"medical" entries

Four short links: 24 March 2015

Four short links: 24 March 2015

Tricorder Prototype, Web Performance, 3D Licensing, and Network Simulation

  1. Tricorder Prototypecollar+earpiece, base station, diagnostic stick (lab tests for diabetes, pneumonia, tb, etc), and scanning wand (examine lesions, otoscope for ears, even spirometer). (via Slashdot)
  2. Souders Joins SpeedcurveDuring these engagements, I’ve seen that many of these companies don’t have the necessary tools to help them identify how performance is impacting (hurting) the user experience on their websites. There is even less information about ways to improve performance. The standard performance metric is page load time, but there’s often no correlation between page load time and the user’s experience. We need to shift from network-based metrics to user experience metrics that focus on rendering and when content becomes available. That’s exactly what Mark is doing at SpeedCurve, and why I’m excited to join him.
  3. 3 Steps for Licensing Your 3D-Printed Stuff (PDF) — this paper is not actually about choosing the right license for your 3D printable stuff (sorry about that). Instead, this paper aims to flesh out a copyright analysis for both physical objects and for the digital files that represent them, allowing you to really understand what parts of your 3D object you are—and are not—licensing. Understanding what you are licensing is key to choosing the right license. Simply put, this is because you cannot license what you do not legally control in the first place. There is no point in considering licenses that ultimately do not have the power to address whatever behavior you’re aiming to control. However, once you understand what it is you want to license, choosing the license itself is fairly straightforward. (via BoingBoing)
  4. Augmented Traffic Control — Facebook’s tool for simulating degraded network conditions.
Four short links: 10 March 2015

Four short links: 10 March 2015

Robot Swarms, Media Hacking, Inside-Out Databases, and Quantified Medical Self

  1. Surgical Micro-Robot SwarmsA swarm of medical microrobots. Start with cm sized robots. These already exist in the form of pillbots and I reference the work of Paolo Dario’s lab in this direction. Then get 10 times smaller to mm sized robots. Here we’re at the limit of making robots with conventional mechatronics. The almost successful I-SWARM project prototyped remarkable robots measuring 4 x 4 x 3mm. But now shrink by another 3 orders of magnitude to microbots, measured in micrometers. This is how small robots would have to be in order to swim through and access (most of) the vascular system. Here we are far beyond conventional materials and electronics, but amazingly work is going on to control bacteria. In the example I give from the lab of Sylvain Martel, swarms of magnetotactic bacteria are steered by an external magnetic field and, interestingly, tracked in an MRI scanner.
  2. Media Hacking — interesting discussion of the techniques used to spread disinformation through social media, often using bots to surface/promote a message.
  3. Turning the Database Inside Out with Apache Samzareplication, secondary indexing, caching, and materialized views as a way of getting into distributed stream processing.
  4. Apple Research Kit — Apple positioning their mobile personal biodata tools with medical legitimacy, presumably as a way to distance themselves from the stereotypical quantified selfer. I’m reminded of the gym chain owner who told me, about the Nike+, “yeah, maybe 5% of my clients will want this. The rest go to the gym so they can eat and drink what they want.”

Health games platforms mature in preparation for mainstream adoption

Business models and sustainability will drive success in the health games space.


SPARX, a behavioral therapy game for youths,
combines a fantasy setting with skills for life.

For the past several years, researchers have strived to create compelling games that improve behavior, reduce stress, or teach healthy responses to difficult life situations. Such healthy games tend to arise in research settings because of the need to demonstrate clinically that the games are effective. I have covered such efforts in my postings from the Games for Health conference in 2012 and 2013.

These efforts have born fruit, and clinical trials have shown the value of many such games. Ben Sawyer, who founded the Games for Health conference more than 10 years ago, is watching all the pieces fall into place for the widespread adoption of games. Business plans, platforms, and the general environment for the acceptance of games (and other health-related apps) are coming together.

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Where did the issue of health data exchange disappear to?

More visible at Health Privacy Summit than Health Datapalooza.

On the first morning of the biggest conference on data in health care–the Health Datapalooza in Washington, DC–newspapers reported a bill allowing the Department of Veterans Affairs to outsource more of its care, sending veterans to private health care providers to relieve its burdensome shortage of doctors.

There has been extensive talk about the scandals at the VA and remedies for them, including the political and financial ramifications of partial privatization. Republicans have suggested it for some time, but for the solution to be picked up by socialist Independent Senator Bernie Sanders clinches the matter. What no one has pointed out yet, however–and what makes this development relevant to the Datapalooza–is that such a reform will make the free flow of patient information between providers more crucial than ever.

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Sequencing, cloud computing, and analytics meet around genetics and pharma

Bio-IT World shows what is possible and what is being accomplished

If your data consists of one million samples, but only 100 have the characteristics you’re looking for, and if each of the million samples contains 250,000 attributes, each of which is built of thousands of basic elements, you have a big data problem. This is kind of challenge faced by the 2,700 Bio-IT World attendees, who discover genetic interactions and create drugs for the rest of us.

Often they are looking for rare (orphan) diseases, or for cohorts who share a rare combination of genetic factors that require a unique treatment. The data sets get huge, particularly when the researchers start studying proteomics (the proteins active in the patients’ bodies).

So last week I took the subway downtown and crossed the two wind- and rain-whipped bridges that the city of Boston built to connect to the World Trade Center. I mingled for a day with attendees and exhibitors to find what data-related challenges they’re facing and what the latest solutions are. Here are some of the major themes I turned up.

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Comment: 1

Citizens as partners in the use of clinical data

A Knowledge Currency Exchange for health and wellness

This article was written together with Mike Kellen, Director of Technology at Sage Bionetworks, and Christine Suver, Senior Scientist at Sage Bionetworks.

The current push towards patient engagement, when clinical researchers trace the outcomes of using pharmaceuticals or other treatments, is a crucial first step towards rewiring the medical-industrial complex with the citizen at the center. For far too long, clinicians, investigators, the government, and private funders have been the key decision makers. The citizen has been at best a research “subject,”and far too often simply a resource from which data and samples can be extracted. The average participant in clinical study never receives the outcomes of the study, never has contact with those analyzing the data, never knows where her samples flow over time (witness the famous story of Henrietta Lacks), and until the past year didn’t even have access to the published research without paying a hefty rental fee.

This is changing. The recent grants by the Patient-Centered Outcomes Research Institute (PCORI) are the most visible evidence of change, but throughout the medical system one finds green shoots of direct patient engagement. Read more…


Changes in the health care system driven by self-service and DIY health

Apps reflect the public's pressing health concerns

Health care is migrating from the bricks-and-mortar doctor’s office or care clinic to the person him or herself at home and on-the-go–where people live, work, play, and pray. As people take on more do-it-yourself (DIY) approaches to everyday life–investing money on financial services websites, booking airline tickets and hotel rooms online, and securing dinner reservations via OpenTable–many also ask why they can’t have more convenient access to health care, like emailing doctors and looking into lab test results in digital personal health records.

The public clamor for digital outreach by health providers

85% of U.S. health consumers say that email, text messages, and voicemail are at least as helpful as in-person or phone conversations with health providers, according to the Healthy World study, Technology Beyond the Exam Room by TeleVox. Furthermore, one in three consumers admits to being more honest when talking about medical needs via automated voice response systems, emails, or texts than face-to-face with a health provider.

And three in ten consumers believe that receiving digital health care communications from providers—such as texts, voicemail, or email—would build trust with their providers. Half of people also say they’d feel more valued as a patient via digital health communications. When people look to engage in health with an organization, the most important enabling factors are trust and authenticity.

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Visualizing Health IT: A holistic overview

O'Reilly report covers major trends and tries to connect the neurons

If visualization is key to comprehending data, the field of health IT calls for better visualization. I am not talking here of pretty charts and animations. I am talking, rather, of a holistic, unified understanding of the bustle taking place in different corners of health: the collection and analysis of genetic data, the design of slim medical devices that replace refrigerator-sized pieces of equipment, the data crunching at hospitals delving into demographic data to identify at-risk patients.

There is no dearth of health reformers offering their visions for patient engagement, information exchange, better public health, and disruptive change to health industries. But they often accept too freely the promise of technology, without grasping how difficult the technical implementations of their reforms would be. Furthermore, no document I have found pulls together the various trends in technology and explores their interrelationships.

I have tried to fill this gap with a recently released report: The Information Technology Fix for Health: Barriers and Pathways to the Use of Information Technology for Better Health Care. This posting describes some of the issues it covers.

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Can data provide the trust we need in health care?

Collecting actionable data is a challenge for today's data tools

One of the problems dragging down the US health care system is that nobody trusts one another. Most of us, as individuals, place faith in our personal health care providers, which may or may not be warranted. But on a larger scale we’re all suspicious of each other:

  • Doctors don’t trust patients, who aren’t forthcoming with all the bad habits they indulge in and often fail to follow the most basic instructions, such as to take their medications.
  • The payers–which include insurers, many government agencies, and increasingly the whole patient population as our deductibles and other out-of-pocket expenses ascend–don’t trust the doctors, who waste an estimated 20% or more of all health expenditures, including some thirty or more billion dollars of fraud each year.
  • The public distrusts the pharmaceutical companies (although we still follow their advice on advertisements and ask our doctors for the latest pill) and is starting to distrust clinical researchers as we hear about conflicts of interest and difficulties replicating results.
  • Nobody trusts the federal government, which pursues two (contradictory) goals of lowering health care costs and stimulating employment.

Yet everyone has beneficent goals and good ideas for improving health care. Doctors want to feel effective, patients want to stay well (even if that desire doesn’t always translate into action), the Department of Health and Human Services champions very lofty goals for data exchange and quality improvement, clinical researchers put their work above family and comfort, and even private insurance companies are trying moving to “fee for value” programs that ensure coordinated patient care.

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Comments: 2

Healthcare Lessons from the Data Sages at Strata

Other industries can show health care the way

This article was written with Ellen M. Martin.

Most healthcare clinicians don’t often think about donating or sharing data. Yet, after hearing Stephen Friend of Sage Bionetworks talk about involving citizens and patients in the field of genetic research at StrataRx 2012, I was curious to learn more.

McKinsey points out the 300 billion dollars in potential savings from using open data in healthcare, while a recent IBM Institute of Business Value study showed the need for corporate data collaboration.

Also, during my own research for Big Data in Healthcare: Hype and Hope, the resounding request from all the participants I interviewed was to “find more data streams to analyze.”

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