T.P. Caruso & Associates

Envisioning a digital infrastructure for a Learning Health System

Basis Band as an Alternative to FitBit

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Maybe you are considering a self-generated health information (SGHI) wearable – sometimes called a health and fitness device that can be worn on the body – as a gift for someone? I can recommend the Basis Band over FitBit unless you immediately need integration with other health and fitness apps you are using, such asRunKeeper, MyFitnessPal, or Tactio Health, since Basis has not yet added features that integrate these apps.  Eventually when Basis completes the full functionality of their API you can simply use TicTrac, the application integration platform for this purpose and get much more integration than you probably need.  I’m also hoping for the API so we can download information using the Validic API.

Basis_Page.ActivityDetails

Basis Activity Details page provides skin temperature (purple), perspiration (blue), heart rate (orange), calories (green bars), and steps (yellow bars). It also provides sleeping, awake and active time bar below the graph.

I like all the parameters that the Basis Band measures.  It has multiple sensors that measure optical blood flow, 3-axis acceleration, perspiration, and skin temperature.  As a result this SGHI wearable device can capture your heart rate, exercise activity and intensity, stress levels, and sleep quality.  All that FitBit can measure is activity level and whether you’re going up or down (i.e. to measure “floors”).

Basis provides the detailed data so that you can look at how these measures may be related to your behaviors during the day and your sleep at night.  You can view one or more of these by selecting options on the left side of the activity details page shown here.  This is a snapshot of just one of my days, but it does appear after looking at multiple days that my perspiration increases throughout the night and drops quickly when I get up.  I’m probably getting warmer under the covers all night and then when I jump out of bed in the morning I am quickly cooled by the ambient temperature in our cold apartment.  By pointing to any point of the display you can determine details about that particular point in time, including any of the parameters that you have selected to view.  For instance, I can see that during exercise my heart rate only gets up to about 113 while my resting heart rate is close to 63.  I’m thinking that I need to push myself a little harder to get that rate to double as is recommended for a rigorous exercise routine.

Basis_Page.Habits

What I really like about the Basis product are the “Habit” options.  Basis provides a wide range of options for motivating your behavior changes.  It allows you to start with one, initially just wearing the band 12 hours per day, and once you complete this you can add another and so on until you have successfully achieved each of your new habits.

In a couple days I was able to earn enough points to start on three habits: wear time at 12 hours per day (“Wear It”), steps at 8000 per day (“Step It Up”) and regular running at 30 minutes per day (“Run Club”).  I didn’t achieve all of them every day, but I earn points each time I achieve a goal that Basis calls a Habit.  The fourth Habit that I added encourages me to get up from sitting as often as I can, which I set too low for the first week at 30 minutes.  I couldn’t get the amount of times between walking to less than 45 minutes between 9 and 5, so this week I increased the goal to 1 hour 30 minutes.  I have to find where I can reach the goal, and then I can push myself to get better from that point.  Isn’t that the point of goals?

Basis_Page.Insights

Basis provides many other options for Habits.  For Activity it has taking a morning or evening lap, riding a bike, burning calories, or increasing the time you are active.  FitBit allows me to set my primary goal to time of activity or calories, but it does not support biking goals or period goals like the morning or evening laps, though it could easily provide period goals in the future.  Basis also has goals you can set for sleep behavior motivation, including setting a more consistent bedtime, regular rising time, or just an effort to get more sleep in the evening.

Another page provides some summary of your daily activities and shows how you earned points that day for successfully achieving your goals.  This is the same information that you would receive on your phone if you allow the Basis smartphone app to provide you with notifications.  Furthermore, it breaks your walking and running periods into components so you can see how your activity was spread throughout the day.  For instance, the figure shows two periods of walking from 1:08-1:15 PM and 4:51-4:58 on Sunday, December 8th.  You can click through each of these items to see more detail about them.

Basis_Page.PatternsThe Patterns page is another feature of Basis not provided by any analytics I have found for FitBit.  This graphic allows the user to step through each of the measured items including calories, perspiration, skin temperature, steps, and heart rate to see any patterns in how they vary throughout the day.  I can’t actually see anything easily from the week that I have been using Basis, except what one might expect, which is that I exercise mostly in the afternoon, increasing the calories (shown here) at those times.  The other times  when I have good calorie use are more interesting probably associated with periods of walking to and from work, or when I have to walk across campus which I did at least once last week.

Generally I like Basis for its analytic possibilities, but I’m discouraged by its lack of connections to other SGHI apps and devices.  For instance it does not integrate with information from my FitBit or RunKeeper, or worse yet, an API isn’t available for companies like TicTrac to allow downloading of the information into their powerful cross-application analytics interface.  One can now download the information from Basis into a spreadsheet, but that’s really only for the most dedicated Quantified Selfers with some technical skills and knowledge of how to use spreadsheets.  Hopefully Basis will get their API working soon because the rest of what they offer is encouraging and exciting for all the possible behavior changes that could come out of this information.

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UPDATE:

Basis adds Zeo-like advanced #sleep tracking to wristworn tracker #SGHI #SmartWatches #Trackers #Activity

Filed under SGHI, Wearables

Health Record Banks as a Solution for a Self-Generated Health Information Exchange

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One of my Self-Generated Health Information Consortium Steering Committee members introduced me to the concept of a health record bank (HRB, though I have been thinking along these lines for awhile now as reflected in my “Transforming Health Research through Use of a Secure Health Data Cloud” presentation made in December 2011 in Saudi Arabia as part of my efforts to develop Quantal Semantics, Inc.).  My investigation of this concept led me to the Health Record Banking Alliance as well as HRB business model and HRB architecture white papers about this concept for health information exchange.  I followed up with Bill Yasnoff the founder of the HRB Alliance and he has been very generous with his time to explain HRBs as well as a specific business plan for moving forward with an HRB.  I’ve asked many questions and I’m hopeful that this maybe the sustainability solution for self-generated health information exchange as well as for provider-generated health information exchange.

Unlike current efforts at providing health information exchange, an HRB is a store of all of an individuals health information in one account.  Access to this information is controlled by the individual or their proxies (i.e. family members).  Information is uploaded to the individual’s HRB account each time an entry is made in a healthcare provider’s EHR about that individual.  This would include doctors notes, lab reports, etc. that update the information for the individual in those EHRs.  The first provider that uploads information and creates the HRB account for the individual, gives that individual an account number from the HRB.  The individual can then provide that account number to any of its healthcare providers, or on their online accounts of self-generated health information (i.e. from mobile health apps or health and wellness devices, etc.).  This information is then all aggregated in the individual’s account where they are able to annotate it and control the sharing of that information.

An HRB would allow the individual to see all their information in one place, and when that information is needed it is efficiently located without any requirement for aggregating the information, as would be needed by current approaches to health information exchange.  As a result, the HRB gives the individual better control over their health information, allowing the individual to not only control who sees any portion of their health information, but also the ability to annotate it and to monitor who actually accesses the information.  Furthermore applications could be developed that would allow individuals to notify themselves or loved ones when their information is accessed, and if the information is accessed in some emergency situation by a provider, those family members who want to know about such an emergency can more quickly respond without waiting for a call from the emergency provider as they do today.

Furthermore, individuals who are interested in supporting research into disease could share their information, and they could potentially obtain funds for sharing that information from the organizations who want to access the information for research purposes.  The possibility of generating income from one’s information will create a variety of business models that will promote the development of higher quality data and larger aggregates of data for improvements in research, and even better efforts to personalize medicine.

The challenge is to get the healthcare industry to support this effort, and Dr. Yasnoff has a solution for that as well.  He proposes to use the funds generated from research uses and other applications sold that use this HRB platform, to support the implementation of EHRs by physician practices.  A discussion I had last night with a physician practice management organization suggests that this would be a viable idea from their perspective.

The Mobile Health Model that will Transform Healthcare

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I’ve been thinking about how a company can take advantage of the opportunity presented by a mobile health (mHealth) app.  It’s not by selling the mHealth app, and though there might be money in the information generated from a large number of users of an mHealth app, no investor will give a company money for such a business model without confidence that a large number of users will download and use the app.  Furthermore, these approaches really are not addressing the underlying issues driving payer compensation for health-promoting products and services.  Instead, I think the mHealth app must serve as a new form of interface to a healthcare provider.

I foresee that mHealth apps will provide access to a phone bank run by well trained responders supported by nurses and physicians, not unlike those banks of professionals who provide case management services for people with high cholesterol, diabetes, chronic obstructive pulmonary disease, etc.   Sure they’ll also have evaluation questionnaires to assess the state of a user’s medical problem and whether they might be included in social network groups with which they might share their experiences with people who have similar issues, as well as information resources and tools like medication and appointment reminders.  However, it will be their connection to a healthcare provider who can coach and monitor an individual’s progress, reacting when some parameter reaches some threshold, that will allow mHealth apps to transform healthcare as we know it today.

Especially with prices for healthcare visits and tests driving insurance to such high levels, the individual will be seeking insurance providers who provide the most cost effective healthcare technologies, while mHealth apps linked to healthcare providers are a great way to keep healthcare costs down while improving the care of individuals who use these approaches to meeting their health goals.

So companies that are offering mHealth apps need to be thinking about how to provide a healthcare service as a core component of their app.  Those apps that include real connections to providers will be the killer mHealth apps of the future.

Self-Generated Health Information – The Future of Caring for your Health

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Patient Generated Health Data which we have renamed, and generalized as Self-Generated Health Information (SGHI), according to Shapiro, Johnston, Wald and Mon (1) includes:

“…health history, symptoms, biometric data, treatment history, lifestyle choices, and other information – created, recorded, gathered, or inferred by or from [individuals] or their designees (care partners or those who assist them) to help address a health concern.”

Products producing SGHI may have been in the hottest market space at the Consumer Electronics Show (CES) as shown by the number of newly introduced devices (2).  Fifteen of these devices created excitement at CES this year.  Partners Healthcare also launched a program they call Wellocracy, which promotes the use of devices creating SGHI to motivate individuals to set and obtain health goals (3).  Joseph Kvedar who leads these efforts for Partners says his research has shown that these devices can be used to keep people out of the emergency room.

This demonstrates the reason for all the SGHI device activity.  Reducing emergency room admissions is a major objective for healthcare organizations that are trying to respond to the new payment initiatives defined by the Acountable Care Act: Accountable Care Organizations (ACOs).  As a result, the driver of care cost reduction is moving away from health insurance companies like Aviva and the various affiliates of BlueCross BlueShield, and towards the care provider in a healthcare organization who will be increasingly encouraged to find ways to keep their patients out of their offices.

While the general expectation is that individuals, as they age are increasingly concerned about their health.  We can watch as the $1.9 trillion size of wellness markets that include markets like beauty and anti-aging, fitness and mind-body exercise, healthy eating/nutrition and weight loss, preventive/personalized health (in which these SGHI devices would be counted), complementary and alternative medicine, wellness tourism, spa, medical tourism, and workplace wellness have been increasing steadily in lock step with this phenomenon as the Baby Boom generation is aging well into their sixties and seventies (4, 5).  The Accountable Care Act (ACA) of 2009 further reinforces these trends as the traditional healthcare systems have failed to control costs and are further burdened by a rapidly aging population.

(1) Michael Shapiro, Douglas Johnston, Jonathan Wald, and Donald Mon.  Patient-Generated Health Data White Paper, prepared for the Office of Policy and Planning, Office of the National Coordinator for Health Information Technology, April 2012, pp. 6.

(2) Jonah Constock.  Slideshow: Health devices that launched at CES 2013, MobiHealthNews.com, Posted January 10, 2013, Last Viewed January 19, 2013.

(3) Bernie Monegain.  Wellocracy launches at CES, mHIMSS, Posted January 9, 2013, Last Viewed January 19, 2013.

(4) Estimated gobal market size of the wellness industry clusster in 2010.  SRI International. Posted by Statista 2013.  Last Viewed January 19, 2013.

(5) Dulcy Gregory.  Wellness Is No Passing Fad: Global Market Estimated at Nearly $2 Trillion. SRI International.  Global Spa and Wellness Summit, Blog Posted June 24, 2010.   Last Viewed January 19, 2013,

Use of NextGen Diagnosis and the Healthcare Reimbursement System in the U.S.A.

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The U.S. has a dilemma concerning genetic tests because health insurance companies may abuse knowledge of this information to modify health insurance premiums.  Health insurance reimbursement is the central issue underlying health information privacy concerns.  I don’t want my insurance company knowing about the factors that might predict the costs associated with my healthcare in the future, so I don’t want them to know my genetic information.  But this has a huge impact on my ability to learn about what type of care I might need because healthcare providers want to limit their exposure to liabilities associated with (1) accidentally releasing this information to insurers, and (2) knowing my genetic predisposition to disease without taking appropriate action.

In this era of next generation sequencing (NGS), we can already generate a huge amount of information about my health and the health of my parents and children, simply by knowing specific sequences of my DNA.  And in the near future, if my entire genomic information were available to health researchers who could link clinical information to NGS information, the possibilities are limitless about what could be learned about how to better care for me and my family.  However, healthcare companies in the U.S. don’t want this information because it creates too much of a privacy liability for them, not to mention the liability of withholding information that eventually results in costs that they could have prevented with the knowledge of this information.

The first of these problems, related to privacy concerns, is not a problem anywhere else in the world because health care is paid by a single payer which will pay for an individual’s care no matter what genetic predispositions they may have.  In the U.S., EHR systems are not capable of segmenting some genetic information from all genetic information based on what information an individual wants to share with his care providers and what information he or she wants to keep private.  U.S. healthcare providers are therefore debating what genetic information to keep out of my healthcare record so there is no record of it at all, and generating only information that is absolutely required because I have requested it or my care requires that it be obtained.

Before I can really get the benefits from this information, I will need to take full control of my electronic health record (called an electronic personal health record, or ePHR), just as I have taken full control of my personal financial records.  I will then be able to decide what information to share and with whom I want to share it.  I will also decide if I want to allow some organization to accumulate some or all of my genetic and clinical information for research purposes, and until I am certain that my genomic information – which I had no way to influence – will not effect my insurance costs, I’m not sharing it with anyone.

It will be a long time before we get all the benefits from information we can now generate easily.

Filed under Health Care System

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