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Measuring Steps to Patient Empowerment – Breakaway Thinking

Posted on November 19, 2014 I Written By

The following is a guest blog post by Jennifer Bergeron, Learning and Development Manager at The Breakaway Group (A Xerox Company). Check out all of the blog posts in the Breakaway Thinking series.
Jennifer Bergeron

Trends and fads come and go. When they stick, it’s clear they address a consumer need, whether it’s a service, promise, or hope. Here at The Breakaway Group, A Xerox Company (TBG), we operate within a proven methodology that includes metrics, and it’s exciting to those of us who can’t get enough of good data. Most people find metrics interesting, especially when they understand how it relates to them, and the results are something they can control. Metrics are powerful.

To understand the power of data in shaping behaviors, consider the popularity of the self-monitoring fitness tracker or wearable technology. Even as their accuracy is scrutinized, sales in 2014 are predicted to land somewhere in the $14 billion range.1 Do mobile fitness trackers actually help people change their activity habits? Could doctors actually use the data to help their patients? Can companies be built on the concept of improving health with a wearable device? Not conclusively.2 Does a dedicated athlete need this kind of information? Some think not.3

So what is driving the growth of the fitness tracker market and what are these devices offering that creates millions of dedicated users? The answer is real-time data, personalized goals and feedback, and a sense of control; in other words, empowerment.

In the 70s and 80s, my grandparents spoke about their doctor as though he were infallible. They didn’t doubt, question, or even note what he prescribed, but took his advice and dealt with the outcomes. If healing didn’t progress as planned, my grandmother blamed herself, as though she’d failed him.

Jump ahead a few decades when more emphasis is being placed on collaboration. We expect our physicians to work with us, rather than dictate our treatment decisions.4 Section 3506 of the Affordable Care Act, the Program to Facilitate Shared Decision Making, states that the U.S. Department of Health and Human Services is “required to establish a program that develops, tests and disseminates certificated patient decision aids.”5 The intent is to provide patients and caregivers educational materials that will help improve communication about treatment options and decisions.6

Patient portals are important tools in helping to build this foundation of shared information. The portals house and track patient health data on web-based platforms, enabling patients and physicians to easily collaborate on the patient’s health management.7  Use of patient portals is a Meaningful Use Stage 2 objective.

The first measure of meeting this objective states that more than half the patients seen during a specified Electronic Health Record reporting period must have online access to their records. The second measure puts the spotlight on the patient and their use of that web-based information. MU Stage 2 requires that more than 5% of a provider’s patients must have viewed, downloaded, or transmitted their information to another provider in order for the provider to qualify for financial incentives from the Federal government.8

Empowered consumers want information immediately, whether it’s a restaurant review, number of steps taken in the last hour, how many calories they’ve burned, or their most recent checkup results. We like to weigh the input, make a decision, and then take action. Learning and information intake, no matter the topic, is expected to happen fast.

Metrics show us where we stand and how far we’ve come, which empowers us to keep going or make a change, and then measure again. We’re in an age of wanting to know but also wanting to know what to do next. The wearable device market has met a very real need of consumers. Whether or not fitness trackers make us healthier, whether or not our doctors know what to do with the information, or if this is information an athlete would really use, these devices can serve the purpose of putting many people in control of their own health, one measurable step at a time.

Sources:
1 Harrop, D., Das, R., & Chansin G. (2014) . Wearable technology 2014-2024: Technologies, markets, forecasts. Retrieved from http://www.idtechex.com/research/reports/wearable-technology-2014-2024-technologies-markets-forecasts-000379.asp

2 Hixon, T. (2014) . Are health and fitness wearables running out of gas? Retrieved from  http://www.forbes.com/sites/toddhixon/2014/04/24/are-health-and-fitness-wearables-running-out-of-gas/

3 Real athletes don’t need wearable tech. (2014) . Retrieved from http://www.outsideonline.com/outdoor-gear/gear-shed/tech-talk/Real-Athletes-Dont-Need-Wearable-Tech.html

4 Chen, P. (2012) . Afraid to speak up at the doctor’s office. Retrieved from  http://well.blogs.nytimes.com/2012/05/31/afraid-to-speak-up-at-the-doctors-office/?_r=0

5 Informed Medical Decisions Foundation. (2011-2014) .  Affordable care act. Retrieved from http://www.informedmedicaldecisions.org/shared-decision-making-policy/federal-legislation/affordable-care-act/

6 HealthcareITNews. (2014) . Patient pjortals. Retrieved from http://www.healthcareitnews.com/directory/patient-portals

7 Bajarin, T. (2014) . Where wearable health gadgets are headed. Retrieved from http://time.com/2938202/health-fitness-gadgets/

8 HealthIT.gov. (2014) . Patient ability to electronically view, download & transmit (VDT) health information. Retrieved from http://www.healthit.gov/providers-professionals/achieve-meaningful-use/core-measures-2/patient-ability-electronically-view-download-transmit-vdt-health-information

Xerox is a sponsor of the Breakaway Thinking series of blog posts. The Breakaway Group is a leader in EHR and Health IT training.

A Treatment Plan for Technology in Health Care

Posted on May 16, 2014 I Written By

The following is a guest blog post by Andy Oram, writer and editor at O’Reilly Media.

The kind of health care reform that brings better care at a reasonable cost will consist of many, tightly interlocking strands. Each of us—everyday consumers and patients, health care providers, payers and public health officials, technology developers, policy makers, and clinical researchers—can do specific things to push health care forward, and many of these involve computer technology.

During a stint in the mental health field, I would meet regularly with a team of professionals from different disciplines (and with the patient) to work out a treatment plan. This article similarly lays out some tasks each of us in his or her respective fields can carry out. Like the meetings I attended many years ago, this is a collaborative approach where my suggestions are meant to elicit constructive responses and push-back.

Naturally, a treatment plan must start with a firm diagnosis and an assessment of the patient’s strengths and weaknesses. For health information technology, I try to provide that assessment in my report, The Information Technology Fix for Health: Barriers and Pathways to the Use of Information Technology for Better Health Care. Refer to it for background as we jump into action and assign tasks to each stakeholder.

Consumers/patients/citizens:

  • Measure the vital signs that are important to your health, and extract them from the silos of devices or vendor web sites into your personal health record. The Blue Button Initiative promotes open standards that increasingly bring within your reach the records that others hold about you.
  • This process is important because physicians will need your statistics to carry out effective diagnoses and planning—for instance, to know whether you need to make an office visit and even to check into the hospital. Collecting this data also means the clinical staff can review it before a visit and not waste your whole 15 minutes asking you about your condition.
  • Casual readers may see this advice as simply an appeal to join the Quantified Self movement, but it is much, much more. Vital signs give you leverage that can drive change throughout the health care system. First, it creates a pressing need for the doctors’ electronic medical records to open up and accept patient-generated data. It can also lead to discussions about who owns your data—it should be you—and who gets to use it for research or other purposes. The ripple effects can render the entire health care industry more responsive and intelligent in handling patients—and also more respectful of their right to control the flow of their data.

Health care providers:

  • Get involved in the design of the technologies you used. Demand to be on the design team, not just consultants on the sidelines, and demand that the software be easy to customize in deep ways that respond to your ways of doing things.
  • This endeavor goes beyond ease of use and even beyond the prevention of errors related to confusing interfaces. It determines the types of data collected, when you can input and change the data, and whether it can empower the patients to choose life-enhancing behaviors. Therefore, advocate for data that patients can also use and understand, because they are responsible for their own behavior. Finally, insist that electronic record systems maintain public databases that can log the errors you find, as recommended in a recent  government report.

Payers and public health officials:

  • Collect and release data to support clinical and cost-containment analyses by providers, payers, and consumers, working with them to ensure the data’s value, accuracy, and usability.  To open its secrets to modern analytical tools, data needs to be consistent, formatted in programmer-friendly ways, and timed to be delivered to the public promptly and regularly.
  • What will be the payback for the investment in shared data sets? Treatment depends on clinical research, but it is well understood now that double-blind clinical studies can’t solve every problem: they are usually short-timed and their subjects are often unrepresentative of realistic populations, so they are often overturned in the field. Therefore, studies need to augmented by longitudinal, large-scale analytics (“big data” solutions) that can turn up trends hidden by the idiosyncrasies of double-blind studies. And your data is lifeblood of large-scale analytics.

Technology developers:

  • Work on free and open source software solutions instead of competing with all your fellow developers to reinvent the programming wheels. Extending the Fast Health Interoperable Resources (FHIR) standard with fields focusing on patient-generated data would be one good step. Open source software does not prevent you from making money from your investment in a variety of ways, including web solutions (Software as a Service). In fact, combining efforts in free software solutions will give you more and better software, because you can exploit the contributions of everyone who is part of the development community. Free, open software also eliminates the current tussles over standards, because data formats will be transparent and therefore easy to produce and consume.
  • The freedom to change and redistribute software will ultimately improve clinical settings as they can adapt the software to their needs, an especially important value to carry software to diverse regions of the world.

Policy makers:

  • Require the collection and exchange of data about patients, providers, and public health (with the consent of the patient) to become an automatic part of the workflow within institutions, between institutions, and between provider and patient. The Meaningful Use guidelines make a start toward interoperability, but the certifications and showcases are not enough to ensure that it’s clean and structured consistently, or that the formats permit viable comparisons.
  • Breaking down the silos between the providers’ data sets will also break down the silos of their thinking and allow better interventions in patients’ medical conditions. It will also welcome the addition of patient-generated data and observations of daily living, a rich source of information that will flesh out lab tests and other data from clinical visits.

Clinical researchers:

  • Develop trials to validate that the new wave of low-cost applications and devices are accurate, safe, and effective. Traditional double-blind clinical trials are usually too expensive and slow to fit the budgets and schedules of modern technology development, so seek out sleeker, cleverer types of tests to provide the necessary validation.
  • Your efforts will be much more than a leg up for companies making medical devices and software The validation of apps and devices will enable doctors to confidently prescribe their use and insurers to pay for them. They will, in turn, lead to a flood of new, patient-generated generated data that will significantly fine-tune treatment—especially when interoperability allows providers to collaborate—and will combine with open data sets to generate new treatments.

This treatment plans focuses on technology because it is a great facilitator, providing the tools and environment for effective treatments and reduced costs. The plan will not in any way diminish the other, less technologically focused stakeholder tasks. Public health officials still have to clean up poisonous environments, battle against obesity and tobacco use, and reduce disparities in gender, race, and environment. Doctors still need to learn compassionate care. Payers should move resolutely to fee-for-value reimbursement—although with a recognition that the data needed to properly stratify patients is sometimes scant—and expand their guidelines to include innovative treatment approaches such as telehealth and games. Clinical researchers still need to uncover whatever factors in the genes and other “omics” differentiate between patients in order to hone in on effective individualized treatments. Everyone with health problems should join support networks.

Progress depends on reformers building relationships with the players named in this article and determining how the interests of each player can be bent to meeting the goals of reform. For instance, take one of the dilemmas mentioned in this article: that devices and software apps are underutilized because they are unvalidated. The players we need to involve are:

Payers: They have an interest in bringing down the out-of-control costs of chronic illnesses that are making their plans unaffordable. This motivates them to encourage the use of medical devices and apps for day-in, day-out patient engagement and monitoring. But they want only devices and apps whose effectiveness has been validated.

Technology developers: They have an interest in getting their devices and apps validated so that they can be integrated into medical care and funded by payers, but double-blind clinical trials are too expensive and time-consuming for this purpose.

Clinical researchers: They have an interest in finding new funding, because traditional sources such as NIH and pharma companies are cutting back.

Consumers/patients/citizens: They urgently want to overcome chronic health conditions—but with solutions that are rock-bottom simple and low-cost. The consumer devices and free or low-cost apps can be this solution if they’re validated and covered by insurance.

The solution may therefore involve persuading payers to fund clinical researchers to develop new validation methods, perhaps by running modern “big data” statistical methods over data provided by payers and others. These methods, when shown to be good enough, can lead to quicker approvals for devices and apps and ultimately to realizing the promise of patient tracking.

Technology remains a key part of the mix. As stakeholders come to understand how technology can help them meet their goals, they can assess the status of the technologies and demand improvements that realize the mission of improved health care.

Connecting Smart Mobile Devices to the EHR

Posted on January 9, 2014 I Written By

Katherine Rourke is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

My colleague, John Lynn, posted a hilarious CES marketing video advertising a new product it calls the iOximeter.  The iOximeter, which operates on both the iOS and Android platforms, is an independent device which attaches to smart phones, turning the phone into a pulse oximeter.

I strongly suspect that an i-glucose meter, i-scale and i-blood pressure cuff designed for the mass consumer market are starting to make major headway.

Not to be Scrooge at the Christmas party — I think such devices are a very positive development — but I’m left wondering what the purpose of getting the data onto the phone really is.  After all, unless the data gets to a physician conveniently, and ideally comes to live in their EMR, just how much good does it do?

On the consumer side, it does little but add bells and whistles to products consumers are increasingly used to using anyway, given that the price point for these devices is low enough that they’re sold in consumer pharmacies.

On the provider side meanwhile, you’re left with data that, while it might be arranged in pretty charts, doesn’t integrate itself easily into clinicians’ work flow.  And with EMRs already dumping huge volumes of data into their laps, some physicians are actively resisting integrating such data into the records.

No, the existing arrangement simply doesn’t do anything for clinicians, it seems.  Yes, consumers who are into the whole Quantified Self movement might find collecting such data to be satisfying, but the truth is that at this point many doctors just don’t want a ton of consumer-driven data added to the mix.

To make such phone-based devices useful to clinicians, someone will probably have to create a form of middleware, more or less, which accepts, parses, and organizes the data coming in from mobile health app/device combos like these.  When such a middleware layer goes into wide use, then you’ll see hospitals and doctors actively promote the use of these apps and devices.  Until then, devices like the iOximeter aren’t exactly toys, but they’re not going to change healthcare either.

Healthcare Pricing, Wiki Style EMR Editing, and Quantified Self Data – @nickdawson Edition

Posted on August 4, 2013 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 15 blogs containing almost 6000 articles with John having written over 3000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 13 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

It’s time again for my roundup of interesting EMR, EHR, and Healthcare IT tweets. Today’s tweets all come from Nick Dawson. I don’t know Nick really well, but see him online quite a bit. Plus, I did a Google Plus hangout with him after TEDMED. He’s a very interesting guy and these tweets illustrate some of his thinking.


I’ve been hearing more and more of these cases and many of them are not even international. I’m not sure if the shift is because of the growth in high deductible plans, but there’s definitely a shift happening as far as awareness of what healthcare really costs. I hope we see a sea change in this regard.

Also, don’t underestimate the medical tourism part of this. I think there are going to be regions of this country and around the world that are going to battle for medical procedures. Eventually we’ll know that certain regions of the country are known for certain medical specialties just the same way we know Texas has oil and Nebraska has corn.


Just the thought of this will make many doctors stomach’s churn, but I like the concept. It would definitely need to be refined so there was a well defined chain of who edited what and when. Not to mention some sort of method for knowing when something was modified and by who. A novel concept, but not one I think we’ll find anytime soon.


I love to read stuff like this. I wonder if Nick pays for the action that happens. This is what really has doctors scared. Nick saved a visit, but the doctor missed out on the revenue that visit would have generated. It’s also why we need to start reimbursing doctors for online visits.

NBA Implements Cerner EHR – NFL Implements eCW

Posted on December 17, 2012 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 15 blogs containing almost 6000 articles with John having written over 3000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 13 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

Over the past couple weeks, a number of major athletic organizations have announced that they’re standardizing their healthcare documentation using EHR software. The NBA is using Cerner’s EHR and the NFL is using eCW’s EHR.

At first blush these announcements remind me of Walmart selling eCW at Sam’s Club and Costco selling Allscripts EHR. Everyone wondered why Costco and Sam’s Club were selling EHR. The obvious answer was that it was a great PR move by eCW and Allscripts. Although, I did hear about one doctor that hijacked an EHR selection process thanks to a Costco mailing. I think that’s the exception.

While big popular sports organizations like the NBA and eCW might be great PR for a company, it is really interesting to consider the unique healthcare needs of a sports league. The first thing that came to my mind was actually whether the teams would want to have their athletes’ health data on one platform. Often, the health of their players is part of their strategic advantage. Certainly there are a lot more rules about disclosure of injuries, but teams still play the injury card before games, in trades, and when signing new players. I imagine the staff doctors for the teams have to be careful how and what they document in the EHR if it’s going to be available to other teams. And we thought privacy was an issue in general EHR use. It’s much more complicated when you have millions of dollars riding on a player.

From a big data perspective, I’m interested to see if either of these leagues will be able to leverage the EHR data they collect in order to deal with the long term health issues of players. This is particularly true in the physically brutal NFL. I’m sure readers are familiar with the long term concussion questions and research that’s happening with the NFL. Not to mention the ongoing battle against the use of steroids and other performance enhancing drugs. Can a unified EHR help to provide a basis for research and understanding of the health consequences of playing in the NFL?

When I start to think about all the medical devices that are coming out, they’re really interesting in an NFL context as well. Imagine all the health data from various devices being sucked into the league’s EHR. When I talked with FitLinxx at the mHealth Summit, they said that the Boston Red Sox used their activity tracking device the year they won the World Series (Seems like Boston might want to consider using it again). From what they described, The Pebble (their activity tracking device) was a great way for the trainer to keep track of compliance with the fitness regiment they suggested. Should this data be in the league’s EHR? I can see health reasons to do so, but it does go back to the question of teams’ competitive advantages.

I bet device makers would love to compare professional athlete’s use of their devices against all of the other data that’s being collected by regular users. Would make for some pretty compelling charts if I could compare my health indicators against Lebron James or Peyton Manning.

What’s also interesting to consider about a major sports league using an EHR is a connected PHR. In these situations you want your players to be well connected to the doctor and you have a real financial interest in their compliance with doctors orders. PHR in this case could make a lot of sense. Although, I wonder if many prima donna athletes would balk at the idea. Well, at least they can have their agent or assistan log in for them.

I do wonder what special features Cerner and eCW were asked to do for the NFL and NBA. Of course, not much of it would likely be useful for the rest of us.

Personalized Medicine – Processing Millions of Health Data Points

Posted on July 19, 2012 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 15 blogs containing almost 6000 articles with John having written over 3000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 13 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

“When you go to the doctor’s office and they do a blood test, they typically measure no more than 20 things. With the technology out there now, we feel you should be able to measure thousands if not tens of thousands if not ultimately millions of things. That would be a much clearer picture of what’s going on.”

This quote comes from a fascinating article by Jon Cohen called, “Examining his own Body, Stanford Geneticist Stops Diabetes in Its Tracks.” The idea is simple, but extremely powerful. I think it also paints a clear future for healthcare.

Michael Snyder is right that we need to have tens of thousands and ultimate millions of data points to be able to really effectively treat the human body. When I start to think about this, it actually makes me proud that the medical profession can treat a patient as well as it does with such limited information. Yet, it also gives me great optimism that the best advances in healthcare are still ahead of us.

As I’ve mentioned multiple times before, I believe that the body of medical knowledge will become too complex for the human mind to process on its own. In fact, we might already be there today. When you add in thousands and eventually millions of additional data points, then no one could even start to question this idea.

How then will we be able to process all these data points? Despite the human minds amazing characteristics, it will have to be assisted by technology. The human mind won’t likely be taken out of the equation, but computing power will assist the human mind to make much better decisions.

One problem with this idea is that the EHR software of today aren’t designed to handle this type of processing. EHR software is the database of healthcare and some might say that’s even a stretch. Does that mean that we’re going to have to deploy a new wave of software and technology to support this type of smart healthcare data processing?

Memory Based Health Care to Information Based Health Care

Posted on April 19, 2012 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 15 blogs containing almost 6000 articles with John having written over 3000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 13 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

The incomparable Vince Kuraitis sent out a tweet a while back that I think is worth highlighting. It was actually a retweet of @Cerner_Network who seems to be quoting L Kolkman, Mosaica Partners, so I’ll give credit where credit is due. Here’s the core of what the tweet said:

From Memory Based Care to Information Based Care

I also love that the tweet included the hashtag #freethedata.

Vince has been a long proponent of the idea of freeing the data. Although, I think the idea of moving from memory based care to information based care is a much bigger deal than just freeing the data. Sure, freeing the data will be an important part of being able to provide information based care. In fact, it’s really quite necessary to provide proper health care.

The thing about this transition is that whether healthcare data is “free” and interoperable doesn’t really deny the fact that doctors are being inundated with more and more data every day.

Back in May of 2009 I wrote this post titled, “Body of Medical Knowledge Too Complex for the Human Mind.” If this was true in 2009, imagine how much worse it is today.

Even if we don’t take into account the wave of information that is and will be coming from those apps, devices, and quantified self-ers (which I assure you is coming. Even if we don’t consider all the data that doctors will be able to get from various HIE sources (which is also coming). Just within a physician’s own EHR software and the body of medical knowledge that’s being published each and every day, the physician’s memory is at its limit.

This isn’t a knock on doctors by any means. I was stunned when my wife went to her OB/GYN after not seeing her for a few years she was able to recount the most important salient points of my wife’s child birth history. This was all without the chart (which they’d filed away in permanent storage for some reason and didn’t have it available for the appointment).

Yep, many physicians are extraordinary people with extraordinary memories, but we all have our limits. Computers have their limits as well. We’ll never be without doctors and that’s a good thing. However, we’re slowly seeing the move to where a doctor really can’t be the best doctor without some technical assistance dealing with the overload of information. I think that’s a good thing.

Quantified Self Is the Future

Posted on October 20, 2011 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 15 blogs containing almost 6000 articles with John having written over 3000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 13 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

I know I’ve mentioned the quantified self a few times in the past. Basically quantified self is that we’re all going to start finding methods, apps, sensors, etc that will collect data about our bodies. I have never been more certain of this movement than I have been talking to the people at the Connected Health Symposium in Boston. It’s going to take a few years for all of the technologies to develop, but it’s going to happen.

A simple example of this is a startup company I met called Ubiqi Health. They have a migraine tracker that helps people to track their migraines and identify their cause. Plus, this is just their first integration. I think it’s really smart for them to work on migraines first. Lots of people have migraines and very few people have a problem admitting that they have a headache (or migraine). For some reason it’s socially acceptable to say you have a headache, but not so much to say you’re depressed for example.

One thing that’s also become clear is that it’s not just going to be devices that work to “quantify” someone. It’s going to be a great mix of devices, but also is going to have to include the narrative that a person provides. The interesting thing is that from the narrative you can often capture events that might have influenced the “disease” and also can explain the quantitative data.

This is going to be really interesting to watch. I’m still thinking about how all of this data is going to affect the doctors and how they treat patients. Either way, it’s going to transform the way we deal with “health care.”