Sustaining Innovations and Disruptive Technologies: Implications

SUSTAINING INNOVATIONS AND DISRUPTIVE TECHNOLOGIES: IMPLICATIONS

FOR MOBILE HEALTH (MHEALTH) CARE PLATFORMS

Jerry Mitchell Robinson

APPROVED BY SUPERVISORY COMMITTEE:

______Anne Balsamo, Chair

______Frank Dufour

______Todd Fechter

Jerry Mitchell Robinson

Thanks also to Dr. Frank Dufour for his leadership, wisdom, and incredible patience. Thank you,

Dr. M. Phillips, for amazing expertise in the art of the dissertation and for being my patient sounding board and encouraging coach. SUSTAINING INNOVATIONS AND DISRUPTIVE TECHNOLOGIES: IMPLICATIONS

FOR MOBILE HEALTH (mHEALTH) CARE PLATFORMS

JERRY MITCHELL ROBINSON, BS, MA

DISSERTATION

Presented to the Faculty of

The University of Texas at Dallas

in Partial Fulfillment

of the Requirements

for the Degree of

DOCTOR OF PHILOSOPHY IN

ARTS, TECHNOLOGY, AND EMERGING COMMUNICATION

THE UNIVERSITY OF TEXAS AT DALLAS

December 2017 ACKNOWLEDGMENTS

Thanks to my committee members: Todd Fechter, Dr. Midori Kitagawa, Dr. Anne Balsamo, and

Dr. Frank Dufour for your support, inspiration, and guidance.

August 2017

v SUSTAINING INNOVATIONS AND DISRUPTIVE TECHNOLOGIES: IMPLICATIONS

FOR MOBILE HEALTH (mHEALTH) CARE PLATFORMS

Jerry Mitchell Robinson, PhD The University of Texas at Dallas, 2017

ABSTRACT

Supervising Professor: Anne Balsamo, PhD

mHealth technology is at the dawn of its effect on humanity and global health. Just as the cell phone rapidly morphed from a sustaining local innovation to a global disruptive innovation, mHealth technology and ecosystems will rapidly morph and expand beyond their original scope.

This paper proposes a limited, predictive analytic method approach to consider mHealth elements. Based on deconstructionist theories of Foucault, affordance theories of Gibson, forecasting theories of Tetlock, and a simple Fermi Estimation prediction model, a simple predictive model for comparing mHealth elements in an IoT wireless ecosystem is presented.

The necessity for frictionally more cost-effective health care solutions is one that mHealth technology can effectively address. Improved forecast methodology assists in selecting the

“most right” mHealth specific methods and technologies to develop and pursue.

vi TABLE OF CONTENTS

ACKNOWLEDGMENTS …...………………………………………………………….....…… v

ABSTRACT ……………………………………………………………………………………. vi

LIST OF FIGURES ……………………………………………………………………………. ix

LIST OF TABLES ……………………………………………………………………………... x

CHAPTER 1 INTRODUCTION: SUSTAINED INNOVATION AND THE IMPLICATION FOR DISRUPTIVE INNOVATION IN mHEALTH CARE DELIVERY ...... 1

CHAPTER 2 DEFINING THE NEED FOR DISRUPTION INNOVATION WITHIN THE HEALTH CARE INDUSTRY ...... 9

CHAPTER 3 A FRAMEWORK FOR EXAMINING AND PREDICTING DISRUPTIVE INNOVATION IN HEALTH CARE DELIVERY ...... 25 Profit 29

Cash 30

Ubiquity of Mobile Networks 31

Global Need for Healthcare Provision 32

Infrastructure of the Mobile Communications Ecosystem 33

End User Practices 34

Rising Health Care Costs 35

US Legislation at Both State and Federal Levels 36

Global Translational Alliances 38

Infrastructure of the Health Care Industry 39

Finance, Funding, and Capital Trends 40

Rate of Growth for Smartphone Applications 43

vii Recent Smartphone Growth from Top Vendors 45

Recent Smartphone Operating System (OS) Growth 46

Recent Smartphone Apps Growth 47

New Smartphone Linked Device Growth 51

Rate of Growth for mHealth Applications 52

Evaluation of Affordances 54

CHAPTER 4 KALMAN VALUATION FOR A COMPOSITE ANALYIS IN mHEALTH FORECASTING ...... 57 A Retrospective on Early Wireless Affordances 58

Accuracy of Experts: Understanding the Importance of Forecasting 62

Device-Level Forecasting within the Mobile Communications Ecosystem: The Automated

External Defibrillator (AED) Example 68

Forecasting Overall mHealth Growth in the Mobile Communications Ecosystem 70

CHAPTER 5 PREDICTIVE MODELS FOR TECHNOLOGICAL GROWTH: IMPLICATIONS FOR FURTHER RESEARCH ...... 76

BIBLIOGRAPHY ...... 85

BIOGRAPHICAL SKETCH ...... 97

CURRICULUM VITAE ...... 98

viii LIST OF FIGURES

Figure 1. Mobile cellular subscriptions (per 100 people). Source: 2016 ITU ...... 19

Figure 2. Smartphone Ecosystem Organization ...... 44

ix LIST OF TABLES

Table 1. Top Global Pharma and Device Makers with offshore Cash ...... 41

Table 2. Current Top Five Smartphone Vendors and Y-Y Growth – April 2017 ...... 46

Table 3. Smartphone Ecosystem Operating Systems and Market Share 2017 ...... 47

Table 4. Apple iOS App Store Sales and Downloads Through June of 2015 ...... 48

Table 5. Google Play App Sales by Date to 2016 ...... 50

Table 6. Evaluation of Affordances Upon mHealth Applications and Devices ...... 55

Table 7. Formula for Calculation of Affordances Upon the Mobile Communications Ecosystem for mHealth Applications and Devices ...... 71

Table 8. Rationale for Binary Values for Each Affordance ...... 73

Table 9. Rationale for Static Values for Each Affordance ...... 73

Table 10. Rationale for Static Temporal Values for Each Affordance ...... 74

x CHAPTER 1

INTRODUCTION: SUSTAINED INNOVATION AND THE IMPLICATION FOR

DISRUPTIVE INNOVATION IN mHEALTH CARE DELIVERY

The breakthrough innovations come when the tension is greatest and the resources are most limited. That's when people are actually a lot more open to rethinking the fundamental way they do business. Clayton Christensen

This chapter discusses how disruptive technology evolves in opposition to sustaining

innovation and the implications of this phenomenon for solving the global challenge of health

care delivery. A key thread of this study is an appraisal of how a sustaining innovation, the mobile telephone, morphed into a globally-disruptive innovation that was not anticipated, even by acknowledged industry experts.1

We recently passed the cell phone's 43rd anniversary milestone. With almost 7 billion

active cell phone subscriptions,2 most of the planet’s 7.4 billion people3 have access to mobile

communications technology. Profound, sweeping political and economic changes have resulted

worldwide from the impact of low cost/low frictional use of wireless communications.

1 Clayton M. Christensen, The Innovator's Dilemma: The Revolutionary Book That Will Change the Way You Do Business (New York: Collins Business Essentials, 2005). 2 Brahima Sanou, “The World in 2014: ICT Facts Figures” (International Telecommunication Union, April 2014). 3 “2014 World Population Data Sheet - 2014-World-Population-Data-Sheet_eng.Pdf,” n.d., 3, accessed October 29, 2014, http://www.prb.org/pdf14/2014-world-population-data-sheet_eng.pdf.

1 While at Motorola, Dr. Martin Cooper4 made the first cellphone call on April 3, 1973.

Cooper led a Motorola development team in inventing the practical cell phone. He is the primary invention patent holder5 and widely considered6 to be the "father of the cell phone."

Interestingly, Cooper credits the 1960's TV show Star Trek (1966-1969) as important inspiration for the cell phone invention.7 Motorola offered commercial cell phones to the market beginning

in late 1983;8 it wasn’t until 1996 that it was able to deliver a production-ready, consumer-

focused clamshell mobile phone.9 The clamshell look, weight, and feel of Motorola’s 1996

StarTAC phone emulated Star Trek's Communicator.

In the early 1980s, pre-breakup of telecommunications giant AT&T,10 a ten-million-

dollar study was commissioned to predict the projected growth of cell phone subscriptions

through the year 2000. McKinsey11 and Company was tasked with conducting the study.

McKinsey's early 1980’s report predicted a total worldwide cell phone subscription market of

4 “Martin Cooper (Inventor),” Wikipedia, the Free Encyclopedia, October 27, 2014, accessed October 27, 2014, en.wikipedia.org/w/index.php?title=Martin_Cooper_(inventor)&oldid=631328568. 5 M. Cooper et al., “Radio Telephone System,” US3906166 A (September 16, 1975): 21. 6 “Brain Scan: Father of the Cell Phone | The Economist,” n.d., accessed October 30, 2014, http://www.economist.com/node/13725793?story_id=13725793. 7 “How William Shatner Changed the World - Martin Cooper, Mobile Phone Inventor - YouTube,” accessed October 30, 2014, www.youtube.com/watch?feature=player_embedded&v=wN- _VA5HFwM. 8 “Motorola StarTAC - Wikipedia, the Free Encyclopedia,” accessed October 30, 2014, en.wikipedia.org/wiki/Motorola_StarTAC. 9 Ibid. 10 Angel Lozano, “The Hall of Innovation,” The Hall of Innovation, accessed October 30, 2014, www.dtic.upf.edu/~alozano/innovation/. 11 Ibid.

2 960,000 by the year 2000.12 However, by the actual year 2000, there were more than

109,000,000 active mobile subscriptions.13 The experts’ prediction was low by a factor of over

108. What happened? Why was this expert study prediction so wrong?14 McKinsey’s purported

inaccurate, expert predictions matter today and can offer up important lessons that can be applied

to the development of highly useful, potentially-global disruptive advancements in mobile health

(mHealth) technology.

Mobile health (mHealth) is defined as the practice of medicine and public health as

supported by mobile devices.15 Given that wireless communications have reduced the frictional

cost of communications and changed humanity’s interrelations, this early story in the life of cell

phones is a valuable lesson in understanding how missed opportunities can occur and how to

avoid them, particularly if we extrapolate that story to the importance of delivering health care, a

trenchant global challenge.

By 1983 Motorola had begun developing and marketing cell phones for commercial use.

Multiple companies had become focused on making products and providing services for this new

type of communication.16 There had been experience with commercial mobile automotive

wireless communications since 1946,17 so it was logical that an expectation of how people would

12 Ibid. 13 Vinod Khosla, “The Innovators Ecosystem,” (12/1/2011): 14. 14 Philip E Tetlock, Expert Political Judgment: How Good Is It? How Can We Know? (Princeton, N.J.; Woodstock, UK: Princeton University Press, 2006). 15 Robert S. H Istepanian, Swamy Laxminarayan, and Constantinos S Pattichis, M-Health Emerging Mobile Health Systems (New York, NY: Springer, 2006). 16 “Brain Scan: Father of the Cell Phone | The Economist.” 17 “Mobile Telephone History Farley_2005_TelenorPage_022-034.Pdf,” n.d.

3 use this new medium and the corresponding market size could be made. Any particular

estimation or prediction was bound to be inexact—but industry experience could deal with

predictive deviations by even a high percentage. Nevertheless, what happened after the first cell

phone call in 1973 the subsequent cell phone and extraordinary subscription growth rate was

well beyond anyone’s prediction or expectation. The exponential growth of the mobile

communications industry shows how a disruptive innovation can alter all bounds of possible

expectation or anticipation. This phenomenon within the industry continues to this day and is

still fueled by invention, innovation, and financial engineering.

The introduction of wireless communications and the industry’s expansion is more than a

story of engaging technology or profitable business success. Indeed, global wireless

communications have become a major event in the story of human history. It has, in fact, altered

our interactivity with others and with tech platforms in ways few people, even industry insiders,

could predict 40 years ago, let alone since the turn of the 21st century. There is a growing

awareness that we would be wise to “get ahead of” technology to contain its power and better

plan its uses. This is especially true in arenas in which population growth, financial strain, and

human need are colliding, as in the health care sector.

Christensen differentiates new technologies as either sustaining or disruptive, to offer an

approach for understanding the trajectory and rate of expansion within a business model, or

ecosystem.18 Mobile communication usage has evolved in a dynamic, chaotic fashion, expanding

18 Clayton M. Christensen, The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail (1st Edition), 1st ed. (Boston, MA: Harvard Business School Press, 1997), xv.

exponentially as devices, platforms and applications are introduced.19 At the same time,

according to Christenson, most innovations are sustaining in nature, providing a profitable and

marketable commodity for companies upon which to anchor a business model. They may be,

according to the author, incremental, discontinuous, or radical in character. In fact, sustaining

innovations “improve the performance of established products, along the dimensions of

performance that mainstream customers in major markets have historically valued.20” However, on occasion disruptive technologies, those that threaten the stability of mainstream products and services, emerge and result in worsening near-term product performance. As a consequence, disruptive technologies “bring to market a very different value proposition than had been available previously…Generally, disruptive technologies underperform established products in mainstream markets. But they have other features that a few fringe (and generally new) customers value.” Within the health care industry as a whole, the value proposition of mHealth care devices and platforms is poised to unsettle existing business models.

Since McKinsey’s inaccurate predictions in the early 1980s, personal cell phone usage has emerged as a disruptive innovation, meaning that it is not just a tool of communication. It is a phenomenon that has, with each new inventive application, expanded both by industry insiders and outsiders, overturned market sectors, profoundly and permanently altered human interactivity, and caused a redirection of research and development of the cell phone as a delivery platform with seemingly endless potential. The term disruptive innovation is central to

19 Vinod Khosla, “The Innovator’s Ecosystem” (Khoslaventures, December 1, 2011), www.khoslaventures.com/wp-content/uploads/The-Innovator’s-Ecosystem.pdf. 20 Christensen, The Innovator’s Dilemma, xv.

the present study because it helps to account for the trajectory and speed with which a sustained innovation, in this case, the mobile telephone, did become a social and industry catalyst. If we fail to be accurate in our current assessment of its value, then we can miss other potentially explosive growth areas that can have even greater impact on human well-being, as in

development of mHealth platforms.

Christensen observes that disruptive technologies are often cheaper, smaller, simpler, and

frequently more convenient to use. As with all innovation, the development of a disruptive turn upon a sustaining product hinges upon consumer need and usage practices. Bill Gates also observes the same process21 and emphasizes time value of action. For a disruptive innovation

example, Amazon’s introduction of its website purchasing “Buy Button” simplified consumers’

buying practices; likewise, replacement of the cell phone key pad for data entry into graphical

touch screens eased usage of a device in ways that end users found faster and more convenient.

Each had a lower frictional cost than its predecessor as well, and, importantly, further inspired

invention and enabled new applications to arise. In each case, the platform already existed but

the new technology, with very little resistance and fueled by consumer need, rapidly took the

business model in new directions.

This framework for the phenomenon of disruptive innovation could provide an

opportunity to address the critical shortage of health care delivery, particularly if predictions

about the growth of mHealth innovation can be better understood. Refocusing industry

development in this area could, in fact, offer a means to reduce crippling consumer costs, unpack

21 Bill Gates, Business @ the Speed of Thought: Succeeding in the Digital Economy, 1st ed. (New York, NY: Grand Central Publishing, 1999).

industry entrenchment, and provide access to care, all of which present a barrier to human health.

Instead of focusing on profit from applications with far less value to overall human need, mHealth invention could revolutionize the practice of medicine and, as importantly, improve an individuals’ awareness of responsibility for good health. Deliberately pursuing disruptive technology within the health care industry could also free up products and services that consumers value and need most. Furthermore, a lowering of wireless communications ecosystem frictional cost promotes more rapid mHealth adoption. An immediate effort toward broader understanding by key stakeholders within the health care industry of existing relational patterns between the tech industry and health care provision would leverage the lesson contained in the

McKinsey reports’ misjudgment about patterns and rates of growth for technology. To examine this idea in the context of mHealth technology, that is, the use of smartphones as a platform for solutions to seemingly intractable problems, this study seeks to answer the following research questions:

 What would the future of the tech industry’s contribution to solving the problem

of health care delivery be if it were self-reflective enough to learn from its

historical trends?

 What forces impede both the prediction and industry development of smartphone

adaptation to solve the health care delivery crisis?

 What perceptual tools can be used to evaluate the current market and development

trends to better predict how mobile health technology (mHealth) might roll out in

effective ways that could impact global health and do so with greater predictive

accuracy?

This study examines concomitant stories within the phenomenon of disruptive innovation as a method to better forecast the potential of mobile health technology. The health industry’s multiple, related and turbulent interactions between need and solution form a dynamic ecosystem from which to predict the efficacy, expansion, and implementation of mHealth applications.

CHAPTER 2

DEFINING THE NEED FOR DISRUPTION INNOVATION WITHIN THE HEALTH

CARE INDUSTRY

An explanation of the context in which this study examines innovation potential within

mHealth platforms is necessary, particularly because mobile health technology today is on the

cusp of a tremendous growth boom, similar in nature to the early cell phone story. It is important

to get these predictions right given the reduced access to care stemming from entrenchment in the health insurance sector. With a significant portion of the US economy vested in solving health care concerns cheaply, broadly, and effectively, it is important for both business stakeholders and health care consumers to be able to understand its early growth and potential value. Some of the lessons gleaned from the AT&T-McKinsey report story provide insight into revolutionary changes that mobile health technology promises. To do so, I propose refining prediction and forecasting methods for development of applications in the mHealth arena in light of obvious human need, as I further explain in Chapter 3.

The dynamic ecosystem of the wireless communications industry means that change can occur rapidly, as we have seen recently, for example, in the popularity of IoT (Internet of things) products like Amazon Alexa, among many other popular consumer applications. Human-tech interrelatedness applications are currently an explosive area of business development and growth. In 1999, Kevin Ashton22 stated, “if we had computers that knew everything there was to

22 Kevin Maney, “Meet Kevin Ashton, Father of the Internet of Things,” Newsweek, last modified February 23, 2015, accessed August 3, 2017, http://www.newsweek.com/2015/03/06/meet-kevin-ashton- father-internet-things-308763.html.

know about things—using data they gathered without any help from us—we would be able to

track and count everything and greatly reduce waste, loss, and cost.” Kevin Ashton was co- founder and executive director of the Auto-ID Center at MIT. He is also widely considered the father of IoT. Within a few years, IoT is forecast23 to generate $19 trillion in profits. Now nearly

20 years after Ashton’s revelation, worldwide physical device logistics distribution channels

have become extremely efficient and can deploy both devices and physical system infrastructures

with lightning speed. Furthermore, existing economic subscriber channels have been overlaid to

include connections to banking and commerce services. Software applications and content are

also accessible in multiple formats and, as translation technologies improve, even language

barriers impeding use are also melting away. Currently, with more cell phones and subscriptions

in place than there are people on the planet, the potential to revolutionize health care for the

world’s population is within range—if we exploit parallel historical developments. New

supporting technologies, such as Cloud-based Big Data technology, IoT technology, IoMT

(Internet of Medical Technology) and an increasing number of targeted applications serve to

enable powerful mobile health technology.

In short, the development of mHealth innovations has the potential to be an important

medical force multiplier. In the US, many studies have focused on the need to improve home and

traditional health care. There is at present a historic opportunity to apply wireless

communications technology to deliver mHealth solutions in novel and disruptively innovative

ways. While some may argue that IoMT and its related applications cannot replace the

23 Bruce Sinclair, IoT Inc.: How Your Company Can Use the Internet of Things to Win in the Outcome Economy: How Your Company Can Use the Internet of Things to Win in the Outcome Economy, 1st ed. (McGraw-Hill Education, 2017).

relationship between doctor and patient, it can shorten the distance between them in vitally

important ways. Consider, for example, that a physicians' ear is not replaced by the stethoscope,

rather it is supplemented. So too, an electronic heart monitor does not replace the stethoscope but

enhances its use. Through the use of innovative applications, that same information could be

made available 24 hours a day, seven days a week with a mHealth wireless monitor and cloud

linked data analysis. An early example of this technology is the Fitbit Alta HR Fitness Tracker.24

Detected unusual conditions could provide an alarm and alert health care providers. Here, a mHealth device serves to multiply the availability and effectiveness of medical providers. Just as there isn’t only one problem, there isn’t just one solution, medical system, geographic region, or method to consider.

Traditional methods of health care provision do not need replacement; they need expanded availability and ease of use by both physicians and patients. If both are supported by new, more effective, more economical and innovative mHealth solutions, then overall consumer health could improve and industry logjams could become a thing of the past. As importantly, predicting and planning for this kind of industry disruption would demonstrate wisdom of forethought applied in the Technological Era.

In March of 2017, the governmental Centers for Medicare and Medicaid Services (CMS) published a healthcare fact summary.25 According to a CMS, health care currently makes up

24 “Fitbit Alta HR Fitness Tracker with Heart Rate Monitor, Sleep Monitoring, Exercise Tracking, and Communications Link,” accessed May 4, 2017, https://www.fitbit.com/altahr. 25 Centers for Centers for Medicare, Medicaid Services 7500 Security Boulevard Baltimore, and Md21244 Usa, “NHE-Fact-Sheet,” last modified December 2, 2016, accessed March 18, 2017, https://www.cms.gov/research-statistics-data-and-systems/statistics-trends-and- reports/nationalhealthexpenddata/nhe-fact-sheet.html.

17.8% of the US Gross Domestic Product (GDP). Of this number, Medicare consists of 4.5% and

Medicaid makes up 9.7%. Between 2015 and 2025, the CMS forecasts that health spending is

projected to grow at a yearly average rate of 5.8%. Healthcare is expected to make up or exceed

20.1% of the GDP by 2025. Prescription drugs costs are increasing at an even faster percentage.

According to CBS News and Segal Consulting,26 prescription drug cost increases for those under

age 65 were 11.3% in 2016 and is forecast to be 11.6% in 2017. For those over 65 and

participating in government medical programs, prescription drug prices rose 10.9% in 2016 and

are forecast to rise 9.9% in 2017. Contrast these cost increases to a forecast 2017 US average

wage increase of 2.5%. The Social Security 2017 Cost of Living27 increase was just 0.3%. Those who earn wages and those receiving government medical support are losing economic ground.

With an impending Republican intention to repeal the Affordable Care Act28 (ACA), the

Congressional Budget Office estimated that there would be three major rising cost effects.

First, 18 million people would lose their health insurance in the first year and could become

uninsured. Later, after subsidy elimination, that number could increase to 32 million by 2026.

Second, insurance premium costs would rise 20 to 25 percent, relative to current projections.

Premium costs would also rise 50 percent by 2026. Third, there would be a strong, as yet

26 Aimee Picchi, “Drug Prices Will Rise 12 Percent in 2017, Faster than Wages - CBS News,” CBS Money Watch: Prognosis for Rx in 2017: More Painful Drug-Price Hikes, last modified December 30, 2016, accessed March 18, 2017, http://www.cbsnews.com/news/drug-prices-to-rise-12-percent-in- 2017/. 27 “Social Security Administration: National Average Wage Index,” accessed April 3, 2017, https://www.ssa.gov/oact/cola/AWI.html. 28 “How Repealing Portions of the Affordable Care Act Would Affect Health Insurance Coverage and Premiums | Congressional Budget Office,” accessed March 18, 2017, https://www.cbo.gov/publication/52371.

unknown response from governmental institutions and those providing care. Given the cost

increases encountered in the years since the Affordable Care Act was set in place, many people

consider the ACA’s effect to be more insurance reform than patient medical coverage. If

proposed ACA repeal becomes law, ACA’s limited provisions could become moot.

Mobile health (mHealth) technologies may provide an immediate force multiplier in

areas that are severely underserved. mHealth delivery methods can provide information and

training in a fashion that people all over the globe are coming to expect. For example, USAID, a

US controversial government entity that provides global civilian crisis relief, has begun using

YouTube video/audio methods for domestic and international medical and health training.29 In times of epidemic or disaster, virtually an entire country can quickly get information and appropriate training via wireless communications. Most populated areas, even in rural Africa, are covered by cell phone services. In second- and third-world countries, wireless technologies are already having a profound force multiplier impact. For example, in parts of Africa online mobile banking and commerce have motivated people to quickly learn and adopt new technology, expanding financial opportunities for even the smallest business owners.

One aspect of health care that has encountered minimal resistance from medical professionals and financial parties in applications of mHealth technology is in assisted living care. Traditional living spaces can benefit from a host of nonintrusive, mobile health

29 USAID, “Training, Economic Empowerment, Assistive Technologies and Medical Rehabilitation (TEAM) | Fact Sheet | Asia Regional | U.S. Agency for International Development,” accessed April 3, 2017, https://www.usaid.gov/asia-regional/fact-sheets/training-economic- empowerment-assistive-technologies-medical-rehabilitation.

technologies, too.30 Amazon’s home gateway Alexa has a growing community of medically challenged users and organizations using it to better cope with life. Web MD,31 Boston

Children’s Hospital,32 and numerous others are leading the rush to legitimize mHealth diagnosis

and support.33 In fact, Amazon has a $100M venture fund34 to promote Alexa “skills”

development, applications designed to address consumers’ daily interactive needs and interests.

As the US baby boomer generation ages, more and more individuals will find a need for

medical support technologies. The World Bank reports that 1 in 6 Europeans and North

Americans are over 65 years old,35 while two-thirds of the Sub-Saharan African population is

under age 25. Declining abilities, inadequate medical infrastructure, and epidemic needs may

require assistance not immediately available through traditional venues.

In one analysis, it was estimated that if technology can assist each person to stay out of a

nursing home or assisted care facility for only a single additional year, the net effect would save

society approximately $300 billion. Patient Quality of Life would be boosted by avoiding or

30 Hoang Nhu, “Smart Home Platform with Data Analytics for Monitoring and Related Methods” (February 16, 2016). 31 Lee Bell, “Amazon Alexa Can Now Be Your Doctor,” accessed March 20, 2017, https://www.forbes.com/sites/leebelltech/2017/03/11/alexa-whats-wrong-with-me-amazons-virtual- assistant-could-replace-your-doctor/#3290de9f5721. 32 “Boston Children’s Hospital Launches KidsMD, an App for Amazon’s Alexa,” MobiHealthNews, last modified April 12, 2016, accessed April 3, 2017, http://www.mobihealthnews.com/content/boston-childrens-hospital-launches-kidsmd-app-amazons-alexa. 33 Bell, “Amazon Alexa Can Now Be Your Doctor.” 34 “The Alexa Fund: VC Funding to Fuel Voice Technology Innovation,” accessed August 3, 2017, https://developer.amazon.com/alexa-fund. 35 World Bank.org Health, Nutrition & Population Data Portal

delaying the need for nursing home or assisted care. Garcia and Rodrigues detail36 this

environment in Ambient Assisted Living. Outside of the US, the medically assisted case support

ecosystem is vastly smaller. A dramatic increase in international research and the number of

international conferences have focused on how to deploy mHealth treatment tools.37 mHealth applications often need ancillary devices beyond a cell phone. Dishongh and McGrath delve into suitable wireless medical sensors38 in Wireless Sensor Networks for Healthcare Applications.

The authors’ work establishes how sensor data capture and cloud-based processing enable

mHealth platforms to provide care support.

The global population exceeds 7.4 billion and is rising.39 Some of the highest birth rates

are in resource-challenged countries. Increased need in a region of stressed supplies creates a

potential dire shortage of basic necessities for the most vulnerable individuals. In the US, the

number of trained medical care providers among millennials is predicted to be far outweighed by

aged baby boomers, further aggravating the problem.

Nevertheless, dire circumstances have faced the world’s population before, and numerous

examples exist to reveal how disruptive technology presented by brilliant inventors solved

deeply troubling challenges. For example, in the late 1800’s, as the world population was soaring

36 Nuno M. Garcia and Joel Jose P. C. Rodrigues, eds., Ambient Assisted Living, 1st ed. (Boca Raton, FL: CRC Press, 2015). 37 Jose Bravo, Ramón Hervás, and Marcela Rodriguez, eds., Ambient Assisted Living and Home Care: 4th International Workshop, IWAAL 2012, Vitoria-Gasteiz, Spain, December 3-5, 2012, Proceedings, 2012th ed. (Berlin ; New York: Springer, 2012). 38 Terrance J Dishongh and Michael McGrath, Wireless Sensor Networks for Healthcare Applications (Boston: Artech House, 2009). 39 “World Population Clock: 7.5 Billion (UN Projection -2017) - Worldometers,” accessed March 30, 2017, http://www.worldometers.info/world-population/.

above a billion people, it became apparent that there would be a global food shortage in the

foreseeable future.40 Easily obtainable supplies of natural agricultural fertilizer were running out.

Wars had been fought over natural fertilizer shortage in 1800’s South America,41 and global mass starvation was predicted to occur within a generation. To combat the end of inexpensive and easily obtainable fertilizer, Fritz Haber and Carl Bosch42 invented a new technological way

to make fertilizer from nitrogen in the air. This creative solution used city size factories to create

massive amounts of fertilizer and demonstrates the intersection between established industry

methods, immediate human need and the importance of disruptively innovative advancements.

Perhaps 40% of all people alive in 2017 are dependent on artificial fertilizer.43 Billions of people

today might not have food if not for the creative technological genius of these two chemists.

Another example of technology being used to address a crucial problem facing humanity

is the story of peak oil and fracking. Through the end of the 20th century, oil experts predicted

the end44 of cheap and easily recoverable oil. The probability of widespread global conflict and

turmoil was rising. Some analyst predicted that billions of people could perish in such conflicts.

40 James K. Laylin, ed., Nobel Laureates in Chemistry, 1901-1992 (Washington, D.C.: Chemical Heritage Foundation, 1993). 41 William F. Sater, Andean Tragedy: Fighting the War of the Pacific, 1879-1884 (Lincoln: University of Nebraska Press, 2007). 42 Thomas Hager, The Alchemy of Air: A Jewish Genius, a Doomed Tycoon, and the Scientific Discovery That Fed the World but Fueled the Rise of Hitler (New York: Three Rivers Press, 2008). 43 Murray Park, The Fertilizer Industry, 1st ed. (Cambridge, England; Place of publication not identified: Woodhead Publishing, 2001), 2. 44 Ian Chapman, “The End of Peak Oil? Why This Topic Is Still Relevant despite Recent Denials,” Energy Policy 64 (2014): 93–101.

Military planners actively gamed and studied these scenarios. Meanwhile, George Mitchell45 had long persisted in developing oil and natural gas fracking46 technology. His efforts were wildly

successful. Fracking changed the world landscape47 of oil production, natural gas production,

politics, and pricing. By several estimates, Mitchell’s fracking innovation indirectly saved

hundreds of millions of dollars and countless human lives.

Though the US has only 4.6% of the world’s population, it is near the forefront of early

mHealth adoption. Medicines, devices, practices, procedures, and applications that are successful

in the US are often rapidly accepted and deployed worldwide.

However, poverty and lack of infrastructure leave most people in the world without the

means or access to medical care,48 and the cost and availability of medical care can be difficult to surmount. It is increasingly true that most of the world’s population has access to mobile phone technology. For example, at a short-term cell phone annual growth rate of 65%, the continent of

Africa is considered the fastest growing cell phone market globally, even surpassing the Asian market.49 At the same time, the World Health Organization-Africa states that among the 17 goals

in the United Nations’ Sustainable Development Goals (SDGs) plan for delivery by the year

45 “George P. Mitchell,” Wikipedia, the Free Encyclopedia, February 12, 2016, accessed May 20, 2016, en.wikipedia.org/w/index.php?title=George_P._Mitchell&oldid=704610618. 46 “George Mitchell, Father of Fracking,” The New York Times - The Lives They Lived, December 21, 2013, accessed May 20, 2016, www.nytimes.com/news/the-lives-they-lived/2013/12/21/george- mitchell/. 47 Russell Gold, The Boom: How Fracking Ignited the American Energy Revolution and Changed the World, 1st ed. (New York: Simon & Schuster, 2014). 48 Roger Thurow and Scott Kilman, Enough: Why the World’s Poorest Starve in an Age of Plenty, Reprint. (New York: PublicAffairs, 2009). 49 African Business Pages “The Market for Mobile Phones in Africa.” http://www.africa- business.com/features/mobile_phones_africa.html

2030, “Almost all …are directly related to health or will contribute to health indirectly.”50 In

2013, WHO’s regional director for Africa, Dr. Luis Sambo, stated

“At least one million new health workers are urgently needed in the African Region to ensure that qualified health workers are available in the right places to deliver quality health services. In addition to this, countries in the Region are grappling with weak education and training capacity, insufficient financial resources, lack of comprehensive data on health workers and information for decision making, among others.”51

The irony is that developing nations are seeing faster growth in the rate of mobile communication subscribers than they are an increase in health care providers. The International

Telecommunication Union (ITU) states that “The next billion mobile subscribers will consist mainly of the rural poor.”52 Recognizing the role of market competition and the need for

communications access across the world, ITU also states that in the last ten years

“…new financing and technology, along with privatization and market liberalization, have spurred dramatic growth in telecommunications in many countries. With the rapid development of mobile telephony and the global expansion of the Internet, information and communication technologies are increasingly recognized as essential tools of development, contributing to global integration and enhancing public sector effectiveness, efficiency, and transparency.”

50 WHO Africa. “Sustainable Development Goals” http://www.afro.who.int/health- topics/sustainable-development-goals 51 WHO Africa. “4th Regional Consultation on Health Workforce”. http://www.afro.who.int/health-topics/health-workforce 52 World Bank.org “Mobile Cellular Subscriptions” International Telecommunication Union, World Telecommunication/ICT Development Report and database. http://data.worldbank.org/indicator/IT.CEL.SETS?end=2015&start=1960

Figure 1. Global Mobile cellular subscriptions (per 100 people). Source: 2016 ITU53 It is, therefore, logical to leverage mobile communication applications and devices to support and deliver health care solutions. The potential for free, or nearly free, mHealth applications that could address the needs of the world’s population is of enormous importance and rests upon forward thinking within the mobile communication ecosystem, the global medical care infrastructure, financial stakeholders and translational partners.

In western countries, the health care financial sector further complicates health care provision through corporate policies that favor profitability over patient health. Costs have been driven up by expertly crafted, well-funded economic and legal machines. Collection companies, credit reporting agencies, a lack of cost transparency, murky pricing, and limited payer negotiations have contributed to a complex pricing system. Select corporate 10K reports, fund

53 “ICT Facts and Figures 2016,” ITU, accessed July 26, 2017, http://www.itu.int:80/en/ITU- D/Statistics/Pages/facts/default.aspx.

prospectus, and court records show how well-oiled billing and collections processes are being play tested in Nebraska, Missouri, Michigan, and Pennsylvania.54

Not all medical providers engage in predatory billing and collection practices, but some

do. Fraud also drives up costs and is a frequent medical billing problem. Furthermore, fully 62%

of all US bankruptcies are a result of unpaid medical costs according to a study published in the

American Journal of Medicine in 2009 and cited ubiquitously in debates about the ACA. The

report details that the bankruptcy rate was high despite the fact that most filers had health

insurance.55 Furthermore,

“Most medical debtors were well educated, owned homes, and had middle-class occupations. Three-quarters had health insurance. Using identical definitions in 2001 and 2007, the share of bankruptcies attributable to medical problems rose by 49.6%. In logistic regression analysis controlling for demographic factors, the odds that a bankruptcy had a medical cause was 2.38-fold higher in 2007 than in 2001.”

Clearly, the cost of health care is prohibitive and leaves many Americans choosing to avoid health care preventive altogether.

There are many examples of Hedge Fund Medical and Pharma organizations. One example of Hedge Fund Pharma practice is Gilead Sciences,56 manufacturer of a patented

Hepatitis C (HCV) treatment drug. HCV is a declared epidemic. Gilead’s HCV treatment is

considered 90% successful and has little to no medical side effects. Gilead had over $25.2

54 Paul Kiel, “For Nebraska’s Poor, Get Sick and Get Sued,” ProPublica, last modified April 28, 2016, accessed May 2, 2016, https://www.propublica.org/article/for-nebraskas-poor-get-sick-and-get- sued. 55 American Journal of Medicine, “Medical Bankruptcy in the United States, 2007: Results of a National Study.” Aug 2009; Vol 122:8, 741-746, accessed July 17, 2017. http://www.amjmed.com/article/S0002-9343(09)00404-5/fulltext 56 “Gilead Sciences, Inc.,” accessed August 1, 2017, http://www.gilead.com/.

Billion in cash assets57 at the end of 2015. It is true that R&D in the US is expensive, so in 2016,

Gilead announced a $3 Billion stock repurchase plan. Even though its flagship drug was

developed partially with US Veterans Administration funds, the drug patent ownership has been

moved offshore. Gilead analysts Avik Roy and Steve Miller58 have observed that with large

amounts of on-hand cash, virtually no opposition to relatively high pricing, little R&D cost, and

an effective offshore tax strategy, “Gilead cannot effectively justify its high patient pricing.”

The strategy of Hedge Fund Pharma is to maximize shareholder value. Such enterprises seek to

maximize revenue from every possible source, by all possible methods. As Wong and Cohen

observed, one of Gilead’s pricing methods is to maintain high prices, so that a substantial

number of HCV patients cannot afford59 the medication. Rita Rubin observed that in one

Congressional study, 97.6% of HCV Medicaid patients were denied60 effective HCV treatment.

Some patients may have government assisted access to HCV medications later in the drug’s

progression. This approach ensures that a substantial number of new people will catch HCV and

likely generate future revenue. It is an effective revenue bolstering strategy. Simple math says

that Gilead Sciences has enough cash, currently on hand, to immediately purchase sufficient

57 “Gilead Sciences 10-K Form 2014,” accessed May 20, 2016, www.sec.gov/Archives/edgar/data/882095/000088209515000008/a2014form10-k.htm. 58 Avik Roy and Dr. Steve Miller, M.D., “The Sovaldi Tax: Gilead Can’t Justify The Price It’s Asking For Hepatitis C Therapy - Forbes,” last modified June 17, 2014, accessed July 13, 2015, www.forbes.com/sites/theapothecary/2014/06/17/the-sovaldi-tax-gilead-cant-justify-the-price-its-asking- americans-to-pay/. 59 John B Wong and Joshua T Cohen, “Cost-Effective but Bad for Health? Hepatitis C Treatment, Moral Hazard and Opportunity Cost” (2017). 60 Rita Rubin, “Hepatitis C Drugs Top State Medicaid Pharmaceutical Expenditures,” JAMA 315, no. 549 (February 9, 2016).

licensed generic61 HCV treatment drugs from India to treat 100% of American HCV sufferers.

Here are Gilead’s numbers:

 $25.2 Billion in cash available at the end of 2015.  ~ 7 million HCV patients in the US.  Estimated HCV manufacturing cost ~$60.  A fully licensed, generic course of HCV treatment medication from India is currently retail priced at $462, including shipping, ($4.62 per pill) for one person.

The company has enough cash on hand to buy at least 7.8 times as much generic retail priced HCV medication as would be needed to treat every HCV patient in America. Hill and

Cooke further estimate62 that the US manufacturing price for a full 12-week treatment can be

brought down to $78 to $166, based on HIV drug cost reduction experience. By keeping costs

high, instead of curing HCV, Brian Edlin estimates that those who are least be able to afford treatment may be stuck with the disease63 for many years. This same disease risk group may also

be the ones most likely to spread the contagion to other people. High treatment cost ensures a

steady supply of potential new patients for Gilead and keeps the revenue stream up.

mHeatlh technology can help address this serious problem by providing web-based disease education, locating blood test clinics, locating experienced HCV knowledgeable physicians (either in person or via telemed systems), helping patients to become aware of effective international treatment options, helping to find low-cost licensed sources for medication, setting up tax-deductible patient-centric medication funding scheme, and more. With

61 Muhammad Umar et al., “ROLE OF GENERICS IN TREATMENT OF HEPATITIS C INFECTION,” Journal of Ayub Medical College Abbottabad 28, no. 4 Sup (2017): 890–894. 62 Andrew Hill and Graham Cooke, “Hepatitis C Can Be Cured Globally, but at What Cost? | Science” 345, no. 6193 (July 11, 2014): po. 141-142. 63 Brian R Edlin, “Access to Treatment for Hepatitis C Virus Infection: Time to Put Patients First,” The Lancet Infectious Diseases 16, no. 9 (2016): e196–e201.

an average US income64 (2015 estimate from the Social Security Administration) of $48,098 per

year, there must be a better way than Gilead’s choice: pay $89,000 for the course of treatment or

do without.

With potential Affordable Care Act repeal or alteration, dramatically rising traditional

costs increasingly open the field for novel, cost reducing mHealth approaches. One creative

solution is proposed by Dr. Bryan Hill and others in the health care industry like him who do

place the well-being of their patients above profit.65 Hill addresses the affordability problem with

a monthly subscription-based medical practice that does not take medical insurance. His

membership model covers most of what the average patient needs. It includes visits, lower priced

drugs, and relies on a business model similar to a cell phone subscription. Hill’s technique is

scalable, and this is one example of a fast-growing movement among pediatricians, family

medicine physicians, internists, and diagnostics groups. When combined with often inexpensive

catastrophic medical insurance,66 a dramatically improved medical outcome experience is

possible even with limited patient resources. If one adds in the innovation of mHealth care

devices and applications, then the financial cost of health care delivery in the US could

dramatically diminish. This is a similar effect as to what was demonstrated in how the recorded

music industry lost vast market share as a result of independent artist creation release. By use of

64 “Social Security Administration: National Average Wage Index.” 65 Lydia Ramsey, “Direct Primary Care, a No-Insurance Healthcare Model - Business Insider,” accessed March 20, 2017, http://www.businessinsider.com/direct-primary-care-a-no-insurance- healthcare-model-2017-3. 66 Rob Bryan, “Out-of-Pocket Healthcare Payments Are Skyrocketing - Business Insider,” accessed March 20, 2017, http://www.businessinsider.com/out-of-pocket-healthcare-payments- skyrocketing-2016-9.

web-based platforms, such as YouTube and Facebook, the fricitional cost of sales and delivery was reduced. At the same time, aritst revenue per creation increased. A similar process is at work in the way that traditional television networks are losing ground to digital on-demand entertainment, such as is offered by Netflix, Hulu, Amazon, and others. Other industries are finding new means of delivering what consumers want - in the way they want - tailored to their context.

Chapter 3 returns to a discussion of how the development of mHealth care within the mobile communications ecosystem is a site in which market forces could be examined using predictive models.

CHAPTER 3

A FRAMEWORK FOR EXAMINING AND PREDICTING DISRUPTIVE INNOVATION

IN HEALTH CARE DELIVERY

While the analytical approaches described in this chapter may seem disparate, they are combined to leverage lessons that may be gleaned from the failure of early industry predictions

and the tech industry’s current and generally-accepted practice of retroactively contributing

technological solutions to address a human product and services development need. Further, the

more accurate a prediction or forecast is, the more frictionally cost effective that good, service,

or application will become. The more advantageous, lower frictional cost solution can spell the

difference between a given effort’s success or failure. With the size, scope, and dynamic nature

of mHealth and cellphone ecosystems, this inaccuracy can result in a massive lost investment

(think billions of dollars) and unmet medical needs (think many lives lost or damaged). The

discussion here is primarily intended to avoid missed health care provision and business

opportunities that would address consumer need through radical new directions within the

existing mobile communications ecosystem.

We can contrast early mobile communications technology predictions to the currently

rich potential of mHealth care adaptation from multiple perspectives. Given the established need

for both affordable and accessible global health care delivery and the global and increasing

ubiquity of mobile communication subscribers, the question becomes whether or not the industry

is inclined to lean forward enough to leverage lessons from its own comparatively young history.

To begin, Foucault’s67 method for deconstruction of historical systems of control provides a useful starting point for examining the likelihood of the industry’s adaptation to

broad-based and accepted mHealth care delivery. Instead of using Lovejoy’s History of Ideas

approach for a top-down study, as outlined in The Great Chain of Being: A Study of the History

of an Idea,68 an analysis of the mobile communications ecosystem against disruptively

innovative new practices benefits from a deconstruction of its constitutive parts. The

deconstructionist approach offered by Foucault lends itself well to breaking down a complex

device, application, or analysis into ecosystem-related streams, or more properly affordances, as

Gibson69 would emphasize. The underlying theory is supported by Lorenz,70 Lao-Tzu,71 and

Gibson. Gibson presented his Ecological Approach to Visual Perception72 and his Theory of

Affordances as an abstract metaphorical way to handle complex topics, relationships, and story.

These abstractions, for this analysis, are referred to as affordances, or information and

influence streams, a proposed reimagining of the mobile communications ecosystem as a

dynamic, complex system into which multiple and varied forces continuously enter and exit. To

evaluate the temporal merit of each stream, and to evaluate relative merit between streams, I

67 Michel Foucault, The Archaeology of Knowledge, trans. A. M. Sheridan Smith (New York: Pantheon, 1972). 68 Arthur O. Lovejoy, The Great Chain of Being: A Study of the History of an Idea, 1st ed. (Harvard University Press, 1936). 69 Harry Heft, Ecological Psychology in Context: James Gibson, Roger Barker, and the Legacy of William James’s Radical Empiricism (Psychology Press, 2015). 70 LORENZ Edward, “Predictability: Does the Flap of a Butterfly’s Wings in Brazil Set Off a Tornado in Texas?,” American Association for the Advancement of Science, Washington, DC (1972). 71 Lao Tzu and Red Pine, Lao-Tzu’s Taoteching, 3rd Revised. (Copper Canyon Press, 2012). 72 James J Gibson, The Ecological Approach to Visual Perception: Classic Edition (Psychology Press, 2014).

posit that statistical measurements can bring about a relative prediction or forecast about the

likelihood of mHealth platform adaptation within the mobile communications ecosystem and the

health care industry.

Shark73 multiple sensory systems are straightforward to understand, monitor, and study

and they provide a brief but useful analogy. Sharks have eight distinct, unique senses:74 hearing,

smell, lateral line, pit organs, vision, Lorenzini, touch, and taste. At any given point of time, not

all shark sensorial information streams have equal weight. By using electronics and telemetry to monitor individual sensorial information streams, we can obtain a great deal of insight into forecasting potential shark future actions, and by extrapolation forecast an outcome of the myriad forces at play regarding mHealth care’s potential within the industry.

We also need a way to weigh dynamic streams comparatively. Studying the shark again helps provide insight on weighing mechanisms. Since not all shark sensorial streams are of equal importance at a specific given time, a Kalman Filter75 style approach may be used to evaluate

and weigh different sensor stream’s relative importance. For example, if a threat is two miles

away, then the relative weight of that threat may be low. If the threat is very close, then the

relative weight of the threat may be high. Different sensor streams are of varied relative

importance in making the threat decision.

73 Thomas B. Allen, The Shark Almanac: A Complete Look at a Magnificent and Misunderstood Creature, 1st edition. (New York, N.Y: The Lyons Press, 1999). 74 “NEFSC Fish FAQ,” accessed March 16, 2017, http://www.nefsc.noaa.gov/faq/fishfaq8.html. 75 Mohinder S Grewal, Kalman Filtering (Springer, 2011).

Kalman filtering76 is a type of statistical analysis that works well to evaluate information

in a single sensorial stream. Multiple streams can be compared and evaluated in the same

fashion. Multiple needs can also evaluate information streams in different fashions, depending on

the requirement. Kalman filtering of information streams is a useful tool to tool for prediction

and forecasting. One practical example of this process is the prediction of shark migratory

decision-making.77 Another example is the use of Kalman filtering in the decision-making

process of robots.78 These scientific methods have practical use in the prediction of market and other forces at play in the future of mHealth care’s innovative disruption of existing health care and mobile communications practices. To make a value decision, the variety of influential and informational streams need to be weighed, parsed, and evaluated. Kalman filtering allows a more efficient reconstitution of the whole or more accurate forecasting and prediction.79

Since a shark could choose to either bite a passing scuba diver or swim away, its future

action must be based on a current situation. Here the Markov Process80 in which prediction of a

future process is solely based on a present state, becomes useful. If a current state is going to

change to a future state in a quantum system, then that is a forecast. Affecters in what that future

76 Paul Zarchan and Howard Musoff, Fundamentals of Kalman Filtering a Practical Approach, ed. Frank Lu (Reston, Va.: American Institute of Aeronautics and Astronautics, 2009). 77 Shara Marie Teter et al., “Migratory Patterns and Habitat Use of Sand Tiger Sharks (Carcharias Taurus) in the Northwest Atlantic” (2011). 78 B Allotta et al., “An Unscented Kalman Filter Based Navigation Algorithm for Autonomous Underwater Vehicles,” Mechatronics 39 (2016): 185–195. 79 Philip E. Tetlock and Dan Gardner, Superforecasting: The Art and Science of Prediction (New York: Crown, 2015). 80 A. T. Bharucha-Reid, Elements of the Theory of Markov Processes and Their Applications (Mineola, N.Y: Dover Publications, 2010).

state may be can consist of statistical modifiers.81 This is where the decision-influencing output

of the Kalman Filter comes into play. The Markov Chain is a stochastic process with the Markov

property. The Markov Chain82 is a very useful concept for understanding change within a

quantum system, where the next state may be predictable. For data compression, financial

mathematics, chemical reactions, and a host of other applications, Markov Chain concepts are

extremely useful to describe dynamic events such as those in the mHealth care question.

The following streams of influence and information will be used in this study:

Profit

Since the rise of the health care professions and industry that surrounds them, health care

has been regarded as a balance between cost and benefit. In recent years, the cost of healthcare

has greatly outstripped an average worker’s income. The US Social Security Administration

reports an average worker annual income increase (AWI)83 of 2.685% from 2005 to 2015. The

Kaiser Foundation reports that health care costs, by contrast, rose84 4.965% annually in this

period. Clearly, health care is becoming less affordable. With additional expenses associated

with insurance, collections, credit derating, legal fees and more, the average annual cost increase

81 Yunfei Xu et al., Bayesian Prediction and Adaptive Sampling Algorithms for Mobile Sensor Networks: Online Environmental Field Reconstruction in Space and Time, 1st ed. 2016 edition. (Springer, 2015). 82 Nicolas Privault, Understanding Markov Chains: Examples and Applications, 2013 edition. (Singapore: Springer, 2013). 83 “Social Security Administration: National Average Wage Index.” 84 “Health Spending Explorer,” Peterson-Kaiser Health System Tracker, n.d., accessed July 19, 2017, http://www.healthsystemtracker.org/interactive/.

is even more. Classic economic income elasticity of demand theory85 provides a way to compare

price variation and alternate solutions for similar outcomes.

For organizational models whose objective is to maximize shareholder value or income,

it is unlikely that they will modify the behavior that has made them successful in favor of better

patient outcomes. Gilead, for example, went through 14 years of losses before achieving a

winning economic strategy. Shareholders and investors will not support a strategy that will

greatly reduce or eliminate HCV when it means that the stock value, available cash parked

offshore, or reduced future earnings will result. Motley Fool labeled86 Gilead Sciences the

“World’s Most Perfect Stock” for these reasons. Profit or similar funding is the source spring for

developing new solutions, thus setting up a possible disruptive solution scenario.

Cash

Cash is the liquidity underlying a dynamic economic system. How that cash is obtained,

how it is managed, the geolocation it is parked in, and accessibility are all critical items in

healthcare innovation. Cash parked offshore, may be more difficult to access and rely on for

future R&D or development. It can serve to eliminate onshore technological ecosystems or

business incubators. Available economic resources are one-third of any effective project, as Fred

85 Sheila Smith, Joseph P Newhouse, and Mark S Freeland, “Income, Insurance, and Technology: Why Does Health Spending Outpace Economic Growth?,” Health Affairs 28, no. 5 (2009): 1276–1284. 86 Sean Williams, “6 Reasons Gilead Sciences Could Be the World’s Most Perfect Stock -,” The Motley Fool, last modified 13:02, accessed July 19, 2017, https://www.fool.com/investing/2017/04/03/6- reasons-gilead-sciences-could-be-the-worlds-most.aspx.

Brooks observed87 in The Mythical Man Month. Access to cash, or financial resources, is an important part of any analysis.

Cash held off-shore,88 such as the 98.6% of Johnson and Johnson’s $41.9 Billion stash, the 43.8% of Medtronic’s $13.7 Billion, or the 86.1% of Gilead Science’s $34.0 Billion can make it easier for small companies and efforts to compete in the medical device and application ecosystem. Factoring in cash for a new venture is critical to that venture’s success.

Ubiquity of Mobile Networks

With the increasing sophistication of mobile phones and the dropping price (frictional cost) of connection, one can reach almost anyone else in the world. Mobile communications ubiquity extends commerce, banking,89 healthcare benefits,90 and educational awareness to

almost everyone on earth. Culturally, the technological effects will not change all people over

night,91 but as Martin Cooper observed:92 “Culture is the most important thing.”

Ubiquity is “the fact of appearing everywhere or being very common.” For wireless

communications, this can physically mean such things cell phone capability, cell network

87 Frederick P Brooks, The Mythical Man-Month: Essays on Software Engineering, 2nd ed. (Reading, MA: Addison-Wesley, 1995). 88 “The 50 Largest Stashes of Cash Companies Keep Overseas,” accessed July 19, 2017, https://www.bloomberg.com/graphics/2017-overseas-profits/. 89 Hsiu-Fen Lin, “An Empirical Investigation of Mobile Banking Adoption: The Effect of Innovation Attributes and Knowledge-Based Trust,” International journal of information management 31, no. 3 (2011): 252–260. 90 Darrell West, “How Mobile Devices Are Transforming Healthcare,” Issues in technology innovation 18, no. 1 (2012): 1–11. 91 Gerard Goggin, Cell Phone Culture: Mobile Technology in Everyday Life, New Ed edition. (London ; New York: Routledge, 2006). 92 “How William Shatner Changed the World - Martin Cooper, Mobile Phone Inventor - YouTube.”

communications nature and bandwidth, billing, translational aspects, and more. For example, in

much of the world, this may mean technical LTE2 communications standards compliance. For

AT&T in the US, LTE2 is no longer supported. Range and data rate aspects also are implicated.

Modern smart phones are agile concerning communication standards, operating bands, and some

range aspects. Older cell phones may not be as flexible. For example, in India, many $2 cell

phones are sold. Though often designed in the US, these low-cost devices may not be compatible

or flexible with some devices or apps. Similarly, there may be far more sophisticated LTE

systems and phones available outside of the US than inside. It is important to evaluate and track

the compliance type, network type, UI-translational aspect, and more.

Global Need for Healthcare Provision

The healthcare world is not limited to the population of the US. With 4.6% of the world

population, the US enjoys some advantages as a developer and an early adopter market.

Applications and education tools are not limited by geographical bounds, however. Purchase of

mHealth devices and products may lag applications purchases, in much of the world.

Where doctors may be limited in number and location, for example in the Ivory Coast,

telehealth applications play a crucial role in early detection and treatment93 of those who may

contract a serious disease. The paper’s author worked just such a project at BD Diagnostics. The

US Army has also extensively tested telemedicine systems and techniques in Croatia,94 Somalia,

93 Victoria Garshnek and Frederick M Burkle Jr, “Applications of Telemedicine and Telecommunications to Disaster Medicine: Historical and Future Perspectives,” Journal of the American Medical Informatics Association 6, no. 1 (1999): 26–37. 94 MAJ JB CROWTHER and LTC RON POROPATICH, “Telemedicine in the US Army: Case Reports from Somalia and Croatia,” Telemedicine Journal 1, no. 1 (1995): 73–80.

Southwest Asia,95 and more. The US Army approach extensively relies on medics and first

responders.96 Information stream evaluations must consider cross border97 medical and support

aspects of telemedicine.98 As the concept of a medic or first responder status becomes more

extended to traditional health care providers, techniques, and medical services, mHealth can

force multiply traditional medical practice to a larger percentage of the world’s population.99

Infrastructure of the Mobile Communications Ecosystem

With cell phone and wireless service increasingly available to the vast majority of

humanity, the ecosystem of devices and applications are still on a disruptively innovative track

upward. Oncoming technological device technology is somewhat predictable in that it may take

years for development and worldwide systems deployment. The ecosystem must also stay

compliant, for the most part, with older generation devices and applications. That said, there are

major technological improvements on the near horizon.

Fifth generation100 (5G) wireless technology is soon to be deployed. Historically, data rate communications were 30KHz for 1G, 200KHz for 2G, 5MHz for 3G, and 20-450+MHz for

95 Col Ronald K Poropatich et al., “The US Army Telemedicine Program: General Overview and Current Status in Southwest Asia,” Telemedicine Journal & e-Health 12, no. 4 (2006): 396–408. 96 CROWTHER and POROPATICH, “Telemedicine in the US Army: Case Reports from Somalia and Croatia.” 97 Vanessa Saliba et al., “Telemedicine across Borders: A Systematic Review of Factors That Hinder or Support Implementation,” International journal of medical informatics 81, no. 12 (2012): 793– 809. 98 Nathan Cortez, “Patient without Borders: The Emerging Global Market for Patients and the Evolution of Modern Health Care,” Ind. LJ 83 (2008): 71. 99 Lama Jarudi, “Doctors without Borders,” Harvard International Review 22, no. 1 (2000): 36. 100 Federico Boccardi et al., “Five Disruptive Technology Directions for 5G,” IEEE Communications Magazine 52, no. 2 (2014): 74–80.

4G. 5G communications extend this data rate to 1GHz for multiple devices in local space.

Bluetooth (and BLE) 5 protocols increase the data rate, extend the range from 1-3 meters to 30-

100 meters, and support dramatically more linked devices accessible on a single device.

Bluetooth/BLE 4 links to 5-9 local devices and Bluetooth /BLE 5 will link to 128-256 local devices. BT5 operating power is dramatically reduced, and BT5 devices will play well in an IoT space. In the IoT space, the number of devices may expand rapidly to 50 billion – on to an installed base of 100’s of billions. Additional, 5G devices will have dramatically increased WiFi performance in terms of data rate, the ability to operate in a mesh, route WiFi information, and communicate with multiple WiFi devices at the same time. For example, one small remote village could have a single cell phone or satellite phone – yet able to link to hundreds if not thousands of other cell phones in a village wide mesh topology. Such a mesh dramatically extends the reach of wireless communications technology. How well a device or application plays with the communications ecosystem is critical to evaluate and track. With the current installed base of cell phone physically moving “upscale” on a worldwide basis, these issues are important.

End User Practices

End user practice is directly related to User Interface101 (UI) design. The one click “Buy

Button” approach used by Amazon102 is a good example. Once set up, a customer only has to click one screen button to purchase an item and have it shipped. Given that a substantial amount

101 Everett N. McKay, UI Is Communication: How to Design Intuitive, User Centered Interfaces by Focusing on Effective Communication, 1st ed. (Morgan Kaufmann, 2013). 102 Melanie Wells, “In Search of the Buy Button,” Forbes 172, no. 4 (2003): 62–70.

of work is needed for traditional103 online purchases, this makes the potential merging advantage

of telemedicine and the ordering of services or prescriptions a tremendously potent concept.

User Interface design is a critical track to evaluate by comparison with other ecosystem

similar goods or services transactionals. A thorough comparison of the Apple Computer apps

ecosystem techniques as championed by Chief Apple Designer Jonathan Ive104 is an approach to

use in comparisons.

Rising Health Care Costs

Rising costs force patients to make increasingly critical decisions on health care. Rising insurance cost105 and deductibles for those have classic insurance106 may result in reduced

coverage or more exposure to already high pharma prices. For those retired or under US

Government coverage, pharma price increases of often 9 – 10% a year are often unsustainable,

especially when inflation adjusted (COLA) pension and retirement checks increase107 by only

0.3%.

103 Deborah L Bayles and Hamir Bhatia, E-Commerce Logistics & Fulfillment: Delivering the Goods (Prentice Hall PTR, 2000). 104 “22 Things You Need To Know About Apple’s Jonathan Ive,” accessed July 19, 2017, https://www.fastcodesign.com/3042524/22-things-you-need-to-know-about-apples-jony-ive. 105 Juliette Cubanski, “The Facts on Medicare Spending and Financing,” The Henry J. Kaiser Family Foundation, July 18, 2017, accessed July 19, 2017, http://www.kff.org/medicare/issue-brief/the-facts-on-medicare- spending-and-financing/. 106 Wells, “In Search of the Buy Button.” 107 “Cost-of-Living Adjustment (COLA) Information,” accessed March 18, 2017, https://www.ssa.gov/news/cola/.

Evaluation of cost choice is one area where mHealth devices and applications have

outstanding potential. Insurance companies108 want cost reduction and comparison by mHealth

applications. Companies such as GoodRx109 collect massive amounts of pharma price

information and present local pricing information to a patient via their application. A recent

experience by the author illustrates the comparison potential. At Walmart, a prescribed

medication was quoted at $99. The pharmacist would not permit printing the “free” GoodRx

coupon out, so the author drove home and printed out the free “prescription card.” After returning to Walmart, the medication was repriced to $33. At a different pharmacy, it was rated at $25.74. With a $10 monthly GoodRx card subscription, the rated price would have been $19.

These comparison techniques can be applied to a host of medical applications and costs. In a

second example, a $185,000 hospital stay could have been rerated to $15,000 with a mHealth

comparison application. Patient outcome information may also be tracked, and those considering

a hospital procedure can intelligently plan a medical procedure. In the track analysis, GoodRx is

an excellent model for operational comparison and implementation difficulty.

US Legislation at Both State and Federal Levels

Just a few years ago, this paper’s author could not get an email from his doctor because there was no way for the doctor to get reimbursed via insurance or from the government. With a government rule change, this situation was resolved by the insurance company. It is therefore critical for any mHealth device or application to be compliant with State and Federal regulations

108 “Cost Estimator | UnitedHealthcare,” accessed July 19, 2017, https://www.uhc.com/individual- and-family/member-resources/health-care-tools/cost-estimator. 109 “About GoodRx,” last modified 2016, accessed April 17, 2016, http://www.goodrx.com/about.

and policies. That is the core requirement behind insurance or other reimbursement coverage.

Compliance and information consistency are an analysis track for every mHealth device. That standard may also include FDA,110 CE,111 or other compliance testing. Devices and Apps should

also be federal data standards compliant and compatible. A mHealth device or application must

meet requirements for each legal jurisdiction in which it is sold. This is one advantageous reason

that devices or applications should be targeted to cell phone and wireless communication

ecologies.

State compliance evaluation is important. For example, Telemedicine112 before the

advent of the smartphone could not foresee all of the usage changes that these devices would

make. Concepts such as telemedicine have the potential to bring113 disruptive changes to

medicine, yet have had a difficult time complying with state approvals and state medical board

acceptance. After great initial resistance, Texas has taken the lead in US state approval114 of

telemedicine and opened the door to a host of associated medical devices and applications.

Employers such as Walmart can now legally make telemedicine consultation available for free to

110 “Guidance, Compliance, & Regulatory Information,” WebContent, accessed July 19, 2017, https://www.fda.gov/drugs/guidancecomplianceregulatoryinformation/. 111 “European CE Marking Strategy for Medical Devices,” Emergo, last modified November 10, 2011, accessed July 19, 2017, https://www.emergogroup.com/services/europe/ce-certification. 112 Adam William Darkins and Margaret Ann Cary, Telemedicine and Telehealth: Principles, Policies, Performance, and Pitfalls (New York: Springer Pub. Co., 2000). 113 “How Telemedicine Disrupts Health Care,” Christensen Institute, May 5, 2015, accessed July 19, 2017, https://www.christenseninstitute.org/blog/how-telemedicine-disrupts-health-care/. 114 “Cheaper, Faster Health Care? Teladoc, Telemedicine Finally Have Open Path in Texas | Health Care,” Dallas News, last modified June 1, 2017, accessed July 19, 2017, https://www.dallasnews.com/business/health-care/2017/06/01/cheaper-faster-health-care-teladoc- telemedicine-finally-open-path-texas.

its 1.2 million employees and support pharmacy linked apps for employees. Compliance tracking

and evaluation for State and Federal rules are important to consider.

Global Translational Alliances

Global conglomerate corporations are increasingly the standard. For the healthcare industry, there are providers and ecosystems with special expertise and a special impact. The boundaries between innovator, distributor, inventor, and customer relationship manager have also blurred. Amazon, Apple, Samsung, Alibaba, Walmart, and traditional telecoms all have had to evolve to be more general in relationship than just a good purchasing outlet. Amazon, in particular, has expanded to be a creative outlet for its customers, an international supplier of goods, services, apps, entertainment, and communications.

The ecosystem that allows mHealth devices and apps to be sold and distributed is global in nature. A product ordered via Alibaba from Shenzhen, China can be shipped for $19 and arrive in a US destination in 2.5 days. Products ordered in the US from Amazon can often be delivered within hours. Products ordered from Banggood (Shenzhen, China) can ship to the US at no cost, even for single items costing one dollar. International currency, payment, language translation, and communications are immediate and free. In increasing areas of the world, banking and business relationships are cell phone centric for both a payments ecology and a banking ecology.115 It is no wonder that a transnational aspect is an important measurement for

any mHealth device, application, or service. Strategic relationships, such a telehealth physician

115 Vijay Mahajan, How Cell Phones and Banking Accelerate African Opportunity and Growth, 1st ed. (FT Press, 2009).

meeting being efficiently linked to a medical prescription delivery by Amazon, can be forecast to

be very important.

Infrastructure of the Health Care Industry

With over 17% of the entire US economy allocated to Health Care, it is important to note

that healthcare is not a monolithic entity. A substantial portion of the health care industry is

bound up with traditional goods and services that which are closely tied to reimbursement

systems of insurance, governmental, and traditional medical practice. Within this portion of the

ecosystem, billing and reimbursement are of primary importance. Pricing does affect choice116 and options with drug117 and medical services. Rising insurance deductibles118 on both Pharma

and traditional medical services also has an adverse effect on patient health.

There are other channels within the Health Care Industry that are not closely tied to

traditional eco-health medical financing and practices. The US Military is making telemedicine

services widely available119 to service members and their families. Military telemedicine practice

does not cover all aspects120 of patient needs, but it provides the first line of response to

116 R. Tamblyn et al., “Adverse Events Associated with Prescription Drug Cost-Sharing among Poor and Elderly Persons,” JAMA 285, no. 4 (January 24, 2001): 421–429. 117 Leigh Purvis and Stephen W. Schondelmeyer, “Rx Price Watch Report: Trends in Retail Prices of Specialty Drugs,” AARP, accessed April 21, 2016, http://www.aarp.org/health/drugs- supplements/info-08-2010/rx_price_watch.html. 118 Michael R. Law et al., “Impact of Income-Based Deductibles on Drug Use and Health Care Utilization among Older Adults,” CMAJ: Canadian Medical Association journal = journal de l’Association medicale canadienne 189, no. 19 (May 15, 2017): E690–E696. 119 “AMD Telemedicine Blog - Telemedicine Is a Huge Ally for Military Clinics,” accessed July 26, 2017, http://www.amdtelemedicine.com/blog/article/telemedicine-huge-ally-military-clinics. 120 mHealthIntelligence, “DoD Expands Telemedicine Access for Military, Families,” MHealthIntelligence, last modified February 5, 2016, accessed July 26, 2017, https://mhealthintelligence.com/news/dod-expands-telemedicine-access-for-military-families.

immediate medical needs. Traditionally, the military’s medical practices are gradually implemented in First Responder medical situations. These practices have also extended to NGO medical and clinical efforts.

One example of this transference effort is at the Center for Military Medicine Research, the University of Pittsburgh.121 Executive Director Poropatich wants to bring these proven effective telemedicine techniques and systems to US Veterans. These techniques and systems have been tested worldwide and are finding extension to the rest of the world by NGOs and other medical care organizations.

Finance, Funding, and Capital Trends

The largest medical entities find it difficult to fund and manage small disruptive development. Frequently, this is due to a strategy that seeks to minimize all cost and maximize shareholder value. Many times, this results in moving cash resources offshore in a variety of fashions. The table below shows 25 of the top Global Pharma companies with offshore cash.

Offshore cash percentages are shown for a select few companies. Four other select, highly profitable, medical device makers are added at the bottom of the list. Since new development and innovation must be funded from current profits or borrowed from future resources, it is logically apparent why R&D funding is more difficult for a larger, offshore cash strategy company. The very core elements that Christensen122 mentions for startup of a disruptive innovation idea are

121 “Center for Military Medicine Research | University of Pittsburgh,” accessed July 26, 2017, http://www.cmmr.pitt.edu/. 122 Clayton M Christensen, The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail, Reprint. (Harvard Business Review Press, 2013).

therefore among the most difficult for a larger, cash oriented company to pursue. These difficulties create an opportunity space for small startups and ideas to thrive.

Table 1. Top Global Pharma and Device Makers with offshore Cash

2014 2013 Overseas % of Rank Growth Growth Company Sales Sales Cash all # ($m) % ($m) ($m) ($Billion) Cash 1 Novartis 47101 47468 ‐367 ‐1.0% 2 Pfizer 45708 47878 ‐2170 ‐5.0% 3 Roche 39120 39163 ‐43 0.0% 4 Sanofi 36437 37124 ‐687 ‐2.0% 5 Merck & Co. 36042 37437 ‐1395 ‐4.0% 6 Johnson & Johnson 32313 28125 4188 15.0% 41.3 98.6% 7 GlaxoSmithKline 29580 33330 ‐3750 ‐11.0% 8 AstraZeneca 26095 25711 384 1.0% 9 Gilead Sciences 24474 10804 13670 127.0% 29.3 86.1% 10 Takeda 20446 19158 1288 7.0% 11 AbbVie 20207 18790 1417 8.0% 12 Amgen 19327 18192 1135 6.0% 35.0 91.2% 13 Teva 18374 18308 66 0.0% 14 Lilly 17266 20962 ‐3696 ‐18.0% Bristol‐Myers 15 15879 16385 ‐506 ‐3.0% 8.4 95.5% Squibb 16 Bayer 15486 14854 632 4.0% 17 Novo Nordisk 15329 14877 452 3.0% 18 Astellas 14099 13508 591 4.0% Boehringer 19 13830 15789 ‐1959 ‐12.0% Ingelheim 20 Actavis 13062 8678 4384 51.0% 21 Otsuka 11308 11226 82 1.0% 22 Daiichi Sankyo 10430 12067 ‐1637 ‐14.0% 23 Biogen Idec 9398 6668 2730 41.0% 24 Baxter 8831 8347 484 6.0% 25 Merck KGaA 7678 8399 ‐721 ‐9.0% Medtronic 6.0 43.8% Biogen 4.3 75.4% Stryker 2.8 85.0% Celgene 6.9 77.9%

Largest Companies with Cash Overseas 2014: PMLIVE Top Pharma List123 Pharma Companies Cash Overseas: Bloomberg124

New opportunities and funding mechanisms for mHealth devices and applications125 find funding from a variety of sources. Crowdfunding126 for mHealth company start-ups, individual medical account support,127 and more enable new fund-raising methods. Crowdfunding source

Kickstarter alone has successfully funded 128,690 campaigns128 with $3,182,242,680 of funds. A small, but growing percentage of these successful campaigns are medical or health related.

Healthcare medical startup incubators129 have increased in number, size, and importance.

Typically, a startup incubator will have a well-planned growth process and resources to support

123 “Top 25 Pharma Companies by Global Sales - Top Pharma List - PMLiVE,” text, last modified March 12, 2014, accessed July 26, 2017, http://www.pmlive.com/top_pharma_list/global_revenues. 124 “These 50 Companies Have the Biggest Stockpiles of Cash Overseas,” Bloomberg.Com, n.d., 50, accessed July 26, 2017, https://www.bloomberg.com/graphics/2017-overseas-profits/. 125 Mark E Grube et al., “Health Care on Demand: Four Telehealth Priorities for 2016: Expanding Telehealth Opportunities via Email, Video, and Other Technologies Can Improve Patient Satisfaction and Convenience, While Ensuring High-Quality Care Is Delivered at Lower Costs,” Healthcare Financial Management 70, no. 1 (2016): 42–52. 126 “Top 10 Crowdfunding Sites by Traffic Rank,” accessed July 26, 2017, https://www.crowdfunding.com/. 127 “Top 6 Personal Fundraising Websites,” Crowdfunding Success Tips, October 25, 2013, accessed July 26, 2017, http://www.crowdcrux.com/top-personal-fundraising-websites/. 128 “Kickstarter Stats — Kickstarter,” accessed July 26, 2017, https://www.kickstarter.com/help/stats. 129 “12 Healthcare Startup Incubators and Accelerators to Know,” accessed July 26, 2017, http://www.beckershospitalreview.com/healthcare-information-technology/12-healthcare-startup- incubators-and-accelerators-to-know.html.

an individual or small company project. Some medical incubators focus specifically130 on mHealth devices and solutions.

Traditional Venture Capital resources are still a valuable resource for a mHealth startup, but the number of actual funded ventures is low. Venture Capital incubators provide a structured process to handle the business side of a venture and map out a low-cost strategy for growth past an initial stage. Frequently, a Venture Capital incubator will “graduate” a successful project to a more traditional funding arena.

There are also a variety of other startup and idea Launchpad approaches to pursue. Many of these alternate approaches combine both a space for an idea or project to be developed along with an education in how the business or medical device ecosystem works.

Funding is an important mHealth success affecter.

Rate of Growth for Smartphone Applications

mHealth applications and devices occupy an evolving position within the smartphone

ecosystem. The ecosystem consists of layered, mutually dependent, supporting entities. The

ecosystem is rapidly expanding in size and economic value. The ecosystem virtually demands

sustaining innovations at a rapid pace. Failure for a supplier to provide such innovation could

result in a supplier’s offerings no longer being generally accepted by consumers. There are many

examples of suppliers which fail to supply new innovations. The smartphone ecosystem is

organized in general layers. Core to this approach is that growth and failures of individual

130 “6 Healthcare Incubators Growing the Future of HealthTech,” EMR and HIPAA, October 30, 2014, accessed July 26, 2017, http://www.emrandhipaa.com/guest/2014/10/30/6-healthcare-incubators- growing-the-future-of-healthtech/.

ecosystem members will generally not ripple through and cause other members to fail

catastrophically. Here are the layers and a brief discussion.

Service Provider

Smartphone Vendor

Smartphone OS

Smartphone Applications Ecosystem

Figure 2. Smartphone Ecosystem Organization Service providers handle cell phone permitting and subscription support. They often

handle financial details. They manage cell phone tower and network linkage issues. They deal

with localized governmental and regulatory issues. They handle or administer physical tower

network linkage. Sometimes, they also provide baseline cell phone and smartphone sales and

support. They frequently implement the upgrade of communications standards within a market.

Smartphone vendors make cell phones and support localized communications standards.

Typically, they also work with all aspects of cell phone manufacturing. They work with component and software suppliers. Top smartphone vendors include Samsung, Apple, Huawei,

OPPO, Vivo, Google, Microsoft, and others.

Smartphone Operating Systems generally are core sourced as Apple iOS or Android compatible software. Apple iOS and Android both allow for a dynamic applications ecosystem which may be supported by a common applications store or authorized outlets. Other suppliers,

such as Microsoft and Blackberry exist but have experienced a declining market share. Apple

Operating System apps are generally far more restrictive than Android Operating System apps.

Smartphone applications may be software, supporting device hardware, or a combination of both. Since standard smartphone technology includes cellular communications, WiFi, and

Bluetooth communications, a host of new possibilities are possible. The fact that a consumer may easily obtain free or low-priced software applications that can then be run on a smartphone or low-cost tablet computer has made this software store approach dominant.

Smartphone sales growth and applications growth offer a historical model and may help forecast potential growth trajectory for mHealth device and applications growth.

Recent Smartphone Growth from Top Vendors

Smartphones are on a dynamically increasing sales growth trajectory. Year over year sales for smartphones increased 4.3% to 347.4 million devices, in just the first quarter of 2017. mHealth devices and applications that are compatible with these vendor smartphones can take advantage of a “rising tide lifts all boats” strategy. As new 5G standard phones arrive in the market, demand for new technology and smartphones is expected to rise. Possible price reduction of current technology may make high-performance smartphone technology available to more people. Table 2 shows 347.4 million smartphones sold just in the first quarter of 2017.

Table 2. Current Top Five Smartphone Vendors and Y-Y Growth – April 2017131

1Q17 1Q17 1Q16 1Q16 Year‐ Vendor Shipment Market Shipment Market Over‐Year Volume Share Volume Share Change 1 - Samsung 79.2 22.80% 79.2 23.8% 0.0% 2 - Apple 51.6 14.90% 51.2 15.4% 0.8% 3 - Huawei 34.2 9.80% 28.1 8.4% 21.7% 4 - OPPO 25.6 7.40% 19.7 5.9% 29.8% 5 - Vivo 18.1 5.20% 14.6 4.4% 23.6% Others 138.7 38.90% 140.0 42.1% -1.0% Total 347.4 100.00% 332.9 100.0% 4.3% Source: IDC Mobile Quarterly Phone Tracker, April 27, 2017 (Shipments in Millions of Units)

Recent Smartphone Operating System (OS) Growth

From an app developer’s economic perspective,132 the iOS App Store ($5.4 billion in Q4

2016 revenue) is more attractive than the Android Play Store ($3.3 billion revenue in the same quarter). Both stores offer 70% of revenue to the developer. The App Store also offers fewer apps compared to the Play Store and is, therefore, less competitive. These numbers do not tell the whole story, however.

Table 3 shows Android with an 85% OS market share. Android is gradually increasing its worldwide market presence over Apple iOS with 14.7% and others with only 0.2%. The Apple

131 “Worldwide Quarterly Mobile Phone Tracker - IDC,” last modified April 27, 2017, accessed July 25, 2017, http://www.idc.com/tracker/showproductinfo.jsp?prod_id=37. 132 Alexandra Vaidos, “Google Play Store vs Apple’s App Store - A Comparison,” Softpedia, accessed July 25, 2017, http://news.softpedia.com/news/google-play-store-vs-apple-s-app-store-a- comparison-512601.shtml.

iOS is highly concentrated in North America, with Android being dominant in the rest of the world.

For an apps developer, OS presence can shape the sequential strategy of goods or services offered with Geographic Location being an important consideration.

Table 3. Smartphone Ecosystem Operating Systems and Market Share 2017133 Windows Android iOS Others Quarter Phone 2016Q1 83.4% 15.4% 0.8% 0.4% 2016Q2 87.6% 11.7% 0.4% 0.3% 2016Q3 86.8% 12.5% 0.3% 0.4% 2016Q4 81.4% 18.2% 0.2% 0.2% 2017Q1 85.0% 14.7% 0.1% 0.1% Source: IDC, May 2017

Recent Smartphone Apps Growth

Insight into smartphone app growth rates can be gained from historical and recent download statistics for iOS and Android apps.

App availability is rigorously controlled in the Apple ecosystem. Apple iOS apps are distributed from the Apple App Store. Founded on July 10, 2008, the App Store has revolutionized how computer application software is sold and used. Apple apps are generally inexpensive and easy to download. Apple had built distribution ecosystems before, such as the iTunes Music Store. The App Store was different in many respects, one of which was control.

Other key differences were the easy app software development and user purchase convenience.

Apple introduced appropriate charges on top of the app cost to fund the ecosystem and have a

133 “IDC: Smartphone OS Market Share,” Www.Idc.Com, accessed May 23, 2016, www.idc.com/prodserv/smartphone-os-market-share.jsp.

stake in each app’s sale. In 2005, there were over 1.5 million apps134 available, and Apple announced that over 100 billion apps had been downloaded, as of June 8, 2015 (see Table 4).

Table 4. Apple iOS App Store Sales and Downloads Through June of 2015135

Available Downloads to Average Downloads Date apps date per app

11-Jul-08 500 0 0 14-Jul-08 800 10,000,000 12,500 9-Sep-08 3,000 100,000,000 18,334 22-Oct-08 7,500 200,000,000 26,667 16-Jan-09 15,000 500,000,000 33,334 17-Mar-09 25,000 800,000,000 32,000 23-Apr-09 35,000 1,000,000,000 28,571 8-Jun-09 50,000 1,000,000,000+ ~20,000 14-Jul-09 65,000 1,500,000,000 23,077 28-Sep-09 85,000 2,000,000,000 23,529 4-Nov-09 100,000 2,000,000,000+ ~20,000 5-Jan-10 120,000 3,000,000,000+ ~25,000 20-Mar-10 150,000+ 3,000,000,000+ ~20,000 29-Apr-10 200,000+ 4,500,000,000+ ~22,500 7-Jun-10 225,000+ 5,000,000,000+ ~22,222 1-Sep-10 250,000+ 6,500,000,000+ ~26,000 20-Oct-10 300,000+ 7,000,000,000+ ~23,334 22-Jan-11 350,000+ 10,000,000,000+ ~28,571 6-Jun-11 425,000+ 14,000,000,000+ ~32,941 7-Jul-11 425,000+ 15,000,000,000+ ~35,294 4-Oct-11 500,000+ 18,000,000,000+ ~36,000 28-Feb-12 500,000+ 24,000,000,000+ ~40,000 3-Mar-12 500,000+ 25,000,000,000+ ~50,000 11-Jun-12 650,000+ 30,000,000,000+ ~46,154

134 “App Store (IOS),” Wikipedia, the Free Encyclopedia, May 20, 2016, accessed May 23, 2016, en.wikipedia.org/w/index.php?title=App_Store_(iOS)&oldid=721178776. 135 Ibid.

12-Sep-12 700,000+ 35,000,000,000+ ~50,000 28-Jan-13 800,000+ 40,000,000,000+ 50,000 23-Apr-13 825,000+ 45,000,000,000+ 50,000 16-May-13 850,000+ 50,000,000,000+ 50,000 10-Jun-13 900,000+ 50,000,000,000+ 50,000 22-Oct-13 1,000,000+ 60,000,000,000+ 60,000 2-Jun-14 1,200,000+ 75,000,000,000+ 62,500 9-Sep-14 1,300,000+ 75,000,000,000+ 62,500 16-Jan-15 1,400,000+ 75,000,000,000+ 62,500 8-Jun-15 1,400,000+ 100,000,000,000+ 62,500

Google spearheads the Android ecosystem with an equivalent Play Store offering. Over

88 primary makers of smartphones use Android as their smartphone OS. It is no wonder that

Android is used in over 85% of the smartphones sold worldwide. The Android apps ecosystem began later than the iOS ecosystem and thus lagged behind it in many key criteria. Google Play was launched136 on March 6, 2012. It was formed by merging three older services, Android

Market, Google Music, and Google eBookstore.

As of March 2017, Android apps out-numbered137 iOS apps by 2.8 million to 2.2 million

(see Table 5). The value of apps sold on Android Play and iOS Store increased from 2015, by about 40%, to $35 billion. Other app sales channels exist, but information is not specifically vetted.

136 “Google Play,” Wikipedia, the Free Encyclopedia, May 18, 2016, accessed May 24, 2016, https://en.wikipedia.org/w/index.php?title=Google_Play&oldid=720917019. 137 “App Stores: Number of Apps in Leading App Stores 2017,” Statista, accessed July 25, 2017, https://www.statista.com/statistics/276623/number-of-apps-available-in-leading-app-stores/.

Table 5. Google Play App Sales by Date to 2016138 Year Month Applications available Downloads to date 2009 March 2,300 December 16,000 2010 March 30,000 April 38,000 August 80,000 1 billion October 100,000 2011 May 200,000 3 billion July 250,000 6 billion October 319,000 December 380,297 10 billion 2012 January 400,000 May 500,000 June 600,000 20 billion September 675,000 25 billion October 700,000 2013 February 800,000 April 850,000 40 billion May 48 billion July 1,000,000 50 billion 2014 June 1,200,000 July 1,300,000 December 1,430,000 2015 Q1 1,500,000 2016 Q1 1,900,000 82 billion

App download type information is tracked. Top Android App download numbers were in

India, with 6.2 billion downloads in 2016. Total app downloads during 2016 were up by 15%

138 “Google Play Information,” Wikipedia, July 24, 2017, accessed July 25, 2017, https://en.wikipedia.org/w/index.php?title=Google_Play&oldid=792100474.

over 2015.139 From current app growth information, one can forecast general app growth to be

approximately 10 - 20% annually or more over the course of the next few years.

New Smartphone Linked Device Growth

Smartphones have operating and performance limitations. They are not designed to be on

all the time, 24/7. They have a battery powered operating life. They are, at heart, individually

specific communications devices. By connecting to other devices, such as a WiFi Hotspot, the

smartphone ecosystem may be dramatically extended.

Functional extensions, such as Augmented Reality (AR) and Virtual Reality (VR) devices

are expected to grow from 10 million devices in 2016 to 100 million devices in 2021.140

Gateway devices, such as Amazon Echo,141 are designed to stay on all the time. Echo serves to

link via WiFi to a local computer (cell phone, WiFi Router, or WiFi link) over the internet to a

Cloud Based Server. These devices dramatically reduce the frictional cost of communication and

improve the ability of the consumer to purchase goods, services, and support everyday life

management. Alexa, Amazon’s software app, will work on a host of computing platforms. Echo

type gateway of platforms and Alexa type voice and user interfaces may dramatically change the

139 Sarah Perez, “App Downloads up 15 Percent in 2016, Revenue up 40 Percent Thanks to China,” TechCrunch, n.d., accessed July 25, 2017, http://social.techcrunch.com/2017/01/17/app- downloads-up-15-percent-in-2016-revenue-up-40-percent-thanks-to-china/. 140 “Worldwide Shipments of Augmented Reality and Virtual Reality Headsets Expected to Grow at 58% CAGR with Low-Cost Smartphone VR Devices Being Short-Term Catalyst, According to IDC,” Www.Idc.Com, accessed July 25, 2017, http://www.idc.com/getdoc.jsp?containerId=prUS42807717. 141 “Amazon Echo,” Wikipedia, July 24, 2017, accessed July 25, 2017, https://en.wikipedia.org/w/index.php?title=Amazon_Echo&oldid=792182717.

landscape of mHealth devices.142 The Amazon Echo device family has geographic limitations yet has nonetheless sold more than 12 million devices in a little more than a year.

Rate of Growth for mHealth Applications

Multiple elements affect mHealth device and application growth. It is a very dynamic,

chaotic, and energetic ecosystem. Forecasting mHealth growth is best approached with a simple

Fermi Method analysis.

First, the base number of cell phones and subscriptions have reached most people on the

planet. From a classic “6 degrees of separation” perspective,143 the vast majority of people are

classically separated to within one to two people144 on the planet, as the classic “Kevin Bacon”

game illustrates. The ITU145 reports annual statistics for mobile communications and estimates

that at least 95% of the world’s population lives in an area covered by a mobile cellular network, of 2G or better. The ITU observes that 84% of the global population and 67% of the rural population have access to at least 3G cell phone communications. LTE class networks have reached almost four billion people or about 53% of the global population. With quarterly sales

(see previous) of almost 350 million cell phones, it can only logically be that most of the world’s population is rapidly increasing their network access speeds and capability. The mobile network characteristic (2G to 5G, and/or LTE) is not only a measure of speed, but also of applications capability. This positive modifier strongly affects mHealth Applications growth.

142 Bell, “Amazon Alexa Can Now Be Your Doctor.” 143 Duncan J Watts, Six Degrees: The Science of a Connected Age (New York, NY: W.W. Norton, 2003). 144 Craig Fass, Brian Turtle, and Mike Ginelli, Six Degrees of Kevin Bacon (New York, NY: Plume, 1996). 145 “ICT Facts and Figures 2016.”

Secondly, regulatory limitations that have traditionally blocked or slowed mHealth

application and device growth are rapidly crumbling. Adoption of telemedicine services by

Walmart (the nation’s leading civilian employer) and the US Military (with millions of service

members and their families) breaks the ice for rapid implementation of computer and mobile

telemedicine services. Leadership by states, such as Texas,146 in passing defining legislation147

for how telemedicine, and by extension telehealth, services and products are reimbursed by

traditional medical payers is a strong positive modifier.

Third, an extension of telemedicine services and products to an international148 market should serve149 to reduce medical costs in the US. The US medical care community, staff, and

mHealth products are strongly represented in telemedicine. Simple price comparison applications alone will deliver downward pricing pressures. This effect also has a positive, strong growth

effect.

Fourth, mHealth comparison applications and companies, such as150 GoodRx.com will be

much more freely accepted as a valid model for medical comparisons. Estimating cost and

pricing of health services is currently difficult or impossible for many procedures. This has very

effectively served to drive up or deny health care services to many people. Outcome based

medical services comparison can also be implemented from publicly available data. What is

146 Erin Dietsche, “Texas Law Marks Turning Point in Telemedicine,” MedCity News, May 30, 2017, accessed July 26, 2017, http://medcitynews.com/2017/05/texas-law-telemedicine/. 147 “Cheaper, Faster Health Care?” 148 Saliba et al., “Telemedicine across Borders: A Systematic Review of Factors That Hinder or Support Implementation.” 149 “How Telemedicine Disrupts Health Care.” 150 “About GoodRx.”

difficult or impossible to know about health-related outcomes and expenses can be known with

the extension of current applications.

Fifth, as 5G performance, capabilities, and applications appear shortly, we can start with

a minimum base production number of at least 150 million 5G units per quarter. This is based on

the supposition that high-end smartphones will substantially be 5G. Different geographic

locations will adopt 5G at different rates, but cell towers may remain the same while changing

only the base system electronics and possibly the connecting networks. 5G roll out rates have not

yet been published, but overall this technology boost is a positive, strong mHealth affecter

There are additional affecters on mHealth Application growth, but they can be discussed in the

next section, where we propose some comparison methods. The purpose of considering affecters

is to link to the analytical approach of Markov Chains and effectors in our analysis.

Evaluation of Affordances

It can be extremely difficult to analyze and forecast successful mHealth innovations,

devices, applications, or systems. A simple Fermi Analysis, as recommended by Tetlock and

Gardner,151 is very useful to start the analysis process. When considering a standard product

conversion, invention, or innovation of a mHealth product, there are three useful basic composite

criteria to use.

First, a composite binary go (yes) / no value may determine whether the device or

application is an appropriate mHealth solution. A simple binary “1” can represent “yes” and a

“0” can represent a “no.” This should be the first factor to reduce the possible solution set.

151 Tetlock and Gardner, Superforecasting.

Second, a static composite value can be determined based on the relative measure of

importance for each analysis stream. This static value must, by nature, be dynamically subject to

revision.

Third, a dynamic composite value can be determined for temporal importance. For

example, in a mHealth start-up, capital resources can be extremely important. As time goes by

and an application is delivered to the market, this dynamic value could reduce in importance.

Consider the example of the shark, with its eight different sensor streams and the temporal value of each stream. Different needs, as Maslow152 identifies, can also be

accommodated by creating a new value matrix for each need.

This approach allows for simple, rapid Kalman valuation for a composite analysis. In a

spreadsheet/matrix form, the table would look as follows:

Table 6. Evaluation of Affordances Upon mHealth Applications and Devices Binary Static Temporal Composite Analysis Stream Yes/No Value Value Value B S T CV Profit B S T CV Cash B S T CV Ubiquity of Mobile Networks B S T CV Global Need for Healthcare Provision B S T CV Infrastructure of Mobile Comm S T CV Ecosystem B End User Practices B S T CV Rising Health Care Costs B S T CV US Legislation at State and Federal S T CV Levels B Global Translational Alliances B S T CV Infrastructure of Health Care S T CV Industry B

152 A. H. Maslow, Motivation and Personality, 1st ed. (Harper & Brothers, 1954).

Finance, Funding, and Capital Trends B S T CV Rate of Growth for Smartphone S T CV Applications B a ‐ Recent Smartphone Vendor S T CV Growth B b ‐ Recent Smartphone OS Growth B S T CV c ‐ Recent Smartphone Apps Growth B S T CV d ‐ New Smartphone Linked Device S T CV Growth B Rate of Growth for mHealth S T CV Applications B Total = B KCV Where: B = Binary = Product of Binary Yes/No S = Static Value = Range between 1 and 10 T = Temporal Value = % multiplier based on time value CV = Composite Value is Static * Temporal value (note: Rate of Growth divided into four parts ‐ 25% each)

A Kalman Filtered Composite Value (KCV) is at the bottom right side of the Table 6 CV column. This simple Fermi Analysis approach of assigning importance (S) and time value (T) can quickly yield a numerical, weighted importance value, which will be applied in Chapter 4 to the affordances identified here.

CHAPTER 4

KALMAN VALUATION FOR A COMPOSITE ANALYIS IN mHEALTH

FORECASTING

Applying Kalman Filtered Composite Value (KCV) to the affordance streams identified in the present study yields the data shown in Table 6 and its explanation presented later in this chapter. As will be explained, the table depicts the values assigned for each of the 14 affordances identified as crucial to forecasting mHealth growth. The formula applied to these values follows their presentation.

First, a discussion of the results of my analysis of the mobile communications ecosystem’s adoption and accepted practice of mHealth care delivery benefits from a description of an interpretative method, a few historical examples, and a discussion of forecasting accuracy to situate readers’ understanding. Examples from history are important to call to mind as mHealth devices and applications start to roll out with increasing speed, a lesson I argue should be codified into standard business decision-making. Specifically, the example of the evolutionary development of early wireless communications technology affords an instructive analogy because it shows in retrospect how affordances upon tech development play out.

A Retrospective on Early Wireless Affordances

To begin, there were many experiments in wireless communications before 1900 and

after. Yet, it took Marconi153 to put together the wireless communication equipment, business opportunity, financial resources, and revenue generating market niche. Experiments conducted with bulky, unreliable, and poor performing equipment were only sometimes successful.

Ultimately, it took efficient and firm solutions in all aspects of the technology to bring two-way communications to market. Much like Samuel Morse,154 Marconi understood that it

took a combination of technologies and methods to develop a successful new business. By using

Hertzian wavelengths, his RF transmissions could travel for great distances. He was able to

establish wireless communications stations on both sides of the Atlantic, to transmit trans-

oceanic messages. Soon there was even widespread communication between ships and ground-

based stations. What Marconi brought to the party was an understanding of all the of the

necessary elements of disruptive innovation. He also understood that there was a market niche

that his company could fill while also generating revenue. Many of the first wireless

technologies could be demonstrated to work, but there was not an overwhelming business or

revenue case for building a company. While early researchers anticipated profitable sales of

voice based wireless communications, no one knew at that point the human impact it would

153 Calvin D. Trowbridge, Marconi: Father of Wireless, Grandfather of Radio, Great- Grandfather of the Cell Phone, The Story of the Race to Control Long-Distance Wireless (S.I.: BookSurge Publishing, 2010). 154 Carleton Mabee, The American Leonardo: A Life of Samuel F. B. Morse, Rev Sub 1943. (Fleischmanns, NY: Purple Mountain Pr Ltd, 2000).

have. However, and importantly, all involved recognized that an industry founded upon wireless telephonic technology would generate revenue.

Fast forward to the contemporary mobile communications ecosystem, which takes an established company with revenue and a sustaining business model to provide the infrastructure, systems, and cell phone towers necessary to deliver mobile services. While many early attempts to wirelessly communicate worked as expected, there wasn’t a compelling problem, that is, an external motivator—an affordance upon the ecosystem—that wireless communications could solve, which is an important distinction in the context of the current mobile communication ecosystem and the pressing need for health care delivery. However, calculating affordances is at present neither a standard nor intuitive method of doing business, and I posit that it should be.

Murray and Sidgmore wrote about the early years of cell phone use and technology, and the picture they paint is revealing. Preceding deployment of the modern cell phone system, they wrote155 that “as late as 1981 [...] only 24 people in all of New York City could be on their mobile phones at once.” The prospect of thousands and then millions of New Yorkers having cell phones, being able to make calls, and then talk at the same time was not a prospect that the original mobile phone network designers envisioned or planned for.

Further, Motorola was focused on delivering a high-performance and low-cost service.

Engineers Mitchell156 and Cooper had an excellent sense of how successful the initial product

155 James B. Murray and John Sidgmore Jr., Wireless Nation: The Frenzied Launch of the Cellular Revolution in America by James B. Murray Jr., John Sidgmore (2001) Hardcover, 2001st ed. (Basic Books, 1709), 19. 156 Guy Klemens, The Cellphone: The History and Technology of the Gadget That Changed the World (Jefferson, N.C: McFarland, 2010).

launch could be, but at AT&T, the company was rigidly focused on the impending, government mandated corporate breakup. What would happen to the separate AT&T operating companies was mostly unknown, and what would happen to the research and product production segments of AT&T was vastly more at risk. Cauley writes of the fall157 of AT&T in End of the Line: The

Rise and Fall of AT&T. Put simply, AT&T had a cash cow strategy that made money from long distance calling. But that cash cow was quickly evaporating under relentless legal and illegal competition. Cauley describes the period as a “perfect storm” of adverse conditions. In this study, such a force is considered an affordance stream, an external motivator for innovative change. One might even think of them as the precursor to any paradigm shift.

After the AT&T breakup in 1984, McCaw158 brought a balance of innovations and cost to the cell phone industry that revolutionized the ability of people to afford and operate their phones. He made it practical to have a frequent cell phone upgrade, thus enabling new revenue streams from those who wanted the service. During the 1980s to early 1990s, he was considered by many159 to be the “father of modern cellular system.” A cellular company is more than phones, cell phone towers, and networks, however. It was and is also about enabling customers to pay to move laterally within the ecosystem.

157 Leslie Cauley, End of the Line: The Rise and Fall of AT&T (New York: Free Press, 2005). 158 O. Casey Corr, Money from Thin Air: The Story of Craig McCaw, the Visionary Who Invented the Cell Phone Industry, and His Next Billion-Dollar Idea, 1st ed. (New York: Crown Business, 2000). 159 F Meeks, “Would You Believe It? Craig McCaw Says He Is Risk-Averse.,” Forbes 151, no. 5 (1993): 78–82.

Furthermore, key changes in the mobile communications ecosystem can be seen in the

smartphone,160 which predominantly uses a Linux-derived operating system. Those that do not,

such as Windows phones, Blackberries, Symbian, Bada, Palm, or Meego seem to be defunct or

on their way out. Modern smartphones have been around in concept for many, many years.

The affordance streams in smartphone app development stem from the fact that they can

do many functions that previously required separate devices, such as a music player, video

player, video game player, digital camera, provide an internet link, and more. Even services like

banking, charitable contributions, navigation, and more are now firmly embedded in the smartphone. This common, usually free, set of powerful functionalities serves to unite people all over the world into a roughly common user community. This is a critical element in the way mHealth technology will roll out. In other words, mHealth is not a “single region” technology.

Communications standards for cell phones have experienced evolutionary growth and are a significant affordance in the mobile communications ecosystem. For the most part, transmission protocols have followed a logical path with some deviations for specialized locations or adaptations, but they are a key influence upon other sectors in the ecosystem. For example, when 2G service arrived text messaging was enabled and found immediate use. With

3G service, vastly improved data transfer speeds, as well as links to computers and other consumer devices, became possible. 4G communications now enable mobile web access, IP telephony, gaming services, mobile HDTV variants, and some cloud-based computing. 4G systems have been deployed since 2008 in the US and Europe in 2009. However, 4G is still not

160 Brian Merchant, The One Device: The Secret History of the IPhone (Little, Brown and Company, 2017).

universally available in Europe. In much of the rest of the world, it is still basic 2G systems that link towers and cell phones. As happened when the transition from 3G to 4G occurred, overall data rates increased, and new uses were enabled.

The next generation of ITU proposed IMT-Advanced 5G standards permit data rates of a gigabit per second and communication with many users from a single cell phone. For example, on the same local office floor, up to one gigabit per second of data can support multiple handsets.

Improved coverage, faster networks, and massive sensor deployment technology is also supported. The general future expectation is that 5G might support up to ten gigabit per second transfers, optimal for IoT applications. The rapid worldwide adoption of faster network standards, such as 3G, 4G, and 4G-LTE is happening. Christensen makes clear in his analysis that a disruptive innovation can result in unexpected outcomes, and this makes the application of forecasting principles vital.

Accuracy of Experts: Understanding the Importance of Forecasting

Dan Gardner and Philip Tetlock brought the elements of careful observation and a scientific prediction process together161 in Superforecasting: The Art and Science of Prediction.

Tetlock makes the point that the average, generally astute technical person (the fox) can learn the skill of prediction and forecasting. A person can then hone the craft and become a measurably more accurate predictor. Tetlock relates the story of a small, generally skilled, diverse group that banded together to learn forecasting skills. They developed forecasting techniques and measurably improved their accuracy in real world situations. This group entered into an open

161 Tetlock and Gardner, Superforecasting.

competition to predict outcomes in designed, competitive situations. They thoroughly trounced

traditional, silo skilled (badger) competing professional predictive competition and won a

substantial prize. Prediction and forecasting are extremely important skills and can be applied to financial, military, political, medical, insurance, scientific, academic, organizational, and more areas.

Forecasting and predictive skills aren’t insignificant. Many sectors of our society depend on accurate, predictive science and data analysis. Events such as the Spanish-American War, the great Flu Epidemic of 1918, the invasion of Iraq, the second invasion of Iraq, the Wall Street

Flash Crash, and others are just a few of the many examples of failed expert predictions.

Accurate prediction skills matter in insurance rates, building schools, and an absolute blizzard of other everyday activities. Do you follow the economic, financial advice of Jim Cramer? Do you buy a Lottery ticket in hopes of winning? Predictive skills are at the heart of everyday decision making.

Tetlock and Gardner advocate use of Fermi Estimation Techniques to improve predictive accuracy. How should a generally skilled individual estimate the probability of an event or a specific result? Enrico Fermi162 used a simple technique quite often. The method can quickly

yield reasonable starting place accuracy and can best be observed by application.

When faced with a problem that one does not have sufficient information or skills for, then the Fermi Estimation method can be a reasonable starting place. Though dated, the classic

162 Aaron Santos, How Many Licks?: Or, How to Estimate Damn Near Anything (Philadelphia ; London: Running Press, 2009).

“Piano Tuners in Chicago” example problem163 assumes that you may not know the exact answer, although one can deconstruct the question into significant parts with readily available information. The example is presented first. The question is “How many piano tuners are there in Chicago?”

1. “There are approximately 9,000,000 people living in Chicago. 2. On average, each Chicago household has two individuals. 3. Roughly one home in twenty has a regularly tuned piano. 4. Regularly tuned pianos are serviced once per year. 5. It takes a piano tuner two hours to tune a piano, including travel. 6. A piano tuner works eight hours a day, five days per week, and fifty weeks per year. 7. From the numbers, we can roughly estimate that there are 225 Chicago area piano tuners. 8. The actual number is approximately 290.“

Fermi came up with a simple prediction/forecasting method to allow quick “back of the envelope” calculations. Fermi’s method is:

1 – “Dare to be imprecise. 2 – Decompose or deconstruct the problem 3 – Estimate by bounding 4 – Sanity check the answers. 5 – (A modern addendum) – use Google for information research as needed.”

Tetlock provides further guidance for aspiring forecasters164 based on Fermi’s methods.

1 – “Triage. Focus on questions where your hard work is likely to pay off. 2 – Break seemingly intractable problems into tractable subproblems. 3 – Strike the right balance between inside and outside views. 4 – Strike the right balance between under and overreacting to evidence. 5 – Look for the clashing causal forces at work in each problem. 6 – Strive to distinguish as many degrees of doubt as the problem permits but no more. 7 – Strike the right balance between under and overconfidence, between prudence and decisiveness. 8 – Look for the errors behind your mistakes but beware of rearview-mirror hindsight

163 “Fermi Problem,” Wikipedia, the Free Encyclopedia, March 15, 2016, accessed May 15, 2016, en.wikipedia.org/w/index.php?title=Fermi_problem&oldid=710266046. 164 Tetlock and Gardner, Superforecasting, 277–285.

biases. 9 – Bring out the best in others and let others bring out the best in you. 10 – Measure the error-balancing bicycle. 11 – Don’t treat commandments as commandments.”

Fermi estimation has use in the most improbable of applications. For example, the Drake

Equation165 uses Fermi estimation methods to predict the probability of intelligent life in the

universe. Fermi estimation methods can be applied to most every prediction or forecasting effort.

As a perceptual tool, an understanding of forecasting tools and techniques is of critical

importance. Not everything that is supposedly factually known is accurate. This is where the role

of storytelling becomes valuable as one method to grasp something as complex as a technology

ecosystem.

Tetlock intensely studied the accuracy of experts for over 30 years. He based his original

approach on the philosophical considerations of Isaiah Berlin. Berlin166 wrote an extraordinary

essay on Tolstoy’s view of history. Does a general collection of skills always outperform a single

specialized skill? Gopnik167 wrote a thought-provoking piece for the Wall Street Journal in

which he examines that question in a very practical fashion. If one is to deconstruct something,

then a multiple skilled analytical perceptual toolset is critical to evaluate possible outcomes.

Multiple analytical skills are essential for object reconstruction.

165 Frank Drake, The Drake Equation: Estimating the Prevalence of Extraterrestrial Life through the Ages, ed. Douglas A. Vakoch and Matthew F. Dowd, 1st ed. (Cambridge University Press, 2015). 166 Isaiah Berlin and Henry Hardy, The Hedgehog and the Fox: An Essay on Tolstoy’s View of History, 2013. 167 Alison Gopnik, “In Life, Who Wins, the Fox or the Hedgehog?,” WSJ, accessed October 25, 2015, www.wsj.com/articles/the-reality-behind-isaiah-berlins-fox-and-hedgehog-essay-1408144444.

Tetlock and Gardner wrote Superforecasting168 founded on accuracy-of-experts research performed by Tetlock and his team. It is important to understand that experts can be inaccurate.

It is also important to comprehend how a broad expertise can improve the overall accuracy of a prediction. This sounds quite abstract until one realizes how truly pervasive that our use of prediction is.

Super-forecasting, in this case of mHealth tech growth, involves applying the basic accuracy of experts principle Tetlock describes. For example, if one goes to a doctor and receives a medical diagnosis, how accurate is it? If one works and saves money for retirement, then how accurate is the financial advice one receives? Should one listen to the financial advice that Jim Cramer doles out on popular broadcast television financial planning shows? Is Cramer’s commentary sound financial advice, showmanship, or both? How do you know and how can you tell? Humans make decisions every day which are, in effect, predictions. This topic is not abstract, it is something that we do all the time.

Forecasting is a critical perceptual and reconstructive toolkit staple. It allows us to make a reasonable, fact and logic based projection. Superforecasting becomes a more advanced step upward. It adds the application of scientific methods and proven techniques to increase forecasting accuracy. Therefore, Superforecasting becomes a useful anticipation element. When things do not go as planned, then one can make a change in prediction. This, obviously, was not something that AT&T or McKinsey did in their report. Their prediction covers a time span beginning in the early 1980s and ending in the year 2000.

168 Tetlock and Gardner, Superforecasting.

Superforecasting, as Tetlock asserts, applies the tools of science to predictive forecasting.

As explained below, in an mHealth forecast, Tetlock’s method affords a means to measure the

accuracy of a forecast and then, for example within the mobile communications ecosystem, use it

to modify or adapt a given course of action. It is valuable to add that Fermi estimation is

consistent with Foucault’s post-structuralist method of analysis, as well. By conducting an

archaeology of the mobile communications ecosystem, as it were, we can begin to comprehend

the relationship between powerful focuses within it. Thus, superforecasting permits a simple

value to be assigned to deconstructed elements, which can then become useful in a theoretical

predictive model.

Tetlock also brings out the iterative nature of the forecasting and predictive process. A

decision early in an iterative predictive process can have a major impact later in the process. This

follows the logical path described by Lao-Tzu, Lorenz, Laplace, and others. Lorenz

popularized169 what is now called “The Butterfly Effect” in his classic 1972 paper,

Predictability: Does the Flap of Butterfly’s Wings in Brazil Set Off a Tornado in Texas? Lorenz

did not set out to change the world with his paper, but he certainly did. People began to consider

his iterative approach in diverse disciplines and how a small initial change can result in a big outcome difference. For purposes of forecasting, it is important to consider what relationship forces are at work. With Lorenz’s observation in mind, let us consider two examples.

169 Edward, “Predictability: Does the Flap of a Butterfly’s Wings in Brazil Set Off a Tornado in Texas?”

The Markov Chain,170 as mentioned previously, is a relationship that allows a linkage to a

future state to be described by the current state and predictive conditions. If a current state is going to change to a future state in a quantum system, then that is a forecast.

Visualization of a chain topology for the transmission of ideas—from source to

destination—is an excellent way to approach the study of idea conception to delivery.

Translation effects happened at each step of the process. This is an example of a chain-based

topology.

Chain topology visualization can be used to understand the translations of ideas from the

luminal space to instantiations. Victor Turner171 credits Van Gennep as the father of “formal

processional analysis.” Turner asserts that Van Gennep:

“Used two sets of terms to describe the three phases of passages from one culturally defined state to another. Not only did he use, with primary reference to ritual, the serial terms separation, margin, and reaggregation; he also, with primary reference to spatial transitions, employed the terms preliminal, liminal, and post-liminal.”

Applications of ritual understanding analysis can be effectively visualized as elements of a

linked chain.

Device-Level Forecasting within the Mobile Communications Ecosystem: The Automated

External Defibrillator (AED) Example

Within the mobile communications mHealth ecosystem, devices may be either certified

or exempt from US FDA rules. The FDA carries a list of over 20,000 FDA registered device

companies. Some companies have many products and some companies only have one. One can

170 Privault, Understanding Markov Chains. 171 Victor W. Turner, Roger D. Abrahams, and Alfred Harris, The Ritual Process: Structure and Anti-Structure, Reprint. (New York: Aldine Transaction, 1995).

take the entire list of medical devices and filter down to what could be adapted to a cell phone.

The remaining qualification list can be further filtered in a variety of fashions. Remaining

devices can have a number of different characteristics compared and a value assigned. Big data

information can allow for large amounts of information to be compared. If one were to take the

top one hundred devices and consider those best suited to cell phone adaptation, one could end

up with a reasonable list of potential mHealth device applications. Thus, superforecasting at the

device level can use big data to accomplish an equivalent approach to understanding market

trajectories.

Linkage to the cell phone network can have a force multiplication effect. As an example,

Automated External Defibrillators (AED) are a portable medical device that may be used to

“jump start” a stopped heart. Since heart attacks are the acknowledged number one killer

(disease) in America, it is important to have the AED work, if needed. AEDs also have a high

failure rate over time. AEDs generally do not have a smart test and notification capability. As a

result, estimates are that about 20% of deployed US AEDs have failed172 and will not work when

needed. A cell phone linked AED system can self-test and notify a concerned party with a text message or a web based application. A mobile phone based AED can tap into online training, it can notify and summon medical assistance when used, and it can provide real-time, online access to expert medical care via audio and video. It could save many lives. Given that AED treated

172 Linda Carrol, “Bad Batteries in Defibrillators Tied to Cardiac Deaths,” Msnbc.Com, last modified September 2, 2011, accessed August 4, 2017, http://www.nbcnews.com/id/44364504/ns/health- health_care/t/bad-batteries-defibrillators-tied-cardiac-deaths/.

heart attack incidents are approximately 40% successful173 versus 5% for CPR, this cost difference, and the need to forecast this technology’s development is crucial. Every minute that passes after a heart attack sees the patient chance for recovery or survival drastically decrease, by seven to 10 percent, per minute. The cell phone based AED design may not be as high quality as we might wish, but it has a greater chance of working when needed and can summon expert

medical assistance much, much faster. It is also at a low enough cost to distribute around the

world in tremendous numbers. Where there is no other choice, it is a game changer in the battle

to save lives.

Forecasting Overall mHealth Growth in the Mobile Communications Ecosystem

Below is an application of superforecasting methods to the affordance streams identified

in Chapter 3. Applying a method to measure the external forces at play within the mobile communications ecosystem represents promising potential for the future relationship between smartphone technology and the growth of mHealth applications.

173 American Academy of Orthopaedic Surgeons et al., Advanced First Aid, CPR, And AED, 7 edition. (Burlington, MA: Jones & Bartlett Learning, 2016).

Table 7. Formula for Calculation of Affordances Upon the Mobile Communications Ecosystem for mHealth Applications and Devices

In Table 7, B is a composite binary go(yes)/no value. It relates to whether a device or

application is an appropriate mHealth solution. A binary “1” represents “yes” and a “0”

represents a “no.” B could also be a fractional value between “0” and “1” to represent that, while some devices and apps are possible, they may be relatively easy or relatively difficult to implement.

S is a relative value measurement estimate for each affordance. Values range from “1” to “10” and do not change for the device or application.

T represents the temporal value. For example, in a mHealth start-up, capital resources can be extremely limited but also important. Cash may also be important initially. As time goes by and an application is delivered to the market, this dynamic value could reduce in importance.

This could be represented by a formula that was time dependent, based on how long to develop the application and time to recover the initial capital after application delivery.

CV represents the composite value of each affordance. The formula would be

CV = B * S * T

Where T nominally a value or a time dependent formula.

KB is the composite binary value. If any of the affordances are inappropriate or completely block the device or application, then KB would be a “0”.

KB = B(1) * B(2) * …. * B(13)

Lastly, KCV represents a composite Markov Value for the table. The KCV value is a type of rudimentary Markov value and allows for general comparisons. The formula is:

KCV = CV(1) + CV(2) + …. + CV(13)

Where the rate of growth affordance has four components at 25% each.

With thousands to millions of potential mHealth devices and applications to consider, there must be a simple way to compare merit on which devices to implement first. Some table values may result from detailed analysis, while others are a “best guess” on relative merit.

Tables 8 to 10 explain the general rational for assignment of Binary, Static and Temporal Values to each affordance.

Table 8. Rationale for Binary Values for Each Affordance Affordance Binary Rationale Value Profit Y/1 Development Funds come from Profits: Current or Future Cash Y/1 Cash limits development size

Ubiquity of Mobile Networks Y/1 Presence of wireless networks and standards limit/enable scope Global Need for Healthcare Provision Y/1 Multi market allows for selective development at variable pace Infrastructure of Mobile Comm Ecosystem Y/1 Infrastructure enables/limits application data rates End User Practices Y/1 Different culture practices directly affect allowable app practice Rising Health Care Costs Y/1 Rising Costs increase market pressures for efficient solutions US Legislation at State and Federal Levels Y/1 Legislation affects reimbursement or gates apps or services Global Translational Alliances Y/1 Affects costs, device, and application deliveries. Infrastructure of Health Care Industry Y/1 Subscription permitting, costs affecter, Communications permit. Finance, Funding, and Capital Trends Y/1 Ecosystem for apps and devices to exist and grow/shrink in. Rate of Growth for Smartphone Applications Y/1 General growth enabler/inhibitor.

Rate of Growth for mHealth Applications Y/1 Affecter of new app, device acceptance, and scope.

Table 9 explains the rational for Static Values (S) assigned to the affordances operating upon the mHealth mobile communications ecosystem.

Table 9. Rationale for Static Values for Each Affordance Static Rationale Affordance (S) Value Profit 1 - 10 Limits project scope and affect device/application mix. Cash 1 - 10 Dynamic composite Cashflow for project needs

Ubiquity of Mobile Networks 1 - 10 Enabler of what kinds of apps/devices operate in a market. Global Need for Healthcare Provision 1 - 10 Different regions have different needs – yet use same ecosystem. Infrastructure of Mobile Comm Ecosystem 1 - 10 Enabling linkage within ecosystem and between ecosystems End User Practices 1 - 10 Cultural expectation for device and app operation Rising Health Care Costs 1 - 10 Regional motivator for acceptance of new mHealth devices and apps US Legislation at State and Federal Levels 1 - 10 Early adopter affecter for new mHealth devices and applications Global Translational Alliances 1 - 10 Key Logistics, Finance, and distribution affecter. Infrastructure of Health Care Industry 1 - 10 Selective ecosystem landscape of specific device/app products Finance, Funding, and Capital Trends 1 - 10 Growth limiter and enabler

Rate of Growth for Smartphone Applications 1 - 10 Consumer acceptance of new device and app types Rate of Growth for mHealth Applications 1 - 10 Expanding ecosystem enables additional mHealth applications

Table 10 below explains the rational for Temporal Values (T) assigned to the affordances operating upon the mobile communications ecosystem.

Table 10. Rationale for Static Temporal Values for Each Affordance Affordance Tempo Rationale ral (T) Value Profit 0 - 2 Profit Needed may vary depending on app or device Cash 0 - 2 Overall project size requirement limitation Ubiquity of Mobile Networks 0 - 2 Limits available apps/devices by region Global Need for Healthcare Provision 0 - 2 Varies by Region and may increase over time Infrastructure of Mobile Comm Ecosystem 0 - 2 Varies by Region and may improve over time

End User Practices 0 - 2 Culturally accepted use and applications Rising Health Care Costs 0 - 2 Increasing pressure on acceptable device and app needs. US Legislation at State and Federal Levels 0 - 2 Can be services inhibitor or reimbursement enabler. Global Translational Alliances 0 - 2 Support ecology for apps and devices.

Infrastructure of Health Care Industry 0 - 2 mHealth devices and apps apply pressure to reduce cost in ecosystem. Finance, Funding, and Capital Trends 0 - 2 Available needs change and source of capital change. Rate of Growth for Smartphone Applications 0 - 2 Generally positive upward pressure on app growth Rate of Growth for mHealth Applications 0 - 2 As app sales grow, mHealth can ride growth and increase organic growth

For a specific mHealth device or application, one may assign a considered value to each affordance in the table and end up with a composite KCV value. The KCV value is a type of rudimentary Kalman Value and allows for general comparisons.

CHAPTER 5

PREDICTIVE MODELS FOR TECHNOLOGICAL GROWTH: IMPLICATIONS FOR

FURTHER RESEARCH

As discussed in earlier chapters, the external forces necessary for innovative disruption of current models and modes of delivering health care already exist. And whether globally or domestically, failing or missing health care provision seems pointless in contrast to the rich potential within tech industries to produce and market life-changing solutions, as opposed to being driven foremost by profit. To grasp the complex and dynamic relationship between mobile

communications technology and health care, a reframing of each using a biological metaphor

borrowed from Gibson174 offers a way to discuss these two realms of business that may

otherwise appear impenetrable to coordinated technological change. Gibson’s psychological

ecosystem theory also frames this analysis of the constellation of competing interests affecting

the development of mHealth technologies. Furthermore, by renaming the information and

influences upon this dynamic relationship as affordances, and in suggesting a method for

weighing a set of affordances with which we can impose mathematical analysis, I have offered

an example to compare and demonstrate that we can systematically study the trajectory and

likelihood of mHealth to evolve from a sustaining innovation to a disruptive innovation. Further,

such a method can be applied across the medical health industry, and even to the development of

new platforms, devices, and applications, to understand and exploit the link between ubiquitous

174 James G Greeno, “Gibson’s Affordances.” (1994).

mobile communication subscribers and the untold potential of technology to address their

mHealth needs.

A return to the questions driving this research project is necessary to summarize the

efficacy of the theoretical model I propose:

 What would the future of the tech industry’s contribution to solving the problem

of health care delivery be if it were self-reflective enough to learn from its

historical trends?

 What forces impede both the prediction and industry development of smartphone

adaptation to solve the health care delivery crisis?

 What perceptual tools can be used to evaluate the current market and development

trends to better predict how mobile health technology (mHealth) might roll out in

effective ways that could impact global health and do so with greater predictive

accuracy?

The present study represents a structured reflection upon a variety of missed opportunities in the history of technology and contrasts those instances to moments when innovation has shown itself to be substantially and profitably disruptive to business models and human practice. From Tetlock and Gardner in Superforecasting175, there is a sound basis for forecasting some short term mHealth ecosystem growth.

175 Tetlock and Gardner, Superforecasting.

The healthcare industry is not a single, monolithic entity. As an industry, technology’s contribution to solving healthcare delivery is, therefore, best approached by considering healthcare players and their technology approach.

For instance, in the biopharmaceuticals segment, Gilead Sciences176 has been hailed as an example of the perfect Pharma stock company by Investor Web site Motley Fool.177 With its patented, incredibly successful Hepatitis C (HCV) treatment drug Harvoni,178 Gilead is delivering what many consider a miracle drug. Gilead’s strategy is to use marketing to entice customers and to strategize other payers to pick up the bill. Insurers, governmental payers, and any other payer—including medical debt technology—are sought. In this era of big data, a very great deal can be known about each patient needing HCV treatment, in particular, their financial ability and third-party payer status. In some locations, HCV is a declared epidemic, yet 97%+ of patients who apply for treatment via Medicaid179 are denied. Given the declared epidemic nature of HCV in some regions, the question of whether Gilead is self-reflective enough to learn from historical trends is very medically important.

Clearly, Gilead has learned from the medical ecosystem in which it exists and responds according, and it is just one example in a long list of corporations that would resist migration to mHealth platforms if their profits are threatened. Gilead’s mission is to maximize shareholder value, as Motley Fool observed. As other companies began to make competing HCV treatments

176 “Gilead Sciences, Inc.” 177 Williams, “6 Reasons Gilead Sciences Could Be the World’s Most Perfect Stock -.” 178 “HARVONI® (Ledipasvir 90 Mg/Sofosbuvir 400 Mg) | Official Site,” accessed August 1, 2017, http://www.harvoni.com/. 179 Rubin, “Hepatitis C Drugs Top State Medicaid Pharmaceutical Expenditures.”

available, there will be a role for mHealth comparison applications to step forward and supply

alternate HCV treatment information. Other companies are making lower cost, competing drugs.

An mHealth app with a full set of choice options will significantly alter the delivery of medical

care, and this represents a resistant force against such an app’s immediate growth. In the health

care industry, addressing human health through mHealth applications means the future will be lower cost and offer consumers far more choice.

A second example is that the cost of health care for employers works to be economically prohibitive. Employers with fifty employees or more have mandated staff insurance coverage.

Therefore, employers are motivated to minimize cost to themselves and their employees.

Walmart, the largest US employer180 with 1.2 million US employees, is a role model for how to offer medical benefits at a reduced overall cost. They offer employees free access to nurse and

doctor supported telemedicine181 applications and services. As telemedicine applications are

becoming better supported by state and federal rules and laws,182 other commercial organizations will be switching to this lower cost model. Telemedicine, a mHealth platform, costs approximately $40 per visit at Teledoc183 or $200 for an annual telemedicine subscription plus a nominal co-payment. Lowering the cost of healthcare services by using telemedicine

technology will be driven by motivated employers and their consumer employees.

180 “Walmart Company Facts,” accessed August 1, 2017, http://corporate.walmart.com/newsroom/company-facts. 181 “Working at Walmart,” accessed August 1, 2017, http://corporate.walmart.com/our- story/working-at-walmart. 182 Dietsche, “Texas Law Marks Turning Point in Telemedicine.” 183 “Cheaper, Faster Health Care?”

An affordance which is not sufficiently addressed here is insurers who are motivated to

reduce cost and improve the medical experience. For example, Kaiser Permanente is a California

based health network. They saw 110 million people last year with 59 million connecting through

online portals,184 as CEO Bernard Tyson reported. Using mHealth apps as a first line screener

and information portal serves to greatly reduce cost and increase health care access. mHealth

telemedicine applications and companies are on a rapidly increasing trajectory. Kaiser is

spending hundreds of millions of dollars in this space and, as a medical industry leader, expects

other insurers and health maintenance organizations to follow suit.

A third example is the US Militiary, in particular, the US Army. The US Army has long

been an advocate of first responder medical support and has great experience in telehealth and

telemedicine systems. US Army telemedicine services185 now extend to both service members

and their families. There is a strong movement to extend these telemedicine services to veterans

and their families, who may be anywhere across the globe. The Department of Defense has long

been a source for early adopters in the US, too, and is moving strongly forward with

telemedicine research186 and applications. As in other technological innovations stemming from

DOD need, its relative freedom from over-regulation, and its overt study of health care

184 mHealthIntelligence, “Kaiser CEO: Telehealth Outpaced In-Person Visits Last Year,” MHealthIntelligence, last modified October 11, 2016, accessed August 1, 2017, https://mhealthintelligence.com/news/kaiser-ceo-telehealth-outpaced-in-person-visits-last-year. 185 mHealthIntelligence, “DoD Expands Telemedicine Access for Military, Families.” 186 “USAMRMC: Telemedicine and Advanced Technology Research Center Holds Demonstration,” accessed August 1, 2017, http://mrmc.amedd.army.mil/index.cfm?pageid=media_resources.news_releases.telemedicine.

innovations are driving expansion of military telemedicine. Military mHealth innovation

exploration will lead to future growth and broad dissemination of first responder telemedicine.

Regarding the forces that impede the prediction and industry development of smartphone

applications to the health care delivery crisis, the question turns out to be less complex. First, the

smartphone has only been around for slightly more than ten years. The Apple iPhone,187 generally considered the first cell phone with smartphone features, was launched publicly by

Steve Jobs188 on January 9, 2007. Already by 2017, there are over 2.5 million software applications (apps) that may run on the iPhone and it’s more numerous Android OS competitor.

But since medical apps or devices often have to go through a lengthy qualification and testing

process, this time-consuming procedure serves to impede industry development. This is not

necessarily a bad process, however, as previous medical market failures show. The US FDA is a

major player in the qualification of medical apps and devices. With a limited staff and little

vetted regulatory process in place, it has drastically slowed down FDA mHealth approvals.

Lack of transparent information is a second major impending problem. Accurate

information, pricing, medical billing details, and coding data can be difficult or impossible to

obtain. There are transparency problems for almost every reason conceivable, fraud, kickbacks,

rebates, credits, and the list goes on. Predicting price on pharma and device products is very

difficult, even with comparison apps like GoodRx.189 Elizabeth Rosenthal, an industry expert,

187 Merchant, The One Device. 188 Walter Isaacson, Steve Jobs (New York: Simon & Schuster, 2011). 189 “About GoodRx.”

details the complete chaos that medical billing has become in American Sickness.190 She asserts that secret pricing, secret discounts, “drive by” medical practices, multiple billing code systems, and more have made transparent pricing and predicted procedure pricing extremely difficult to predict. Transparent pricing and one-price-procedures are common in many countries, such as

India. The obvious answer to the question of why pricing is so high and outcome information is so sparse is because there is more economic benefit (read greater profits) with greater confusion.

Even with the nation’s largest employer, Walmart, pharma card based pricing is very difficult to obtain.

Clearly, those with a vested interest in higher prices and costs will impede transparent information. Vested interest will generally, but not always, oppose or impede applications and devices that reduce costs and supplier profits. Rosenthal makes the point that multiple standards of medical coding and the financial rewards from splitting the bill into its components are a large part of the rising cost problem. There is, as she observes, no reason that a standard 1.5 cent pain tablet should cost $25 to $70 in a hospital setting. Consequently, forces of economic transparency, which future competition between mHealth apps will inevitably provide, will ultimately collide with monied interests in both the medical care and mobile communications industries and present an impediment to efficient mHealth growth.

Perceptual evaluation and analytical tools discussed here can be used to better predict how mHealth devices and application might roll out by using a comparative, weighted model approach. The model can strongly impact global health by allowing rapid analysis of need,

190 Elisabeth Rosenthal, An American Sickness: How Healthcare Became Big Business and How You Can Take It Back, 1 edition. (New York: Penguin Press, 2017).

difficulty, frictional cost, and geographic application suitability. Since there is already a cell

phone subscription, financial relationships, use information, and geographic pinpointing, a

mHealth device or application prediction can be far more accurate.

An understanding of perceptual relationships between ecosystem static objects is

necessary to predict how change can occur. A knowledge of linked relationships, for example,

what a Markov chain consist of, is an excellent place to start. How energy, forces, and matter all

relate to allow for prediction of a “next” element in the chain sets a fundamental basis for

prediction. Also important is understanding more complex static relationship types such as rope,

fractal relationships, nonlinear relationships, and complex network relationships. Dynamic

relationship mechanics such as Sync,191 Viterbi192 encoding, Burst,193 and translational

relationships are then useful relational predictive and evaluation tools.

It is useful to understand the bubble theory194 of an apps ecosystem, as well. In that

theory, the natural relationships of a bubble can be compared to how apps can operate195 in a multi-million app environment. As the energy of a bubble increases or decreases, the bubble may expand or contract. Walls of the bubble are based on the structural material of the ecosystem. If a bubble “pops,” then the energy and material of the bubble is free to be used by

191 Steven H Strogatz, SYNC: How Order Emerges from Chaos in the Universe, Nature, and Daily Life (New York: Theia/Hyperion, 2003). 192 Andrew J Viterbi and Nagabhushana T Sindhushayana, “Soft Decision Output Decoder for Decoding Convolutionally Encoded Codewords” (August 3, 1999). 193 Albert-László Barabási, Bursts: The Hidden Patterns behind Everything We Do, from Your e- Mail to Bloody Crusades (New York: Plume, 2011). 194 Christopher E. Brennen, Cavitation and Bubble Dynamics, 1 edition. (New York: Oxford University Press, 1995). 195 Michael Begon et al., Ecology: From Individuals to Ecosystems, 2006.

surrounding bubbles. This symbolizes196 that the economic resources and people involved in app

development may increase or they may decrease and may move on to other app bubbles.

Moreover, Khosla emphasized the mutual interdependence of ecosystem members, something

that inspires further research.

Simple, flexible evaluation techniques, can be iteratively applied to information to evaluate current and development trends. Fermi estimation, or Tetlock’s improved Fermi

estimation and forecasting technique, comprise an excellent starting method. This study

advocates such an approach to business and mHealh197 forecasting, particularly regarding

products and services with global human reach.

Evaluation of a mHealth device, application, or general space can be done with an

affordances approach to merit. For specific devices or applications, there may be unique

additional affordances to consider. In specific cases, a general and a application specific set of affordances can be considered.

Iterative evaluation of affordances, based on real world results is inherent in a simplified, analytical approach such as is presented. Model evolution and training could be based on real world results from select crowd funded situations, such as data obtained from 120,000+

successful198 Kickstarter campaigns.

196 Carlota Perez, Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages (Cheltenham: Edward Elgar Pub, 2003). 197 Abu Saleh Mohammad Mosa, Illhoi Yoo, and Lincoln Sheets, “A Systematic Review of Healthcare Applications for Smartphones,” BMC medical informatics and decision making 12, no. 1 (2012): 67. 198 “Kickstarter Stats — Kickstarter.”

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BIOGRAPHICAL SKETCH

Robinson is an electronics, medical device, and consumer product Design Engineer. After decades of creating "bleeding edge" electronic product designs, he came back to UT Dallas to

complete a Ph.D. in Arts and Technology (ATEC). During his technology career, he has been

fortunate to design and create leading edge technology. Robinson architected early designs for

external disk storage, video and gaming computers, audio/video editing and production

equipment, RAID technologies, set-top box technologies, fabric computing, network

communications, wireless communication systems, energy products, and autonomous vehicle

designs.

Robinson directly started up five companies, co-founded others, performed Venture Capital

Accelerator technical analysis, and did consulting design for disruptively innovative

organizations. For any new idea to achieve success, a chain of successful components must

work. The very best ideas may often fail due to one link’s failure. This is why ATEC, stressing

multiple disciplines, is important. Robinson is interested in the "why and how" of technology.

Why “one thing" works instead of "another" becomes increasingly important as technology

evolves.

Robinson studied Nuclear Engineering at the University of Tennessee, has an AAS from

Richland College, a BSEE from UTD, a MA in ATEC from UTD, and a PhD from UTD.

Robinson is focused on mHealth, IoT, Green Technologies, and the ecosystems that enable them.

CURRICULUM VITAE

Jerry M. Robinson

EDUCATION AAS – Associate of Arts and Sciences, Richland College BSEE – Bachelor of Science, Electrical Engineering, University of Texas, Dallas MA-ATEC – Master of Arts in Arts and Technology, University of Texas, Dallas PhD-ATEC – Doctorate in Arts and Technology, University of Texas, Dallas

RESEARCH INTERESTS IoT – Internet of Things mHealth & Medical Device /Applications Design and Product Development Electronic Systems Design and Development Predictive Analytics for Inventive and Innovative Technologies Business Startup Methodologies

TECHNICAL SKILLS Electronics Design and Development mHealth and Medical Device/Apps design Multi Discipline Skill Set Approach to Technology Development

PROFESSIONAL MEMBERSHIPS SMPTE – Society of Motion Picture and Television Engineers IMIS – International Moving Image Society (formerly BKSTS) IEEE – Institute of Electrical and Electronics Engineers