There is a lot of buzz regarding the Internet of Things (IoT) and what new capabilities are made possible through the networking of all types of devices, both in the consumer and the commercial market. Many of the potential issues with the concept have also been documented (need for large pool of Internet Protocol (IP) addresses, really good security, privacy, safety, etc.). The segment where IoT could have a profound impact is health, thus the Health[care] IoT (HIoT). This will really make possible the concept of Connected Health , which in turn will make the Continuum of Health (CoH) a reality.
HIot and Connected Health go beyond telehealth and the remote delivery of health by physicians. They define the interconnections of devices that regulate functions, record biometric data continuously or on demand and at frequent intervals, when it is convenient for the individual. It extends to the transmission, storage, security, access and analysis of the data for the benefit of the individual and the population.
CoH is defined as a continuous cycle starting with wellness, preventive and proactive healthcare, transitioning to clinical healthcare and extending to post clinical care, home health, remote monitoring and back to wellness. This cycle describes the phases of healthcare during a lifetime. There is the promise of predictive and preventative health (identifying and treating issues early-on before they become an emergency) as having the potential of reducing hospitalisation and lowering treatment costs.
The technology to achieve HIoT is mostly available. The Continua Alliance  has been looking at connected health devices for years and has defined standards and guidelines Devices are available from a number of vendors, many of which are household brands, especially in clinical settings, and others are from new companies which have realised the promise and opportunity of IoT and connected devices. As data is generated by these devices, there are companies which are focusing on the analysis of this data, some following traditional "store and analyse" methods and others exploring "streaming analytics" methods (analysis of data in real-time), in order to identify present conditions and predict future situations. To make all this possible, what is needed is the will to develop the integrated systems to deliver the promise of HIoT and cut across company/organisation/industry/government interests and deliver solutions which put the individual first. Two other important items that need to be addressed, to make HIoT a success, are interoperability and standardisation, which will make configuration, integration and data exchange easier, effectively making it simpler for end-users to deploy. The CommonWell Health Alliance  is looking into these topics and the interoperability between health IT systems.
The one single item which could derail the promise and potential of HIot is security. There are many medical devices which are used to regulate various functions (e.g. pacemakers). Should such devices are compromised, attacks could be implemented to impact the safety and health of the patient. Here security needs to address the device itself and all its components (hardware and software), wireless and wired communications (WiFi, Internet, phone lines, etc.), any devices used to communicate with the medical device (home monitors, smart phones, etc.) and software running on such devices (embedded applications, mobile applications, etc.), plus extended systems, like those in health facilities and at the device manufacturer. Such medical devices effectively become critical assets  where a security breach may result in a life and death situation.
The market is huge and global, to support many participants and allow for growth and profitability. Of course for this to happen there is the need for a shift from business as usual. The technology is the easy part. Habits, interests, policies, regulations will determine whether HIoT will deliver its real potential. HIoT is a data driven market and it should be acknowledged that the individual should own and control their data and determines to whom this data can be made available and how can be used. This is private, personal data, which should not be considered the property of the provider, the payer or some other third party. Third parties could and should have access to anonymous data for population health purposes, which would benefit the whole society. Individuals should have full control and access to all their data (whether considered PHR or EMR based on today's terminology) and make it available to providers when needed. This will also require rethinking the concept and purpose of PHR, EHR and EMR data and should enable transitioning to a "patient centric" health model.
Big Data is in the news on a daily basis, both in the business and mainstream media. It is hard to avoid stories about personal data collected from smart phones, web sites, online retailers, social media, personal fitness devices. The list is almost endless and many organisations make considerable investments into the collection and analysis of such data. On the other hand, the value realised by companies and consumers is not well quantified.
I would like to focus on the fitness/wellness data collected by the numerous wearable (fitness tracker) devices. There is certainly a huge amount of data generated and collected on a daily basis. Most of this data is made available and presented, through mobile applications and web sites, in beautiful coloured graphs, charts and trends showing changes over time.
A recent study, conducted by researchers from Iowa State University and published in Medicine & Science in Sports & Exercise  compared the accuracy of eight consumer fitness trackers against lab equipment that also measure energy expenditure. The results showed that consumer fitness trackers are not as accurate as lab equipment and the error rate ranges from 9.3% to 23.5% (based on the trackers tested). A similar study conducted by researchers from the University of Pennsylvania and Amherst College and published in the Journal of the American Medical Association  showed that smartphone applications are as accurate as wearable devices at tracking activity. So that leads to the question of the value of all the fitness data collected by these devices. Is there real value in collecting and trying to analyse the plethora of this data or the devices should be seen only as motivational tools prompting you to be active and exercise?
The other side of this has to do with the objectives of using wearable devices, how the data is being used by the users and perceptions about that data. It is clearly the case that wearable device data should not be used to make decisions regarding wellness or health and definitely cannot be used by medical professionals. This is because these devices are not medical devices, have not received FDA clearance and the data collected is not at the accuracy required by medical professionals. So what good is all this data and is there a better way?
There is some value in the data collected by wearable devices. Even though these are not medical devices and the data is not very accurate, a user can get information about their activity and trends over time, especially if weight information is also part of that data. Then analysis of the data can show the relationship between activity and weight. But how about if a user needs to control their blood pressure, glucose, cholesterol, etc. Then the consumer devices have little value and FDA cleared medical devices should be used.
This is where a lot of actual value could be realised. Medical devices can be used for obtaining measurements and sharing those with clinicians, for tracking health. Medical devices should be used in conjunction with wearable devices. They can be available at exercise, office and other easily accessible locations. Medical devices offer the ability to monitor the general status of wellness and, as non-invasive devices get better and obtain FDA clearance, also monitor glucose, cholesterol and other parameters. Currently integration with personal-use devices, like glucose meters and the automatic recording and aggregation of that data can greatly contribute to awareness about personal wellness and the active engagement of the individual in the participation and monitoring of their wellness.
How many people check their blood pressure on a regular basis? Most do it once or twice a year, when they visit their doctor. It would be far more constructive and informative to be able to check blood pressure more often (monthly, weekly, even daily). Such data, that is accurate, could contribute toward obtaining a better understanding of the personal and population health and developing strategies to improve it. A good starting point would be the use of self-service integrated medical devices which can measure multiple parameters, including weight and blood pressure.
The longitudinal data and sharing it with clinicians, plus the ability to set goals and generate alerts based on readings and progress toward those goals could further contribute toward monitoring, controlling and improving population health. The combination of medical and wearable device data would generate an even larger pool of data to drive analytics and generate actionable insights. But it will also necessitate putting the data at the hands of the individual and let them control who can have access to that data and for what purposes.
Such capabilities and this type of individual engagement could have a profound impact to the overall population health and lead to reduced healthcare expenditures, thus freeing budgets for investments into other areas which could spur economic activity. That would definitely support the thesis that Big Data has real value and could positively contribute to the society.
 Jung-Min Lee, Youngwon Kim, Gregory Welk; Validity of Consumer-Based Physical Activity Monitors; Medicine & Science in Sports & Exercise; September 2014, Volume 46, Issue 9, p. 1840-1848.
 Meredith Case, Holland Burwick, Kevin Volpp, Mitesh Patel; Accuracy of Smartphone Applications and Wearable Devices for Tracking Physical Activity Data; The Journal of the American Medical Association, February 2015, Volume 313, No. 6, p. 625-626.