals set up their systems, introduce a vast array of new access points to the network. … a very scary thought when you consider the sensitivity of the data that is being transmitted.”
As he went on to describe possible security solutions (e.g., store all data in central servers rather than on local devices), I was reminded of a post my colleague Simon St.Laurent wrote last fall about “security after the death of trust.” In the wake of some high-profile security breaches, including news of NSA activities, St.Laurent says, we have a handful of options when it comes to data security—and you’re not going to like any of them.
A video interview with Colin Hill
Last month, Strata Rx Program Chair Colin Hill, of GNS Healthcare, sat down with Dr. Dennis Ausiello, Jackson Professor of Clinical Medicine at the Harvard Medical School, Co-Director at CATCH, Pfizer Board of Directors Member, and Former Chief of Medicine at the Massachusetts General Hospital (MGH), for a fireside chat at a private reception hosted by GNS. Their insightful conversation covered a range of topics that all touched on or intersected with the need to create smaller and more precise cohorts, as well as the need to focus on phenotypic data as much as we do on genotypic data.
The full video appears below.
There is a storm brewing in Healthcare. Doctors have been in charge of healthcare for a long time, and have become comfortable, sometimes even arrogant, with their authority and power. But dumb data beats smart doctors every time. Forward thinking doctors are embracing data, with surprising grace and humility. Others are having much more trouble adjusting.
Doctors, historically, have been the “end of the discussion” on clinical matters. Doctors make the diagnosis, they make the calls in the surgery suite, they get to decide if someone is suffering enough to justify pain medications, they frequently decide whether someone is mentally incompetent or merely eccentric. Our society places a lot of trust in doctors, because they have the training needed to make really hard choices.
Doctors, as a group, have been in charge of how healthcare operates for centuries. In times past, the only way to determine whether a doctor was doing a good job was to become a doctor yourself, and then perform case reviews. Even in court, if you wanted to refute a doctor, you needed another doctor.
Increasingly available data spurs organizations to make analysis easier
Genomics is making headlines in both academia and the celebrity world. With intense media coverage of Angelina Jolie’s recent double mastectomy after genetic tests revealed that she was predisposed to breast cancer, genetic testing and genomics have been propelled to the front of many more minds.
In this new data field, companies are approaching the collection, analysis, and turning of data into usable information from a variety of angles.
In which the question of whether research subjects have any rights to their data is pondered.
The GET (Genomes, Environments and Traits) conference is a confluence of parties interested in the advances being made in human genomes, the measurement of how the environment impacts individuals, and how the two come together to produce traits. Sponsored by the organizers of the Personal Genome Project (PGP) at Harvard, it is a two-day event whose topics range from the appropriate amount of access that patients should have to their genetics data to the ways that Hollywood can be convinced to portray genomics more accurately.
It also is a yearly meeting place for the participants in the Personal Genome Project (one of whom is your humble narrator), people who have agreed to participate in an “open consent” research model. Among other things, this means that PGP participants agree to let their cell lines be used for any purposes (research or commercial). They also acknowledge ahead of time that because their genomes and phenotypic traits are being released publicly, there is a high likelihood that interested parties may be able to identify them from their data. The long term goal of the PGP is to enroll 100,000 participants and perform whole genome sequencing of their DNA, they currently have nearly 2,300 enrolled participants and have sequenced around 165 genomes.
How our vision for this important conference is shaping the program we hope to present, and how you can get involved
After a strong inaugural event in October 2012, Strata Rx is heading into its second year. My fellow chair, Colin Hill, and I have spent a lot of time thinking about and discussing what we’d like to see on the program this year, and I thought I’d share some of those thoughts for anyone considering submitting a proposal or attending the event. (The Call for Proposals is currently open until April 10.)
One of the most interesting challenges in creating a program about data science in healthcare has been deciding what to leave out. Topics like genomics and cancer research are so vast and complex that they can and do have entire conferences about just them. While we won’t reject a talk for centering on a topic like this, it has to be relevant to one of our larger goals, as well.
What we hope to accomplish with Strata Rx
So what are those larger goals? Well, here are a few of the key ones.
Promote dialog across silos
Right now, there are already a lot of niche conferences for specific groups in healthcare. There are events for specific areas of research, such as oncology and genomics, as previously mentioned. There are also events for specific kinds of people, like pharmaceutical reps, or insurance providers. Those conferences that do cut across the industry are only for one level of people, such as Chief Officers.
We want Strata Rx to convene a broad swath of people with an interest and a stake in the healthcare system: researchers, funders, providers, application developers, patient advocates, board members, insurers, IT staff, legislators, and everyone in between. By starting conversations among these different specialists, and by combining their relative expertise, we believe we can build a stronger community that is better able to solve problems.
We aim to be fire-starters, igniting connections and conversations.
An interview with Fred Smith of the CDC on their open content APIs.
Health care data liquidity (the ability of data to move freely and securely through the system) is an increasingly crucial topic in the era of big data. Most conversations about data liquidity focus on patient data, but other kinds of information need to be able to move freely and securely, too. Enter several government initiatives, including efforts at agencies within the Department of Health and Human Services (HHS) to make their content more easily available.
Fred Smith is team lead for the Interactive Media Technology Team in the Division of News and Electronic Media in the Office of the Associate Director for Communication for the U.S. Centers for Disease Control and Prevention (CDC) in Atlanta. We recently spoke by phone to discuss ways in which the CDC is working to make their information more “liquid”: easier to access, easier to repurpose, and easier to combine with other data sources.
Which data is available from the CDC APIs?
Fred Smith: In essence, what we’re doing is taking our unstructured web content and turning it into a structured database, so we can call an API into it for reuse. It’s making our content available for our partners to build into their websites or applications or whatever they’re building.
Todd Park likes to talk about “liberating data” — well, this is liberating content. What is a more high-value dataset than our own public health messaging? It incorporates not only HTML-based text, but also we’re building this to include multimedia — whether it’s podcasts, images, web badges, or other content — and have all that content be aware of other content based on category or taxonomy. So it will be easy to query, for example: “What content does the CDC have on smoking prevention?”
Five ways we can improve the information we collect to help us solve hard problems in health care.
I was honored to chair O’Reilly’s inaugural edition of Strata Rx, our conference on data science in health care, this past October along with Colin Hill. As we’re beginning to plan this year’s event, I find myself thinking a lot about a theme that emerged from some of the keynotes last fall: in order to solve the problems we’re facing in health care — to lower costs and provide more personal, targeted treatments to patients — we don’t just need more data; we need better data.
Much has been made about the era of big data we find ourselves in. But though the data we collect is straining the limits of our tools and models, we’re still not making the kind of headway we hoped for in areas like health care. So big data isn’t enough. We need better data.
What does it mean to have better data in health care? Here are some things on my list; perhaps you can think of others. Read more…