So what is blockchain? Most have heard of bitcoin and it is not uncommon to encounter a great deal of confusion when we talk about blockchain in sectors like healthcare. Blockchain is the infrastructure that bitcoin is built upon; the two are interrelated but not the same thing. Blockchain is a distributed, public ledger, meaning that certain elements of transaction data are visible to anyone. It is decentralized so that no particular party can control the ledger. Due to the cryptographic nature of the blockchain, entries cannot be reversed therefore making a system more tamper-proof. Any attempt to change a previous entry will be immediately obvious because the entry will be hashed on the blockchain in a way that differs from the original.

William Mougayar makes a distinction between the technological, business, and legal meanings or significance of blockchain as follows:

Technically the blockchain is a back-end database that maintains a distributed ledger that can be inspected openly. Business-wise, the blockchain is an exchange network for moving transactions, value, assets between peers, without the assistance of intermediaries. Legally speaking, the blockchain validates transactions, replacing previously trusted entities.

He notes that we need to understand “blockchain as a new protocol that sits on top of the internet just as the World Wide Web sits on top of the internet.” As such we need to begin thinking about the new technologies and business models it will enable, which may not be in existence currently due to the architecture of the existing web.

Why is this important? Look at the internet in its present day structure. Security has become a seriously difficult challenge. Today’s internet cannot by any stretch of the imagination be considered a trusted network. We increasingly hear that there are two types of people in the world now, those who know they’ve been hacked and those who don’t know. Blockchain can enable a much higher level of security for transactions on the internet as well as offer efficiencies by cutting out third parties or administrators who take a fee for settling transactions.

Blockchain is based on cryptographic methods that involve keys, digital signatures, and hashing to verify the integrity of data (the hash). Keys enable controls over who can access information on the blockchain where we find multiple signatures (multisigs). Multisigs mean that for a given transaction to be approved, multiple signatures are required just like we see in paper contracts, but the blockchain can automate this process if the decisions or requirements of a contract are programmed into the blockchain. This is an important part of the blockchain that enables smart contracts and even smart property.

William Mougayar (2016) has identified six primary capabilities of blockchain that will enable and have effects on the future of these areas.

In the sections that follow, we will explore concrete applications of the blockchain that use these capabilities to create new products and services or alternative pathways that offer administrative or financial efficiencies over existing businesses. But one of the central advantages of the blockchain that many existing technologies fall short on is the growing need for new ways to think about identity management given our separate use cases that range from access to government services to banking, healthcare, and even social media. The largely paper-based notions behind current identity regimes is likely going to encounter significant changes in the coming years.

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The growth of wearable computing, tracking, social-network analysis, and data analytics is opening up new ways of addressing both the wellness of employees as well as understanding the underlying social dynamics of any given firm that may also contribute to less stress and better health. These two areas are often treated separately. But their intersection offers the potential to build both healthier and more productive companies if the early generations of programs using these tools can prove their effectiveness and sustainability in the coming years.

Key findings in this report include:

• While the U.S. Affordable Care Act creates incentives for employers to offer rewards to employees who practice healthy lifestyles, that driver is counterbalanced by inhibitors, including employee privacy concerns, minimal proof of ROI, and a backlash against badly designed behavioral incentives like gamification.
• Employers are finding that wellness plans can suffer from lack of employee engagement, participation, and adherence. They should evaluate the results and potential solutions from programs such as Humana Vitality, Keas, Hubbub, and Jiff.
• Tracking data on “people dynamics” will be a critical addition to employee wellness and productivity. The combination of monitoring internal work networks complements wellness programs to deliver an effective quantified workplace.

Thumbnail image courtesy of flickr user Nicola.

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Strategists at device makers, health plans, and data analytics vendors must develop their ability to build and exploit partnerships as the key to success, via a “disruptive cooperation” paradigm for innovation. They’ll need to understand the use cases of platforms in the health system, how feedback loops can create data hooks and markets, and how the next generation of data services can generate more sustainable use of devices. Success in this space, despite the persistent hype about new devices, depends on the jobs that platforms must perform, including:

• Making it easier to integrate data from an expanding ecosystem of devices where health IT interoperability has failed in the past
• Building useful data services that can help consumers and systems lower costs, improve the quality of care and improve access to healthcare through connectivity
• Enabling mobile access to patients and real-time data monitoring that can improve population health management and data analytics while maintaining privacy and security
• Improving the experience of healthcare or self-tracking by making engaging data analytics products and services in both fitness and healthcare

These demands from both major markets mean that the platforms will serve as an anchor for building complex ecosystems where the trick will be to align health data value chains and value capture across the spectrum of suppliers.

Thumbnail image courtesy: iStock/Thinkstock

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Smart cites tap into technology and social experiments with open data, civic hacking, low-cost sensors, and big data as a tool for city managers. Parallel investments in M2M, the internet of things, wearable computing, and mobile devices have added to the range of innovative tools and platforms to create real-time data on the dynamics of social interactions, the environment, health, transportation, water management, and utilities via smart grids.

Urban planning, just like healthcare and a host of other social sectors, is filled with data silos, fragmented policy-making, and local politics that make the task of building a smart city quite challenging. These trends could offer a tremendous number of new business opportunities for technology companies in the future, though plenty of obstacles remain. This report will examine the possibilities and challenges that smart cities are beginning to face in the wake of the first generation of lessons learned.

Key findings include:

• Greater use of open data, open standards and open APIs along with business process standards could improve efficiencies in procurement as well as facilitate the creation of enterprise grade platforms that can transcend silos and improve privacy and security.
• The EU, Singapore and Korea have been some of the leading areas for smart city growth but we should expect a great deal of activity in middle income countries like Brazil, India, and China in the coming years.
• Energy, transportation and public safety/sustainability (recycling/waste) tend to be the most popular verticals in cities but the IoT opens up a number of growing opportunities for health, education, and system integration across all sectors.
• Some of the leading companies driving innovation in this space include Cisco, IBM, Siemens, Accenture, and PwC.
• Smart cities combined with well-informed open data policies offer opportunities for more bottom-up or hybrid approaches to smart cities that build on civic hacks, local accelerators, and university research to support the concept of “city as platform” for catalyzing innovation at a local and regional level.

Thumbnail image courtesy of: iStock/Thinkstock.

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For our Sector RoadMap^TM of Quantified Self devices we have identified five key forces and trends driving the marketplace over the next 24 months. As companies respond to these Disruption Vectors they will create new opportunities to meet these needs and compete for market share.

Key findings in our analysis include:

• Interoperability is the most important Disruption Vector. Data integration across personal and professional sources is a huge challenge. The health care industry has been notoriously slow to integrate electronic medical records (EMRs). At this point, there’s no obvious data integration supplier or platform.
• Companies that can create a data analytics business model, particularly one that supports and encourages the potential for behavioral change, will be winners. Useful analytics feedback will engage users and encourage usage, which in turn will cultivate positive health and fitness behaviors.
• Tapping into social networks is table stakes for these devices and platforms. And ultimately, the industry must move beyond the early-adopter Quantified Self crew to achieve mass scalability for health devices and services.

We evaluated a number of representative companies in the Quantified Self device and platform space. Currently Fitbit is the device maker best aligned with market forces, and Qualcomm’s 2Net, PatientsLikeMe, Runkeeper, and Withings are also in good positions.

Source: Gigaom Research

Disclosure: Fitbit is backed by True Ventures, a venture capital firm that is an investor in the parent company of Gigaom. 

Thumbnail image courtesy of JumpStock/Thinkstock.

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New types of sensor technology, rapidly growing analytics enabled by big data, and the new business models that IoT may catalyze will have a major impact on health care in the future.

Health care systems rely on complex supply chains, complex diagnostic and monitoring technology. Increasingly, where the production of health care occurs is moving away from the clinic and into the home. This opens up opportunities for everyone from cable service providers to telcos and a broad range of digital service providers to engage in the health care market and upend business as we know it.

Key findings of our analysis of this marketplace include:

• New sensors will drive medical devices and build on the momentum of wearables, which to-date have mostly focused on personalized fitness.
• Sensors and wearables will enable “citizen science” in a broader social, political, and environmental context. The health IoT, if developed in a sustainable manner with robust business models and privacy/security protection, could bring a more revolutionary paradigm to health care and medicine than genomics alone could manage.

• Health IoT, mobile health, and the slow transition to electronic medical records (EMRs) will generate vast amounts of data. The winners will be those with the power and insight to become the next generation of integrative platforms that can monetize those areas, which collectively we call the connected-health economy.

Feature image courtesy Flickr user ZM Yi

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• The Patient Protection and Affordable Care Act and the creation of accountable care organizations (ACOs) will require robust data analytics for both clinical and financial success in the coming years.
• Inefficiencies, fraud, and waste have become hot-button issues in the current financial crisis, and big data can play a major role in driving performance improvements that address these issues.
• The rapid growth of m-health and other digital-health platforms including M2M means that the data deluge will become a serious challenge if big data tools are not adopted.
• Open-data policies espoused by the U.S. Department of Health and Human Services are driving a new wave of innovative startups that address the information asymmetries and lack of transparency in health care markets.
• Health care will be personalized and customized in the coming years as genomics and sensor data as well as advances in the health-research sciences make personalized medicine more practical.

This Sector RoadMap^TM explores these drivers and looks at a sample of the companies that are making the first forays into the area of big data in health care. We also examine some of the barriers that make health data a difficult challenge for many mainstream big data firms. It’s a major issue that 80 percent of all data in health care is unstructured. Strict data-privacy laws and the particularities of the organization of the health care system have made silos and health enterprise data management difficult to tackle. Nonetheless, we are already seeing important insights from early ventures that offer great promise for addressing some of the most important organizational challenges in health care as well as basic research.

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During a Formula 1 race a driver experiences wrenching forces of more than 4.5G. His heart rate may exceed 180 beats per minute and his blood pressure could rise by half. With soaring temperatures inside the cramped cockpit he will also dehydrate, typically losing 2–3 litres of water during the race. Yet the driver must concentrate well enough to achieve lap times that might vary by just a tenth of a second. This is tough, on both mind and body. Hence it is not just the performance of the car itself which an array of sensors keeps an eye on, wirelessly transmitting data about the engine, suspension and so on to the pit crews. The drivers’ own vital signs are constantly monitored, too.

—Economist, Nov. 3, 2011

Wearable computing, or wearables, has recently moved from the realm of science fiction and military technology to being on the cusp of commonplace consumer technology. ABI Research estimates the global market for wearables in health and fitness could reach 170 million devices by 2017. Adding further momentum to the growth of the market is the entry of most of the major platforms into the space, including Google, Microsoft and Apple.

The first several decades of wearable computing failed to produce any notable success stories on the consumer front, but advances in materials sciences, battery power, augmented reality and chip evolution have made the possibilities for wearables grow rapidly. Google’s recent unveiling of Project Glass has garnered a great deal of attention, but the market is much broader and includes fashion, health and wellness technologies, and technologies for the aging and disabled. As the quantified-self trend gains traction the use of wearables will grow too. This report covers wearables across these verticals as well as provides examples of how applications developed in one area can enable blue-ocean strategies to open up new market opportunities. (Blue-ocean strategies imply not competing with existing market competitors but instead opening up the market space, or blue ocean, to make the competition irrelevant.)

Finally, one of the more interesting aspects of wearable computing is the potential impact it could have on the form function of mobiles down the road. Much of the functionality of a smartphone can currently be rendered within a wearable device, and as wearable devices become more common over the next decade mainstream devices such as the cell phone may be rethought.

The post The wearable-computing market: a global analysis appeared first on Gigaom.

There are a number of devices and platforms used widely by quantified-self practitioners, including:

heart-rate monitors and fitness devices that track length of workouts, calories, time
sleep-tracking devices
wireless scales and blood pressure cuffs
social media platforms such as the Quantified Self blog and LinkedIn groups
data analytics and dashboard services such as InsideTracker.com

The movement is beginning to have an impact on medicine. When patients who have been using self-tracking tools appear at a clinical encounter with data from several months of tracking activities, it can have a profound impact on the encounter, which can be shifted to a more partnership-based model. But for this to happen, we will need to have better tools to facilitate clinician engagement with patient data as this trend accelerates. Organized communities of quantified-self practitioners also have a more prevention-focused ethos that is quite different from the traditional curative focus of biopharmaceutical companies. The large quantified-self platforms such as CureTogether.com are demonstrating the power of the quantified-self movement to conduct legitimate research with traditional research entities.

More work on data policies and ownership may be important in the coming years as the movement takes off. As insights from these communities get translated into monetized products there will be a need to demonstrate benefit sharing and some form of commons-based production to share the benefits of the research and to ensure further engagement of participants and equitable benefits.

The post The quantified self: hacking the body for better health and performance appeared first on Gigaom.

The current norms and practices are increasingly coming under direct assault by a myriad of social and technological forces that are rapidly eroding business as usual. To be competitive and successful in the future business world, individual workers and entire organizations and firms will have to master new skills in the data sciences and the ability to work in a cooperative or collaborative fashion (in contrast to competition’s being the primary driving force). These same tools may ultimately transform not only how work is accomplished but also the form of the organizations themselves.

Further, at the heart of the future of work and the future firm will be the role of information and how we collect it, manage it, share it and ultimately move from data to information and knowledge to the wisdom that will drive the next generation of innovative products and services.

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