ENTRIES TAGGED "medical"

Using Big Data and Game Play to Improve Mental Fitness

Digital tools and data analysis to stay sharp, stay well, and overcome illness

This article was written together with Ellen M. Martin and Melinda Speckmann.

Games have been part of human culture for millennia. It is no surprise that elements of play can be powerful digital tools to grab our attention and keep us on a path to taking care of ourselves and others.

Big data is already behind brain games. The use of big data is becoming increasingly mainstream in health play applications. Once we are drawn in, game play (with big data under the hood) can help us to:

  1. Stay sharp,
  2. Stay well, and
  3. Overcome illness.

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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.

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23andMe flap at FDA indicates fundamental dilemma in health reform

We must go beyond hype for incentives to provide data to researchers

The FDA order stopping 23andM3 from offering its genetic test kit strikes right into the heart of the major issue in health care reform: the tension between individual care and collective benefit. Health is not an individual matter. As I will show, we need each other. And beyond narrow regulatory questions, the 23andMe issue opens up the whole goal of information sharing and the funding of health care reform.

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Geographic data is the glue for public health and treatment

Esri conference highlights uses of GIS data

We’ve all seen cool maps of health data, such as these representations of diabetes prevalence by US county. But few people think about how thoroughly geospacial data is transforming public health and changing the allocation of resources at individual hospitals. I got a peek into this world at the Esri Health GIS Conference this week in Cambridge, Mass.

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Where are the chances for change in health care – top-down or bottom-up?

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:

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Ticking all the boxes for a health care upgrade at Strata Rx

What is needed for successful reform of the health care system?

Here’s what we all know: that a data-rich health care future is coming our way. And what it will look like, in large outlines. Health care reformers have learned that no single practice will improve the system. All of the following, which were discussed at O’Reilly’s recent Strata Rx conference, must fall in place.

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Building the Brain of Dr. Algorithm

Archimedes advances evidence-based medicine to foster model-based medicine

This posting is by guest author Tuan Dinh, who will speak about this topic at the Strata Rx conference.

Legendary Silicon Valley investor Vinod Khosla caused quite a stir last year when he predicted at Strata Rx that “Dr. Algorithm”–artificial intelligence driven by large data sets and computational power–would replace doctors in the not-too-distant future. At that point, he said, technology will be cheaper, more accurate and objective, and will ultimately do a better job than the average human doctor at delivering routine diagnoses with standard treatments.

I not only support Khosla’s provocative prophecy, I’ll add one of my own: that Dr. Algorithm (aka Dr. A) will “come to life” in three to five years, by the time today’s first-year med school students are pulling 30-hour shifts as new interns. But what will it take to build the brain of Dr. A? And how can we teach Dr. A to account for increasingly complex medical inputs, such as laboratory tests results, genomic/genetic information, family and personal history, co-morbidities and patient preferences, so he can make optimal clinical decisions for living, breathing patients?

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OneHealth: Combining Patient-Generated Data With Communities and Feedback Loops

Evolution from a research tool to a platform for patient engagement

Bruce Springer of OneHealth will speak about this topic at the Strata Rx conference. This article was written by Patrick Bane of OneHealth in coordination with Bruce Springer.

According to a recent study performed by the Jesse Brown VA Medical Center and University of Illinois at Chicago, patient-centered care has demonstrated positive outcomes on patients’ health, patients’ self-report of health, and reduced healthcare utilization. The study’s results are consistent with previous research that the patient-centered care model improves the quality of care while simultaneously lowering the cost of care.

OneHealth’s behavior change platform extends the patient-centered model by connecting members anytime, anywhere through mobile and web applications. Member generate data in their daily lives, outside of a clinical setting, which creates a much richer dataset of behaviors that are required to understand the patients’ condition(s), and their readiness to change. Members freely choose what to do and their choices actively generate data in five classes of information:

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How to bend fate in the health care field

Data that matters to patients

This article is by guest author Amik Ahmad. He is speaking on this topic at Strata Rx.

Distractions didn’t have a chance. My phone was devoid of reception. The New York Times mobile application searched impossibly for a Wi-Fi connection. Conditions perfect for focus: away from a world always on and connected, noisy, and belligerent with information overload. I could have found joy in a single byte. But instead, I was pushed to the limit of sensory deprivation, and I teetered on the edge of insanity. I spent nine hours of my life in a hospital waiting room.

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Mental Health Costs for 18-to-35 Year Olds: The Hidden Epidemic

Hypothesis-free data analysis turns up unexpected incidences of illness

This posting was written by guest author Arijit Sengupta, CEO of BeyondCore. Arijit will speak at Strata Rx 2013 on the kinds of data analysis discussed in this post.

Much of the effort in health reform in the United States has gone toward recruiting 18-to-35 year olds into the insurance pool so that the US economy and insurers can afford the Affordable Care Act (ACA). The assumption here is that health care costs will be less for this young population than for other people, but is this true? Our recent analysis of 6.8 million insured young adults, across 200,000 variable combinations, suggests that young adults may be more expensive to insure than we realize.

Our study shows a high occurrence of mental health diseases among 18-to-35 year olds who have insurance and therefore more affordable access to medical care. Moreover, expenses associated with mental health conditions are very high, especially when coupled with a physical ailment. As the previously uninsured 18-to-35 year olds get access to affordable care, we may see a similarly high rate of mental health diagnoses among this population. The bad news is that the true costs of insuring 18-to-35 year olds might be much higher than previously suspected. The good news is that previously undiagnosed and untreated mental health conditions may now actually get diagnosed and treated, creating a significant societal benefit.

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