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  • A 2017 research project found that only 6 out of 18 FDA-approved blood glucose monitoring (BGM) systems tested were accurate
  • Each day BGM systems are used by millions of people with diabetes to help them self-manage their condition, and avoid devastating and costly complications
  • Thousands of similar smart devices support the prevention and self management of other chronic lifetime conditions, whose prevalence levels are high
  • The increasing demand for healthcare, its escalating costs, and rapidly evolving technologies are driving the growth of such remote self-managed devices
  • The most valuable aspect of such devices is the data they produce
  • These data tend to be under valued and under utilized by healthcare providers
  • This has created an opportunity for giant technology companies to enter the healthcare market with a plethora of smart devices and start utilizing the data they collect to enhance patient outcomes and lower costs
  • Giant technology companies could dis-intermediate GPs and re-engineer primary care
 

Digital blood glucose monitors and the disruptive impact of giant tech companies on healthcare


A 2017 research project, which tested 18 FDA-approved digital blood glucose monitoring (BGM) systems, which are used daily by millions of people with diabetes to check the concentration of glucose in their blood, found that only 6 were accurate. The research, led by David Klonoff of the Diabetes Research Institute at San Mateo, California, was funded by Abbott Laboratories.
 
This Commentary describes both traditional and next-generation BGM systems, and Klonoff’s research. The Commentary suggests that BGM systems are just one part of a vast, global, rapidly growing market for consumer healthcare devices, and argues that the most valuable aspect of these devices is the data they collect. With some notable exceptions, healthcare professionals do not optimally utilize these data to enhance care and reduce costs. This has created for an opportunity for technology companies to enter the healthcare market and re-engineer primary care. The one thing, which might slow the march of giant technology companies into mainstream healthcare, is the privacy issue.
 

Traditional and next-generation BGM systems
 
Traditional BGM systems
Regularly, each day, BGM systems are used by millions of people with diabetes to help them manage their condition. Managing diabetes varies from individual to individual, and peoples with diabetes usually self-monitor their blood glucose concentration from a small drop of capillary blood taken from a finger prick. They then apply the blood to a chemically active disposable 'test-strip'. Different manufacturers use different technology, but most systems measure an electrical characteristic, and use this to determine the glucose level in the blood. Such monitoring is the most common way for a person with diabetes to understand how different foods, medications, and activities affect their condition. The challenge for individuals with diabetes is that blood glucose levels have to be tested up to 12 times a day. People obliged to do this find finger pricking painful, inconvenient and intrusive, and, as a consequence, many people with diabetes do not check their glucose levels as frequently as they should, and this can have significant health implications. If your levels drop too low, you face the threat of hypoglycemia, which can cause confusion or disorientation, and in its most severe forms, loss of consciousness, coma or even death. Conversely, if your blood glucose levels are too high over a long period, you risk heart disease, blindness, renal failure and lower limb amputation.
 

Next generation BGM system
Abbott Laboratories Inc. markets a BGM system, which eliminates the need for routine finger pricks that are necessary when using traditional glucose monitors. Instead of finger pricks and strips, the BGM system, which measures interstitial fluid glucose levels, comprises a small sensor and a reader. An optional companion app for Android mobile devices is also available. The sensor is a few centimetres in diameter and is designed to stay in place for 10 days. It is applied to the skin, usually on the upper arm. A thin (0.4 mm), flexible and sterile fibre within the sensor is inserted in the skin to a depth of 5 mm. The fibre draws interstitial fluid from the muscle into the sensor, where glucose levels are automatically measured every minute and stored at 15-minute intervals for 8 hours. Glucose levels can be seen at any time by scanning the reader over the sensor. When scanned the sensor provides an answer immediately. It also shows an 8-hour history of your blood glucose levels, and a trend arrow showing the direction your glucose is heading. The device avoids the pain, and inconvenience caused by finger-prick sampling, which can deter people with diabetes from taking regular measurements. In the UK the system costs £58 for the reader, plus £58 for a disposable sensor, which must be replaced every 10 days and from November 2017 have been available on the NHSAbbott Laboratories is a global NASDAQ traded US MedTech Company, with a market cap of US$86bn; annual revenues of US$21bn, and a diabetes care division, which produces annual revenues of some US$600m.
 
Klonoff’s research on BGM systems

BGM systems used by Klonoff and his team for their research were acquired over-the-counter and independent of their manufacturers. All were tested according to a protocol developed by a panel of experts in BGM surveillance testing.
 
Klonoff’s research specified that for a BGM system to be compliant, a blood glucose value must be within 15% of a reference plasma value for a blood glucose >100 mg/dl, and within 15 mg/dl of a reference plasma value for a blood glucose approved” a BGM system had to pass all 3 trials.  Only 6 out of 18 passed by achieving an overall compliance rate of 95% or higher. 

 

The FDA
Klonoff’s findings add credibility to patients’ concerns about the accuracy of BGM systems, which triggered responses from both manufactures and the US Food and Drug Administration  (FDA). Manufacturers suggest that increasing the accuracy of BGM systems would raise their costs, and reduce their availability, which patients do not want. The FDA tightened approvals for BGM systems, and in 2016 issued 2 sets of guidelines, one for clinical settings, and another for personal home-use. The guidelines only apply to new products, and do not impact BGM systems already on the market. So while the FDA’s tighter accuracy requirements are a positive change, there are a significant number of less-accurate BGM systems still on the market. 
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Next-generation BGM systems
Next generation BGM systems use ‘sensing’ technology, and have the capacity to automatically track and send blood glucose readings to the user’s smartphone, then onto their healthcare provider through the cloud where they can be amalgamated with other data. Analytics can then track an individual’s data, and compare them to larger aggregated data sets to detect trends, and provide personalized care.

Large rapidly growing remote self-managed device market

Although BGM systems address a vast global market, they represent just one part of a much larger, rapidly growing, remote monitoring market to help prevent and self-manage all chronic lifetime conditions, while improving healthcare utilization, and reducing costs. In 2015 some 165,000 healthcare apps were downloaded more than 3bn times. Of these, 44% were medical apps, and 12% were apps for managing chronic lifetime conditions. Today, mobile devices enable people to use their smartphones to inspect their eardrums, detect sleep apnoea, test haemoglobin, vital signs such as blood pressure, and oxygen concentration in the blood. This is a significant advance from the early precursor of activity tracker and step counting.

Chronic lifetime conditions
21st century healthcare in developed countries is predominantly about managing chronic lifetime illnesses such as diabetes, cancer, heart disease and respiratory conditions. These 4 diseases have high prevalence levels, relatively poor outcomes, and account for the overwhelming proportion of healthcare costs. For instance, in the US alone, almost 50% of adults (117m) suffer from a chronic lifetime condition, and 25% have multiple chronic conditions. 86% of America’s $2.7 trillion annual health care expenditures are for people with chronic health conditions. This chronic disease pattern is replicated throughout the developed world, and has significant healthcare utilization and cost implications for public and private payers, individuals, and families.
 
Healthcare providers tend not to optimally utilize data

Although personal remote devices are increasingly important in the management of chronic conditions, the data these devices create are underutilized, despite their potential for improving outcomes and reducing costs. This is partly because doctors and health providers neither have the capacity nor the resources to exploit the full potential of these data; partly because doctors tend to resist technology to improve doctor-patient interactions, and partly because remote healthcare devices have not been validated for clinical use. 

Validation
Although health professionals tend to prefer to use more expensive medical grade devices, which ensure data validity, but often drive up costs, research validating the data collected by remote self-managed devices for clinical use is beginning to emerge. In 2016 Analog Devices, a US multinational semiconductor company specializing in data conversion and signal processing technology, and LifeQa private US company with advanced bio-mathematical capabilities, announced a joint venture to establish whether data from wearable’s are accurate enough for clinical use.
 
A study published in 2017 in the journal Nature Biotechnologyprovides some validation for data derived from apps to be used clinically. Using ResearchKit, an open source framework introduced by Apple in 2015 that allows researchers and developers to create powerful apps for medical research, the 6-month study enrolled 7,600 smartphone users who completed surveys on how they used an app to manage their asthma. Researchers then compared these patient-reported data with similar data from traditional asthma research, and found that there were no significant differences. Although there still remains some methodological challenges, the findings gave scientists confidence that data derived from an app could be reliable enough for clinical research. If data from self-managed remote monitoring devices are validated, then such devices could be used to unobtrusively and cost effectively enter the daily lives of patients to collect meaningful healthcare patient data, which could be used to enhance outcomes. Early research adopters of ResearchKit include the University of Oxford, Stanford Medicine, and the Dana-Farber Cancer Institute.

 
Giant technology companies entering healthcare market
 
The increasing validation of data generated by mobile devices and the continued underutilization of such data by health providers has created an opportunity for giant global technology companies to enter the healthcare market by: (i) developing and marketing self-monitoring devices directly to consumers, (ii) collecting, integrating, storing and analysing data generated by these remote devices, and (iii) supporting research initiatives to validate data from remote devices for clinical use.
 

Apple Inc.
Just one example of giant technology companies entering the healthcare market is Apple Inc., which has a market cap of about US$1tn and 700m users worldwide. In 2017, Apple announced that it has been testing a BGM system, which pairs with the company’s existing Watch wearable. In August 2017, the US Patent and Trademark Office officially published a series of 50 newly granted patents to Apple. One covers an invention relating to health data, and more specifically to a smartphone that computes health data. 
 
The technology involves emitting light onto a user’s body part and measuring the amount of light reflected back. This data can then help to determine body fat, breathing and even emotional health. This, and other patents issued to Apple fuel rumors that the company is preparing to turn its flagship smartphone into a predominantly healthcare-focused device.

 
Takeaway
 
Given the size and momentum of technology giants entering the healthcare market, and given the powerful demographic, technological, social and economic drivers of this market, it seems reasonable to assume that in the medium term, giant technology companies are well positioned to dis-intermediate primary care doctors, and re-engineer primary care. One thing that could slow this march, is the question of privacy. Health records are as private as private gets - from alcohol or drug abuse to sexually transmitted diseases or details of abortions: things we may never want to reveal to employers, friends or even family members. Significantly, these data are permanent, and privacy at this point is non-negotiable.
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  • Healthcare systems throughout the world are in constant crisis
  • Attempts to introduce digital infrastructure to improve the quality of care, efficiency, and patient outcomes have failed
  • Modern healthcare systems were built on the idea that doctors provide healthcare with meaning and power, but this is changing
  • Advances in genetics and molecular science are rapidly eating away at doctors’ discretion and power
  • People are loosing their free will and increasingly being driven by big data strategies
  • An important new book suggests that a biotech-savvy elite will edit people's genomes and control health and healthcare with powerful algorithms, and that people will merge with computers
  • Homo sapiens will evolve into Homo Deus
 
Future healthcare shock
 
This book should be compulsory reading for everyone interested in health and healthcare, especially those grappling with strategic challenges. Homo Deus: A brief history of tomorrow, by Yuval Harari, a world bestselling author, published in 2016 is not for tacticians responding to their in-trays, but for healthcare strategists planning for the future.

The book is published a year after an OECD report concluded that NHS England is one of the worst healthcare systems in the developed world; hospitals are so short-staffed and under-equipped that people are dying needlessly. The quality of care across key health areas is “poor to mediocre”, obesity levels are “dire”, and the NHS struggles to get even the “basics” right. The UK came 21st out of 23 countries on cervical cancer survival, 20th on breast and bowel cancer survival and 19th on stroke.


Harari pulls together history, philosophy, theology, computer science and biology to produce an important and thought provoking thesis, which has significant implications for the future of health and healthcare. Homo Deus, more than the 2015 OECD Report will make you think.
 
Healthcare’s legacy systems an obstacle for change

While a large and growing universe of consumers regularly use smartphones, cloud computing, and global connectivity to provide them with efficient, high quality, 24-hour banking, education, entertainment, shopping, and dating, healthcare systems have failed to introduce digital support strategies to enhance the quality of care, increase efficiency, and improve patient outcomes.

Why?

The answer is partly due to entrenched legacy systems, and partly because digital support infrastructure is typically beyond the core mission of most healthcare systems. Devi Shetty, cardiac surgeon, founder and CEO of Narayana Health, and philanthropist, laments how digital technologies have, “penetrated every industry in the world except healthcare”, and suggests doctors and the medical community are the biggest obstaclesto change.
 
 
Doctors’ traditional raison d'être is being replaced by algorithms

Notwithstanding, modern medicine has conquered killer infectious diseases, and has successfully transformed them, “from an incomprehensible force of nature into a manageable challenge . . . For the first time in history, more people die today from old age than from infectious diseases,” says Harari.
 
Further, modern healthcare systems were built on the assumption that individual doctors provided healthcare systems with meaning and power. Doctors are free to use their superior knowledge and experience to diagnose and treat patients; their decisions can mean life or death. This endowed doctors and healthcare systems with their monopoly of power and their raison d'être. But such power and influence is receding, and rapidly being replaced by biotechnology and algorithms.

 
Healthcare systems in crisis

This radical change adds to the crisis of healthcare systems, which lack cash, and have a shrinking pool of doctors treating a large and growing number of patients, an increasing proportion of whom are presenting with complicated co-morbidities. Aging equipment in healthcare systems is neither being replaced nor updated, and additionally, there is a dearth of digital infrastructure to support patient care.
  
A symptom of this crisis is the large and increasing rates of misdiagnosis: 15% of all medical cases in developed countries are misdiagnosed, and according to The Journal of Clinical Oncology, a staggering 44% of some types of cancers are misdiagnosed, resulting in millions of people suffering unnecessarily, thousands dying needlessly, and billions of dollars being wasted. Doing more of the same will not dent this crisis.
 
Computers replacing doctors
 
As the demand for healthcare increases, healthcare costs escalate, and the supply of doctor’s decrease, so big data strategies and complex algorithms, which in seconds are capable of analysing and transforming terabytes of electronic healthcare data into clinically relevant medical opinions, are being introduced.
 
Such digital infrastructure erodes the status of doctors who no longer are expected solely to rely on their individual knowledge and experience to diagnose and treat patients. Today, doctors have access to powerful cognitive computing systems that understand, reason, learn, and do more than we ever thought possible. Such computers provide doctors almost instantaneous clinical recommendations deduced from the collective knowledge gathered from thousands of healthcare systems, billions of patient records, and millions of treatments other doctors have prescribed to people presenting similar symptoms and disease states. Unlike doctors, these computers never wear out, and can work 24-7, 365 days a year.
 
The train has left the station

One example is IBM’s Watson, which is able to read 40 million medical documents in 15 seconds, understand complex medical questions, and identify and present evidence based solutions and treatment options. Despite the resistance of doctors and the medical establishment the substitution of biotechnology and algorithms for doctors is occurring in healthcare systems throughout the world, and cannot be stopped. “The train is again pulling out of the station . . . . Those who miss it will never get a second chance”. For healthcare systems to survive and prosper in the 21st century is to understand and embrace “the powers of biotechnology and algorithms”. People and organizations that fail to do this will not survive, says Harari.
 
The impact of evolutionary science on healthcare systems

Roger Kornberg, Professor of Medicine at Stanford University who won the 2006 Nobel Prize in chemistry, "for his studies of the molecular basis of eukaryotic transcription", describes how human genome sequencing and genomics have fundamentally changed the way healthcare is organized and delivered. “Genomic sequencing enables us to identify every component of the body responsible for all life processes. In particular, it enables the identification of components, which are either defective or whose activity we may wish to edit in order to improve a medical condition,” says Kornberg.



 
The new world of ‘dataism’

Harari’s “new world” describes some of the implications of Kornberg’s discoveries, and suggests that evolutionary science is rapidly eroding doctors’ discretion and freewill, which are the foundation stones of modern healthcare systems and central to a doctors’ modus vivendi. Because evolutionary science has been programmed by millennia of development, our actions tend to be either predetermined or random. This results in the uncoupling of intelligence from consciousness and the “new world” as data-driven transformation, which Harari suggests is just beginning, and there is little chance of stopping it.
 
Over the past 50 years scientific successes have built complex networks that increasingly treat human beings as units of information, rather than individuals with free will. We have built big-data processing networks, which know our feelings better than we know them ourselves. Evolutionary science teaches us that, in one sense, we do not have the degree of free will we once thought. In fact, we are better understood as data-processing machines: algorithms. By manipulating data, scientists such as Kornberg, have demonstrated that we can exercise mastery over creation and destruction. The challenge is that other algorithms we have built and embedded in big data networks owned by organizations can manipulate data far more efficiently than we can as individuals. This is what Harari means by the “uncoupling” of intelligence and consciousness.
 
We are giving away our most valuable assets for nothing

Harari is not a technological determinist: he describes possibilities rather than make predictions. His thesis suggests that because of the dearth of leadership in the modern world, and the fact that our individual free-will is being replaced by data processors, we become dough for the Silicon Valley “Gods” to shape.
 
Just as African chiefs in the 19th Century gave away vast swathes of valuable land, rich in minerals, to imperialist businessmen such as Cecil Rhodes, for a handful of beads; so today, we are giving away our most valuable possessions  - vast amounts of personal data - to the new “Gods” of Silicon Valley: Amazon, Facebook, and Google for free. Amazon uses these data to tell us what books we like, and Facebook and Google use them to tell us which partner is best suited for us. Increasingly, big-data and powerful computers, rather than the individual opinion of doctors, drive the most important decisions we take about our health and wellbeing. Healthcare systems will cede jobs and decisions to machines and algorithms, says Harari.
 
Takeaways

For the time being, because of the entrenched legacy systems, health providers will continue to pay homage to our individuality and unique needs. However, in order to treat people effectively healthcare systems will need to “break us up into biochemical subsystems”, and permanently monitor each subgroup with powerful algorithms. Healthcare systems that do not understand and embrace this new world will perish. Only a relatively few early adopters will reap the rewards of the new technologies. The new elite will commandeer evolution with ‘intelligent’ design, edit peoples’ genomes, and eventually merge individuals with machines. Thus, according to Harari, a new elite caste of Homo sapiens will evolve into Homo Deus. In this brave new world, only the new “Gods”, with access to the ultimate source of health and wellbeing will survive, while the rest of mankind will be left behind.

Harari does not believe this new health world is inevitable, but implies that, in the absence of effective leadership, it is most likely to happen.

 
 
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Structured educational courses to help people living with diabetes manage their condition are not working.

A few closed service providers dominate diabetes education in the UK, and according to the last National Diabetes Audit, less than 2% of the 3.8 million diagnosed with diabetes attend any form of structured education.

The non-dramatic, insidious and chronic nature of diabetes masks the fact that it has become a global epidemic with the potential to overwhelm national health systems, if education can’t halt its progress.

Although advances in diabetes research are significant, the horizon for a cure is still distant. At this moment in time, the best option to halt the progression of diabetes is convenient, fast and effective education.

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