Category Archives: data saving lives

Google gunning for the end of death…

Terrific summary of the state of play.

British gerontologist Aubrey de Grey believes achieving human immortality is inevitable. Last October de Grey told the audience at a US technology conference that they could expect to live 1000 years, maybe longer.

 

http://thenewdaily.com.au/life/2014/02/11/medical-science-close-curing-death/

Could medical science be close to curing death?

8:49pm, Feb 11
MICHELLE HAMER
If you were given the chance, would you choose to live forever, or another few hundred years? It may sound like the stuff of fantasy, but some very smart people are working to make death a thing of the past.
Live forever

Scientists are working to stop the ageing process, and extend the living… Photo: Shutterstock

Nanobots in your blood stream, backing up your brain to a computer, swapping your fallible human form for a sophisticated holographic avatar – it might sound like science fiction, but these are just some of the ways that science is hoping to extend human life and inch us closer to living forever.

US futurist, inventor and Google’s head of engineering, Ray Kurzweil has predicted that by the end of the century humans and machines will merge to create super humans who may never face the prospect of death. And Kurzweil, 65, hopes to be among those kicking mortality to the curb.

Ray Kurzweil

Ray Kurzweil: Working to bring an end to death. Photo: Getty

“Twenty years from now, we will be adding more time than is going by to your remaining life expectancy,” Kurzweil told Forbes Magazine. “We’ve quadrupled life expectancy in the past 1000 years and doubled it in the past 200 years. We’re now able to reprogram health and medicine as software, and so that pace is only going to continue to accelerate.”

Kurzweil is no slouch when it comes to accurate predictions. In the 1980s he predicted the incredible rise of the internet, foresaw the fall of the Soviet Union and identified the year when computers would beat humans at chess.

His next predictions include the programming of nanobots to work from within the body to augment the immune system and fight pathogens. By 2045 he sees us backing up our minds to the cloud and downloading ourselves into robotic forms.

And he’s not the only scientist hoping to blow out hundreds of candles in the future.

Immortality: Not if, when

British gerontologist Aubrey de Grey believes achieving human immortality is inevitable. Last October de Grey told the audience at a US technology conference that they could expect to live 1000 years, maybe longer.

Ageing, he says, is a simple case of bad engineering, and once the human body’s kinks are ironed out we’ll be able to reverse its effects and put death on the back burner.

“My approach is to start from the straightforward principle that our body is a machine. A very complicated machine, but nonetheless a machine, and it can be subjected to maintenance and repair in the same way as a simple machine, like a car,” de Grey has said. “What I’m after is not living to 1000. I’m after letting people avoid death for as long as they want to.”

Google is on board

It’s a goal that even tech giant Google thinks is worth pursuing.

When Google entered the anti-ageing business last year, with the launch of its new biotechnology company Calico, it brought a new level of interest, respectability and crucially – funding – to the field.

Calico has poached some of the leading anti-ageing researchers from across the world to work on the challenge of extending life.

“I think that if Google succeeds, this would be their greatest gift to humanity,” said David Sinclair, an Australian professor of genetics at Harvard Medical School.

Professor Sinclair led a research team which last year announced it had reversed muscle ageing in mice, the results of which exceeded his expectations.

“We want immortality so badly that we’re always ready to be swept away into unthinkingness … Half in love with the impossible we’ve always wanted to conquer death.”

“I’ve been studying ageing at the molecular level now for nearly 20 years and I didn’t think I’d see a day when ageing could be reversed. I thought we’d be lucky to slow it down a little bit,” he was quoted as saying.

“There’s clearly much more work to be done here, but if those results stand, then aging may be a reversible condition, if it is caught early,” he said.

The research involved improving communication between a cell’s mitochondria and nucleus. Mitochondria are like a battery within a cell, powering important biological functions. When communication breaks down between this and the nucleus, the effects of ageing accelerate.

Human trials of the groundbreaking process are expected to start this year.

Buying life

It’s the sort of breakthrough that can’t come soon enough for several  billionaires across the globe who are pouring their fortunes and hopes into immortality research.

Russian entrepreneur, Dmitry Itskov founded the 2045 Initiative in 2011 with the aim of thwarting human death within three decades. Itskov envisages ‘neo-humans’ who will relinquish clunky human forms and adopt sophisticated machine bodies. He claims humans will eventually download their minds into artificial brains, which will then be connected to humanoid robots he calls Avatars.

According to 2045.com: “Substance independent minds will receive new bodies with capabilities far exceeding those of ordinary humans … Humanity will make a fully managed evolutionary transition and eventually become a new species.”

PayPal co-founder Peter Thiel donated $US3.5 million to Aubrey de Grey’s not-for-profit research foundation, telling the New Yorker at the time that: “Probably the most extreme form of inequality is between people who are alive and people who are dead”.

Clearly Thiel would prefer to remain among the living and he’s prepared to pay for his pitch at immortality, most recently making a large donation to the Singularity Institute, which focuses on creating artificial intelligence that could see the rise of cyborgs (merged humans and machines).

Maximising life, minimising death

US entrepreneur turned science innovator, David Kekich, dedicated his life and impressive bank balance to reversing ageing after he was paralysed from a spinal cord injury in 1978. Kekich initially raised money for paralysis research but then switched to anti-ageing research. He founded the Maximum Life Foundation in 1999 and aims to reverse human ageing by 2033.

On his website Kekich writes: “We are moving from an era in which nothing could be done to defeat ageing into an era in which advancing biotechnology will give us the tools to do overcome it … Now, at the dawn of the biotechnology era, the inevitable is no longer inevitable. The research establishment – if sufficiently funded and motivated – could make spectacular inroads into repairing and preventing the root causes of ageing within our lifetime.”

But given that there are yet to be any proven means for extending human life, these billionaires may be motivated more by ego than altruism.

As US author Adam Leith Gollner writes in The Book of Immortality: the Science Belief and Magic Behind Living Forever (Sribner 2013): “We want immortality so badly that we’re always ready to be swept away into unthinkingness … Half in love with the impossible we’ve always wanted to conquer death.”

Yet he says all humans can really do to live longer is to eat well and exercise.

“We all have to go … whether dying in battle, tumbling off a horse, succumbing to pneumonia or being shivved by a lover. Maybe one day we just don’t wake up. However it happens, we enter the mystery.”

Insights can go stale…

  • Data is meaningless unless it helps make decisions that have measurable impact. Unfortunately, many decision makers are ensnared rather than enlightened by Big Data, preventing data and insights from making it to the front lines in relevant and usable forms.  Too many Big Data projects are formulated without input from front-line operators, or consume so much time that the insight goes stale before it can be used.

    In our experience, generating value from Big Data is a matter of connecting data to insights to action in a fast, repeatable way.

Picture a factory:

  • Insights are products—goods that are valuable because they are useful;
  • data is the raw material from which the products, the insights, are made; and
  • front-line operators are the consumers, or the people who need and use the product.

The “insight factory” approach enables companies to sift through massive amounts of data quickly, run the right analytics, and provide relevant insights so people can take meaningful action.

Add this to the analogy of a the brontosaurus nervous system being too slow to respond to an tale injury.

  1. Decide what it is you want to produce – get to specific questions
  2. Source the raw materials – start with “small data”
  3. Produce insights with speed – act like a startup
  4. Deliver the goods and act – “Good enough” information available now can be used now to inform specific actions.

For an insight factory to work, think of the people who use the insights as your customers. They need to be part of a process that gives them simple ways to use the insights, such as interactive frontline tools (e.g. competitive price tracker, customer scorecards, or store operations health monitor). The most effective approach is not to push these tools on managers, but to listen and respond to their needs and then create pull.

http://www.forbes.com/sites/mckinsey/2013/10/22/four-steps-to-turn-big-data-into-action/

10/22/2013 @ 9:31AM |9,473 views

Four Steps To Turn Big Data Into Action

Data is meaningless unless it helps make decisions that have measurable impact. Unfortunately, many decision makers are ensnared rather than enlightened by Big Data, preventing data and insights from making it to the front lines in relevant and usable forms.  Too many Big Data projects are formulated without input from front-line operators, or consume so much time that the insight goes stale before it can be used.

In our experience, generating value from Big Data is a matter of connecting data to insights to action in a fast, repeatable way. Picture a factory.Insights are products—goods that are valuable because they are useful; data is the raw material from which the products, the insights, are made; and front-line operators are the consumers, or the people who need and use the product.

The “insight factory” approach enables companies to sift through massive amounts of data quickly, run the right analytics, and provide relevant insights so people can take meaningful action.  And we’ve seen top-line sales increase 5 – 15 percent as a result.

1. Decide what to produce

Before work begins at an insight factory, you should have a clear understanding of what you want to achieve, such as reducing customer churn or predicting what a given customer segment will buy next. Decide what discrete questions your business needs to answer and the actions you want those answers to enable. Prioritize questions that address the largest economic opportunities and that lead to practical actions. Then configure your factory to produce just those insights. One retailer, for example, discovered that 90 percent of its year over year sales decline was concentrated in 12 percent of its customers in specific markets. It focused questions, accordingly, on understanding the root cause and quickly reversed the trend with targeted local market merchandising tactics.

2. Source the raw materials

While it’s useful to identify a range of data sources to build insights, start with the best data immediately available.  Chasing after the “perfect dataset” is time-consuming (and often fruitless) and reduces the ability to act quickly. Instead, start with “small data”. A comprehensive “data warehouse” is a great asset over the long term, but a smaller, more selective “data mart” makes it easier to produce insights fast, preventing you from getting mired in complexity. Over time, you can then layer on additional data sets. In one case, a leading retailer setting out to understand its customers began by complementing transactional POS data with third-party customer data from aggregators, syndicated competitor data, and public sources that were immediately available. Over a year, it enriched these insights by adding social media data (for sentiment analysis), location data (to understand store traffic and movement), and financial information from credit card providers (for share-of-wallet).

3. Produce insights with speed

We have found that when it comes to analytics, productive action is mainly a product of speed. Focusing on quick decisions and execution, which circumvent long discussions, leads to insights the front line can actually use. Put finite time limits on your insight factory to force short production times and rapid bursts of structured output based on repeatable analytical models and automation.

We recommend acting like a start-up. Start-ups are driven by an inherent need for speed that doesn’t let perfect get in the way of good enough. Aware AWRE -0.31% that a futile quest for perfection creates paralysis, they thrive on a test-and-learn culture that celebrates failing early and moving to action quickly with imperfect information. Create small, nimble teams combining strategic, analytical, and technical skills to address specific topic areas rather than a single, generalized, and usually slow-moving “committees.” To keep the factory running around the clock, consider recruiting offshore talent to execute structured analysis continuously, at relatively low cost.

4. Deliver the goods and act

“Good enough” information available now can be used now to inform specific actions. If data yields the insight that milk and eggs are 90 percent likely to be purchased together, why not quickly pilot the placement of milk and egg shelves next to each other rather than wait for more comprehensive options?

Making sure that insights drive action requires a clear understanding of what front-line managers can actually use. These managers need to identify what they need. Too often, marketers or sales people are provided with data analysis they subsequently ignore. In many cases, the analysis isn’t practical, isn’t clear, isn’t trusted, or isn’t perceived as relevant. For an insight factory to work, think of the sales and marketing people who use the insights as your customers. They need to be part of a process that gives them simple ways to use the insights, such as interactive frontline tools (e.g. competitive price tracker, customer scorecards, or store operations health monitor). The most effective approach is not to push these tools on managers, but to listen and respond to their needs and then create pull.

Build a “factory” culture over time

To successfully weave the insight factory into the fabric of the way the business works, avoid  leading off with momentous change. Accustom stakeholders to incrementally embed data and insights into everyday decision making. Over time, the integration of insight factory production into business-as-usual will create a willingness to accept bigger decisions and greater change.

Tim McGuire is a senior McKinsey partner from Toronto who leads the firm’s global Consumer Marketing Analytics Center; Chris Meyer is a senior partner in McKinsey’s Dallas office who leads the firm’s work in Big Data & Analytics in Retail; Maher Masri is an associate principal in McKinsey’s Marketing and Retail practices; Abdul Wahab Shaikh is an engagement manager in McKinsey’s Atlanta office.

BUPA thinks about the future…

  • Dr Paul Zollinger-Read is Chief Medical Officer at Bupa
  • He’s tried to think about the future
  • ubiquitous, embedded sensors will be important
  • gamification will help change behaviours
  • In November 2013, Bupa signed a partnership agreement with the United Nations agency, the International Telecommunication Union (ITU), to work together on a global ‘m-Health’ initiative called ‘Be Healthy, Be Mobile’.

http://www.telegraph.co.uk/technology/news/10634366/Healthcare-in-2024-clothes-that-detect-blood-sugar-levels-and-a-toilet-that-monitors-hydration.html

Healthcare in 2024: clothes that detect blood sugar levels and a toilet that monitors hydration

Smart technology will transform healthcare over the next ten years, according to Bupa

Google unveiled a revolutionary smart contact lens which detects glucose levels in diabetes sufferers’ tears earlier this year

By 2024, mobile technology will have completely transformed medical provision across the world, according to global healthcare company Bupa. Clothes, household appliances and furniture will all play a vital role behind the scenes of our daily routines, helping keep track of health and alerting people at the first sign of illness.

Meanwhile, ‘gamification’ of healthcare could reward everyday positive choices and healthy behaviour in the same way gamers unlock badges in mobile apps such as Angry Birds or Foursquare, aiding disease prevention and dramatically reducing the onset of diseases such as diabetes.

“This glimpse into the future has allowed us to imagine a time where sophisticated mobile technology and advancements in the connected home mean that people can become guardians of their own health,” said Dr Paul Zollinger-Read, Chief Medical Officer at Bupa.

“Being aware of their likelihood of disease and possible risk factors, coupled with constant monitoring through intelligent technology means that they will be able to spot the symptoms of illness from a very early stage, or simply prevent them altogether.”

Some of the innovative healthcare solutions suggested by Bupa include ‘smart’ nappies that allow parents to check their child’s hydration levels or monitor for kidney infections, intelligent fibres in clothing that canl detect movement of the chest and pulse, monitoring breathing and heart rate and detecting irregularities, and contact lenses featuring microscopic cameras that will monitor changes in the back of the eye, spotting early signs of diabetes.

Shoes featuring pressure sensors could detect when the wearer is sedentary, and alert them with updates on fitness goals, and the household fridge will monitor liquid, nutrition and calorie consumption, while ‘tattoo’ skin patches will monitor body temperature and hydration.

Bupa said that wearable technology and the connected home will transform prevention of diseases in the next decade by gathering data from a number of devices about our bodies and presenting it back to us in simple, visual, practical terms.

The news comes after Google unveiled a revolutionary smart contact lens which detects glucose levels in diabetes sufferers’ tears earlier this year. Human trials of a miniature artificial pancreas are also set to begin in 2016.

In November 2013, Bupa signed a partnership agreement with the United Nations agency, the International Telecommunication Union (ITU), to work together on a global ‘m-Health’ initiative called ‘Be Healthy, Be Mobile’.

Bupa and ITU will provide multidisciplinary expertise, health information and mobile technology to fight chronic diseases including diabetes, cancer, cardiovascular and chronic respiratory diseases, in low- and middle-income countries.

Doctors detecting depression

Filling out forms is very much the v1.0 use of IT in the detection of mental health issues.

http://depressionscreening.org/

http://online.wsj.com/news/articles/SB10001424052748703471904576003520708615998

THE INFORMED PATIENT

How Doctors Try to Spot Depression

By

LAURA LANDRO
Updated Dec. 7, 2010 12:01 a.m. ET
Appearing anxious and overwhelmed on a routine visit with her primary-care provider, Lucy Cressey was prescribed an anti-anxiety medication and referred for talk therapy with a social worker.The treatment recommendations came after Ms. Cressey agreed to fill out two questionnaires during the medical visit at the John Andrews Family Care Center in Boothbay Harbor, Maine, last year. Ms. Cressey scored high on both questionnaires, designed to help depression and anxiety.

Following the recent death of her best friend, a tough spinal surgery and some family financial woes, “a lot of stressors just snowballed for me,” says Ms. Cressey, a 52-year-old veterinary technician. “But in rural Maine it’s not so cool to talk about being depressed or anxious, and those questionnaires really open some doors for them to help you.”

A growing number of primary-care providers are using screening tools to assess depression and other mental-health conditions during routine-care visits. They are also coordinating care of depressed patients with behavioral-health specialists. Such so-called mental-health-integration programs have been shown to reduce emergency-room visits and psychiatric-hospital admissions, and to increase employees’ productivity at work.

One in four American adults who visit their primary-care doctors for a routine checkup or physical complaint also suffer from a mental-health problem, federal data show. But patients often don’t raise the issue and doctors are too busy to ask. As a result, many never get treatment: Less than 38% of adults in the U.S. with mental illness received care for it last year, according to the federal Substance Abuse and Mental Health Services Administration.

A number of health-care groups work in tandem with behavioral-health providers. And some insurers, including AetnaAET +5.23% are promoting integrated care. About 5,000 physicians participate in Aetna’s Depression in Primary Care program, which reimburses them for administering a Patient Health Questionnaire, or PHQ-9, to patients. Aetna is also training behavioral-health specialists, and stationing them in primary-care offices.

Health groups increasingly recognize that physical and emotional health are intertwined. Many patients with mental-health problems have two or more other issues such as heart disease, obesity or diabetes. As many as 70% of primary-care visits are triggered by underlying mental-health issues, according to behavioral-health researchers.

Intermountain Health in Salt Lake City, Utah, uses the PHQ-9 depression-screening tool in about 70 of its 130 medical practices. “The aim is to see if we stabilize patients and get them well in primary care, or whether we need to transition them to a behavioral-health expert,” says Brenda Reiss-Brennan, director of the Intermountain Mental Health Integration program.

Wayne Cannon, an Intermountain physician helping lead the effort, says that patients who are asked to fill out the PHQ-9 form might be classified as mildly, moderately or severely depressed. Scoring programs on the questionnaires include guidelines to help doctors determine whether patients need just watchful waiting, medication or a course of psychotherapy. Patients can be immediately seen by a behavioral-health specialist in what’s known as a “warm hand-off,” Dr. Cannon says, making them more comfortable and likely to follow through with treatment.

 

Amy Young, a 32-year-old patient at Intermountain who has multiple sclerosis and takes antidepressants, says her primary-care doctor last year referred her to a psychologist who works in the same office and knew about some struggles faced by MS patients. “Your primary-care doctor can’t talk to you for an hour at a time like a therapist can,” says Ms. Young. “They can talk to each other if they have questions about anything going on with me and I feel much more relaxed because I’m used to going to the same office.”

Intermountain says its own studies show that adult patients treated in its mental-health integration clinics have a lower rate of growth in charges for all services than those treated in clinics without the service. It also found that depressed patients treated in the clinics are 54% less likely to have emergency-room visits than are depressed patients in usual care clinics.

Patients being treated for depression should have the PHQ-9 test regularly administered, says John Bartlett, senior adviser in the mental-health-care program at the nonprofit Carter Center in Atlanta, which promotes mental-health treatment in primary care. If doctors don’t offer it or don’t repeat it, patients should take the test on their own and alert their doctor to any worrisome score, he says. The test is available free online atdepressionscreening.org.

MaineHealth, a network of providers in the state that includes the John Andrews Center where Ms. Cressey is treated, recruited behavioral-health specialists to work in doctors’ offices in different communities. Cynthia Cartwright, program director, says MaineHealth created an Adult Wellbeing Screener combining questions from the PHQ-9 for depression, and other tests for anxiety, bipolar disorder and substance abuse. “It’s hard sometimes to reduce depression symptoms to the questions on a form, but you have to start somewhere, and I think they help doctors notice, ask about and treat mood disorders,” says Debra Rothenberg, one of the physicians participating in the program.

Because behavioral-health services are typically covered separately under most insurance plans, doctors often have to advise patients to seek out additional mental-health care by calling their insurer for a referral. But many patients don’t follow through to make the appointments, and there are often limits to their mental-health coverage. That is changing as new federal rules take effect prohibiting insurers from setting stricter limits on mental-health benefits than they do for other illnesses. And mental-health-integration programs are expected to get a boost from the new federal health law, which includes funding for programs creating “medical homes” that coordinate physical- and mental-health care for patients.

In the Aetna program, the insurer’s case managers help track patients’ progress and alert physicians if they are not improving. Case managers also assist with referrals to additional mental-health services.

Primary-care physicians increasingly are using screening tools to assess depression during routine-care visits. Getty Images

Aetna’s studies show that on average, patients completing the case-management program experienced a 4.7% increase in productivity at work, based on a questionnaire measuring the impact on productivity of employee health problems. Hyong Un, Aetna’s chief psychiatric officer, says the insurer uses its own records to identify patients who may be candidates for depression screenings, including those who have stopped filling their antidepressant prescriptions.

Richard Wender, chair of the department of family medicine at Thomas Jefferson University in Philadelphia, says participation in the Aetna program has helped motivate its doctors to administer the screens and follow up with patients. Having a behavioral-health specialist in the same office “has helped us assess behavioral-health issues more frequently and have a plan in place to deal with them,” he says.

Corrections & Amplifications

The Trustees of Dartmouth College hold the copyright on diagrams used by some doctors to screen patients for mental-health problems. Reproductions of the diagrams that accompanied an earlier version of the Informed Patient column were incorrectly attributed to MaineHealth.

Lung cancer detecting smart phones…

zero-stage disease prevention… why not!!

http://www.forbes.com/sites/mckinsey/2013/10/22/four-steps-to-turn-big-data-into-action/

Partnership tests smartphone sensor for detecting lung cancer

February 11, 2014 | By 

Vantage Health, an mHealth company developing a proprietary breathalyzer attached to a smartphone for non-invasive lung cancer screening, announced that they have formed a strategic partnership with Scripps Translational Science Institute (STSI), the NIH-sponsored consortium led by San Diego-based Scripps Health.

Redwood City, Calif.-based Vantage Health is developing mobile apps for personalized screening which leverage chemical sensing capabilities inside a small smartphone device.

Through this partnership with Vantage, STSI will provide assistance in the testing, evaluation and detection of certain basic volatile organic compounds (VOCs) using gas chromatography and mass spectrometry to calibrate the results.

STSI will assist in the testing, evaluation and detection of specific VOCs commonly associated with lung cancer. VOCs in breath provide a noninvasive and quick approach to diagnosing lung cancer in its early stages. STSI and Vantage Health will collaborate in the planning and execution of clinical trials which are expected to be carried out at STSI in San Diego, as well as a second location in the Midwest and a third location in New England.

Last month, Vantage Health announced that it had entered into an exclusive license agreement with NASA to commercialize mobile healthcare products derived from the space agency’s patented technology. The agreement with NASA licenses the use of multiple patents relating to inventions in, among other fields, chemical sensing.

The sensor technology, which won the 2012 NASA Government Invention of the Year, has been deployed by the space agency to detect trace gases in the crew cabin on the International Space Station. The sensors have also been tested and used for such applications as trace chemical detection in planetary exploration, air monitoring, leak detection and hazardous agent detection using cell phones.

“This is arguably one of the most vital and exciting steps in our effort to transfer the technology out of the labs at NASA and into the marketplace, as part of our commercialization process,” said Jeremy Barbera, chairman and CEO of Vantage Health, in a written statement.

Open source quantified self data API

http://www.getquant.com/

Not taking sign-ups yet, but looks interesting…

Analyze all your quantified self data in one place.

Plug in any self-tracking data source for beautiful graphs of your body, brain, and behaviour.


Free as in speech

Quant is an open source project.
Our codebase is MIT licensed and publicly available for download. You’re free to host your own version, make modifications, and contribute back to the community.

Automatic or manual

Track personal data from virtually any QS data source. From Fitbit, to Jawbone, Foursquare, and Withings, we’ve built API integrations for everything. Plus, you’ll be able to enter your own data manually if you’d prefer.

Lies, damned lies, and stats

Quant helps you navigate all of the data you’ve collected by allowing you to slice, rearrange, and order by source, date series, weighted averages, and more. The quantified self movement is about more than just making bar charts, after all.

 

Originally found at:

http://www.fastcolabs.com/3026076/could-an-apple-iwatch-bring-the-open-source-movement-mainstream

Could An Apple iWatch Bring The Open Source Movement Mainstream?

With a rumored focus on quantified health metrics, Apple’s new gadget could prompt people to care more about their data.

The latest rumors say the Apple iWatch will be full of sensors for tracking health metrics. With a deep level of awareness about people’s well-being, these new devices and platforms could revolutionize health care. But if iTunes purchases are any indication, it’s likely that data will stay within Apple’s walled garden. Will this make consumers uncomfortable enough that they get wise to the value of the open source movement?

Companies like Quant should hope so. Quant is an open source library that makes it easy to export data from all the different activity tracking devices. The hope is that peoples’ fear of misappropriation will get them to value their data more than they currently do, pressuring device makers to build products that are more accessible.

“The single biggest challenge is inconsistently structured data from each of the providers,” says Joshua Kelly, Quant’s lead developer. “Everyone has implemented a slightly different format for each kind of data. Meshing these together can prove challenging.”

What happens when consumers are generating their hyper-personal data? Who owns it? What happens to the data if the device company gets into financial trouble, shuts down, or just decides to try and sell it? Even the current crop of rather harmless activity trackers have raised privacy concerns. Mother Jonesrecently dug into the different privacy policies of some of the major players in the space such as Fitbit and Nike with somewhat troubling findings, and the Federal Trade Commission is holding a conference on the matter in May 2014.

“Do I sleep better after eating fewer carbs? How does running impact my mood versus lifting weights? I worry that we won’t even be able to ask these types of questions at all if the trend of closed APIs picks up.”

The concern here is the aggregate impact if Apple does switch on health tracking features. In the recent holiday quarter, Apple sold more than 50 million iPhones and there are hundreds of millions of iOS devices already in the wild. If that many people started tracking their daily activity with a sensor-equipped iWatch and the rumored Healthbook app for iOS, the impact on health care in general would be colossal.

“Apple would be an incredible boon to the space if they can provide a hardware platform for others to build on,” says Kelly. “I think everyone is still trying to figure out what the killer device or app will be, and if history is a guide, Apple could definitely be the one to do it.”

 

To improve health care, governments need to use the right data

Terrific Economist snippet…

http://www.economist.com/news/international/21595474-improve-health-care-governments-need-use-right-data-need-know

Measuring health care

Need to know

To improve health care, governments need to use the right data

DECIDING where to seek treatment might seem simple for a German diagnosed with prostate cancer. The five-year survival rate hardly varies from one clinic to the next: all bunch around the national average of 94%. Health-care providers in Germany, and elsewhere, have usually been judged only by broad outcomes such as mortality.

But to patients, good health means more than life or death. Thanks to a study in 2011 by Germany’s biggest insurer, a sufferer now knows that the national average rate of severe erectile dysfunction a year after removal of a cancerous prostate gland is 76%—but at the best clinic, just 17%. For incontinence, the average is 43%; the best, 9%. But such information is the exception in Germany and elsewhere, not the rule.

Doctors and administrators have long argued that tracking patients after treatment would be too difficult and costly, and unfair to providers lumbered with particularly unhealthy patients. But better sharing of medical records and a switch to holding them electronically mean that such arguments are now moot. Risk-adjustment tools cut the chances that providers are judged on the quality of their patients, not their care.

In theory, national health-care systems should find measuring outcomes easier. Britain’s National Health Service (NHS) compiles masses of data. But it stores most data by region or clinic, and rarely tracks individual patients as they progress through treatment. Sweden’s quality registries do better. They analyse long-term outcomes for patients with similar conditions, or who have undergone the same treatment. Some go back to the 1970s and one of the oldest keeps records of hip replacements, letting medics compare the long-term performance of procedures and implants. Sweden now has the world’s lowest failure rate for artificial hips.

Elsewhere, individual hospitals are blazing a trail. Germany’s Martini-Klinik uses records going back a decade to fine-tune its treatment for prostate problems. The Cleveland Clinic, a non-profit outfit specialising in cardiac surgery, publishes a wide range of outcome statistics; it now has America’s lowest mortality rate for cardiac patients. And though American politicians flinch at the phrase “cost-effectiveness”, some of the country’s private health firms have become statistical whizzes. Kaiser Permanente, which operates in nine states and Washington, DC, pools the medical records for all its centres and, according to McKinsey, a consultancy, has improved care and saved $1 billion as a result.

Such approaches are easiest in fields such as prostate care and cardiac surgery, where measures for quality-of-life are clear. But some clinics have started to track less obvious variables too, such as how soon after surgery patients get back to work. This is new ground for doctors, who have long focused on clinical outcomes such as infection and re-admission rates. But by thinking about what matters to patients, providers can improve care and lower costs at the same time.

Leeder on outcomes…

 

The 1 February edition of The Economist, in an article entitled Need to Know (about health outcomes), took up the theme. The article observed that in Germany, its biggest insurer made available data in 2011 about outcomes for all to see.

Among the outcomes, the data showed five-year survival after treatment for prostate cancer was uniform across the nation – 94 per cent. But the data collected by the insurer went further: while the national average for subsequent erectile dysfunction was 76 per cent, at the best-performing clinic it was just 17 per cent. “For incontinence, the average was 43 per cent: the best 9 per cent,” The Economist wrote.

Armed with data such as these, prospective patients can choose where to be treated. The same data form the basis for discussion between those who provide and those who pay for health care.

 

https://ama.com.au/ausmed/case-measuring-outcomes-what-we-do

The case for measuring the outcomes of what we do

18/02/2014

Archie Cochrane, the Scottish medical epidemiologist after whom the Cochrane Collaboration that develops the evidence base for clinical medicine is named, came out of the Spanish Civil War and World War Two sceptical about the outcomes of his medical care.

Cochrane said, “I knew that there was no real evidence that anything we had to offer had any effect on tuberculosis, and I was afraid that I shortened the lives of some of my friends by unnecessary intervention.”

He changed career, moving into public health and conducting epidemiological research into TB and occupational lung diseases. He became especially sceptical about screening and, as Wikipedia puts it, “his ground-breaking paper on validation of medical screening procedures, published jointly with fellow epidemiologist Walter Holland in 1971, became a classic in the field”.

Cochrane recalled in his 1972 book Effectiveness and Efficiency: Random Reflections on Health Services being puzzled by a crematorium attendant he met who was permanently serenely happy. Cochrane asked why: the attendant said that each day he marvelled at seeing “so much go in and so little come out”.  Cochrane suggested that he consider working in the National Health Service.
In Australia we assess how much work we do in hospitals through activity-based funding.  Money flows in direct proportion – so many coronary grafts, so many strokes treated. But little attention, at least in routine care, is paid to what we achieve. There are examples that contradict this general assertion, but mainly it is true.
Recently, the Bureau of Health Information in the NSW Ministry of Health made available statewide mortality data for five conditions treated in NSW public hospitals, taking account of variations in severity. Such data begin to fill the blanks in our knowledge about outcomes, and prompt discussion about why these variations occur.

The 1 February edition of The Economist, in an article entitled Need to Know (about health outcomes), took up the theme. The article observed that in Germany, its biggest insurer made available data in 2011 about outcomes for all to see.

Among the outcomes, the data showed five-year survival after treatment for prostate cancer was uniform across the nation – 94 per cent. But the data collected by the insurer went further: while the national average for subsequent erectile dysfunction was 76 per cent, at the best-performing clinic it was just 17 per cent. “For incontinence, the average was 43 per cent: the best 9 per cent,” The Economist wrote.

Armed with data such as these, prospective patients can choose where to be treated. The same data form the basis for discussion between those who provide and those who pay for health care.

Once, clinical trials of new cancer drugs were concerned principally with the survival of patients treated versus those not treated with new medications. But they now measure more than life expectancy.

For over 25 years mortality data have been supplemented by quality of life assessments.

But the excellence in clinical trial outcome measurement has not spread to routine care.

So much goes in, but what comes out?
In the US, health care expenditure is a huge worry for individual citizens, for Government (which spends as much as a proportion of GDP/GNP as ours does on health), and for industry, which pays for a lot of health insurance for employees. In response, comparative effectiveness research – CER – has recently evolved.

Wikipedia advises that “The Institute of Medicine committee has defined CER as ‘the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition, or to improve the delivery of care. The purpose of CER is to assist consumers, clinicians, purchasers, and policy makers to make informed decisions that will improve health care at both the individual and population levels’.”

There are many agencies and individuals now in the US committed to CER, including Dr John Wennberg at the Dartmouth Institute for Health Policy and Clinical Practice.

He and his colleagues have studied variations in medical practice across the US with a view to ironing out the wrinkles caused by inferior care.

They claim that 30 per cent of health care costs could be saved by correcting care that falls below expected outcomes.

Australia has not been entirely idle, and we have led the world in aspects of outcome measurement in relation to drugs.

Since 1953, Australia’s Pharmaceutical Benefits Advisory Committee (PBAC) has constructed the formulary of publicly funded medicines. Since 1990, the PBAC has made cost and effectiveness (outcome) assessment a mandatory prelude to listing. Pricing and other political decisions follow, but the solid outcome data are necessary. Others are now following our example.

When we have a health care system that is fully connected electronically, the task of measuring outcomes and using them to good effect in managing the system will be far easier. Outcome data are critical to achieving real financial efficiency. They can be used to help us stop doing things that achieve nothing, or cause harm, and instead use the resources saved for clinical care with good outcomes.

But assessing outcomes, as the prostate surgery example demonstrates, extends well beyond financial efficiency and, indeed, beyond life expectancy. When we confidently explain what we achieve with what we do – quantity and quality of life gained –  patients are empowered to make choices.

Wearables snapshot…

A market snapshot of wearables… useful for presentations.

Want A Neat Overview Of What’s Going On In Wearables? Point Your Eyes Right Here…

Want A Neat Overview Of What’s Going On In Wearables? Point Your Eyes Right Here…

Posted  by  (@riptari)

Former Groupon Product SVP Jeff Holden Joins Uber As Chief Product Officer

Wearables are so hot right now. Apple iWatch rumours are in rude health. Google isapparently looking (beyond Glass) at picking up and strapping onto its business anotherstartup in the wearables space (guesses for which in the comments pls).

Jawbone, maker of the UP fitness tracker bangle (and apparently not the company in Google’s Glassy sights), is running sweat-free towards an IPO. Action camera maker GoPro — ok, not technically a wearables company but the point of its cameras are that they are, y’know, wearable — has already filed for one. Smartwatch maker Pebble has raised a tonne of money since 2012, first via Kickstarter and then, off the back of its snowballing crowdfunder, from VC checkbooks.

Even though the genuine usefulness of bits of technology that you strap to your person still has a lot of proving to do – vs the intrusion (both visual, with a lot of these early devices being best described as uuuuuuuugggglllyyy; and, more importantly, the sensitive personal data being captured and monetized) – it’s the big huge lucrative potential that’s exciting makers and investors.

Mature Western markets are saturated with smartphones — ergo step forward sensor-stuffed wearables as the next growth engine for device makers. Devices whose literal positioning on our bodies enables them to gather far more intimate data on the lives and (physical) habits of users than previous generations of consumer mobiles. If only we can be persuaded to wear this stuff.

Yesterday analyst Canalys suggested 2014 will be the year for the wearables category becomes a “key consumer technology” — with more than 17 million wearable bands (alone) forecast to ship this year, rising to 23 million by 2015, and more than 45 million by 2017.

So that’s only wearable tech targeting the wrist, such as the Fitbit fitness tracker and Samsung’s Galaxy Gear smartwatch — it does not include devices aiming to squat on other body-parts (such as Google Glass). In short: tech makers gonna put a smart ring on it. Many are already trying.

On the ‘who is already making what’ front, wearable tech research and consulting firm Vandrico has put together this neat overview of the space — tracking the number of devices in existence; areas of market focus; and even which parts of the body are being targeted most.

(The most popular anatomical target for wearables is the wrists, since you’re curious — with 56 devices vying for that small patch of flesh; followed by the head, with 34 devices wanting to cling to it. On the flip side, the least popular body part for wearables thus far is apparently the hand, with just two devices listed, although the data doesn’t delve into the crotch region, so, yeah, there’s there too. Makers apparently not falling over themselves to fashion iCodpieces…).

According to Vandrico, there are some 115 wearables in play already; with an average selling price of $431; and with lifestyle, fitness and medical being the most popular market areas targeted (in that order).

wearables

The researcher has also taken the time to list and profile every single one of the 115 wearables it reckons are currently in play, so you don’t have to — from 3L Labs Footlogger to the ZTE Bluewatch (another mobile maker doing a smartwatch, who knew?).

Or at least all of the wearables its research has turned up. It’s asking for submissions for missing devices so it can keep expanding this database. (I’m going to throw the Fin into the ring on that front.)

Click here to check out — and start quantifying — the data for yourself.

[Image by IntelFreePress via Flickr]

the world’s most potent, booming unnatural resource: data

 

Predictive analytics is “powered by the world’s most potent, booming unnatural resource: data.”

You have been predicted — by companies, governments, law enforcement, hospitals, and universities. Their computers say, “I knew you were going to do that!”

Great quotes from Eric Siegel.

http://bigthink.com/big-think-edge/you-can-predict-the-future

You CAN Predict the Future, and Influence It Too

FEBRUARY 13, 2014, 12:00 AM
Shutterstock_64061473

We are better than ever at making predictions – whether you’re going to click, lie, buy or die, as Eric Siegel puts it.

In a lesson on Big Think Edge, the only forum on YouTube designed to help you get the skills you need to be successful in a rapidly changing world, Siegel, a former professor at Columbia University, shows how predictive analytics is “powered by the world’s most potent, booming unnatural resource: data.”

You have been predicted — by companies, governments, law enforcement, hospitals, and universities. Their computers say, “I knew you were going to do that!”

Advertising

Netflix and Pandora predict the movies and music you will like. Online dating sites select possible matches for you based on your interests. Companies can predict whether you’re going to default on your credit card statements and whether you’re going to commit an act of fraud.

So what do governments and companies do with this gold mine? In the video below, Siegel tells Big Think that these entities not only have the power to predict the future “but also to influence the future.”  And so can you.

Sign up for a free trial subscription on Big Think Edge and watch Siegel’s lesson here:

https://www.youtube.com/watch?v=Kriiamz9KqQ

Reflection Questions 
— Describe how your company is using predictive analytics to influence any operational decisions? Do you analyze who is likely to respond before initiating a marketing campaign? If not, how could this help streamline operations in your department?– How are predictive analytics at work in your life? Do you use Netflix or Pandora to predict movies or music you will like? Have you used an online dating site that selects possible matches for you based on your interests? How has this worked out for you?

— Is the use of predictive analysis exposing people to other people, entertainment, or services that more accurately match their interests or is it pigeonholing people by suggesting things they may like based only on a limited amount of information on previous decisions they’ve made?

For expert video content to inspire, engage and motivate your employees, visit Big Think Edge

Watch the video below and sign up for your free trial to Big Think Edge today.