Thursday, October 22, 2015

Managing Risk in Institutional Innovation Programs

By John Mattison

Chief Medical Information Officer
Assistant Medical Director

Kaiser Permanente, SCAL

The ascent of rapid innovation is changing our culture and planet in historic proportions.  The exponential pace of innovation challenges our imagination, and it’s often a matter of how quickly we can introduce radical change.  As every institution races to create or enhance their innovation programs, there are several avoidable pitfalls. Institutions whose primary mission is operational services, such as healthcare, appear to be at higher risk of these pitfalls.  The skills and experience required for high performance are not necessarily abundant, and recruiting experienced talent is difficult. Further, existing incentive models within healthcare can clash with models better suited for rapid innovation.  This brief reports highlights common pitfalls and is not intended to be comprehensive.

Focusing On The Principles—And Pitfalls—Noted Below Can Help You To Manage the Inherent Risks in Institutional Innovation:

1)  Principle:  Focus on important problems
  • Confusion of ideation with innovation.  Generating large portfolios of ideas without aligning them with strategic priorities is hazardous.   
  • ‘Spray and Pray’ approach (aka acute and chronic pilotitis):  Assuming that a few big successes will emerge out of a plethora of innovation pilot projects is risky.  While this strategy may appear similar to early phase Venture Capital portfolios, healthcare institutions generally don’t have the variety and flexibility of capital investment vehicles available to entrepreneurs in the open market.   When many innovation projects ‘fail’ it can discourage intrapraneurs, strategic partner entrepreneurs, and the overall culture of innovation.
  • “Vision without action is a daydream. Action without vision is a nightmare." – Japanese Proverb  

2)  Principle:  Dedicate the right resources
     (People, Processes, and Technology)

  • Confusing enthusiasm for competence.  Enthusiasm is necessary but not sufficient.  Skillful support resources are critical to channel that enthusiasm.  
  • Delay in securing effective sponsorship:  Securing sponsorship can be more difficult later in the life cycle, when it is most needed.

3)  Principle:  Understand the full life cycle of innovation from ideation to scale

  • Premature death of early pilots:  Every innovation follows certain patterns during the evolutionary life cycle of iteration and enhancement, but each one also has its own unique pathway.  It is critical to recognize milestones that warrant a transition in approach or resources to progress through the next stage and eventually reach scalable solutions.
  • Underestimating the time needed for success:  Some innovations can be completed in months, but many require many years.  Recognizing when more time will help or not is critical.  As Einstein said, “Innovation is 1% inspiration and 99% perspiration”.  

4)  Principle:  Exploit platforms (especially open modular and open source):

  • Allowing innovation to occur across competing platforms is unnecessarily costly for both initial development and support.  Furthermore, downstream integration of user experience is impaired when ‘platform jumping’ is required.

5)  Principle:  Fail early, adjust, iterate, and remove ego from learning

  • Innovation is increasingly a team sport, relying on acquiring skills and resources from across the multi-platform ecosystems or ‘plecosystem’.  Teams must embrace the tension of conflicting ideas.  Celebrating success is helpful unless it focuses too much on individuals.  A focus on individual credit risks individual blame and impedes the critical pace of rapid iteration.    

6)  Principle:  Empathic design  (a user-centered design approach focused on
     the user's feelings toward a product)

  • Failure to distinguish empathic design from democratic design is dangerous.  Leadership and support is critical to avoid design by consensus.  Consensus-bound decisions often threaten the best opportunities.

7)  Principle:  Recruit key leadership with deep experience in innovation

  • Versatility in experience and leadership:  Large institutional models of promoting leaders often focus disproportionately on political skills at the expense of more basic entrepreneurial skills and track records of success. Versatility is critical in any leadership role for innovation.  Since different types of innovation require different approaches and skills, knowing what skills, resources, and processes to apply at different project stages is critical.  A single innovation success is not a sufficient predictor of versatile leaders.
  • Critical review of candidate resumes:  Key leadership must have experience across the full life cycle of multiple innovations.  Beware of resume claims of multiple successes when each success requires more time than the tenure of that individual in their role on that project.
  • Avoid the “articulate incompetent”.  The CEO of a large tech company once described this term and her series of screening and interview tools to determine whether the representations made by a candidate were justified by the evidence for those claims.  She attributed her low employee turnover rate to this thorough screening process.

8)  Exploit and spread existing internal successes

  • Overlooking existing successes is a serious hazard, and reflects both “not-invented-here” as well as competition between institutional silos.  Applying ‘positive deviance’ as a discipline will bear many fruits.

Each of the above pitfalls is compounded by the presence of any other. The most critical asset to prevent these problems is to select leaders who already have established track records of several successes over the full life cycle of ideation, prototypic iteration, operationalization, funding, and scale.  Once these uncommon skillsets are recruited, they can be effectively leveraged across the innovation infrastructure.  Avoiding these pitfalls not only saves money, but more importantly avoids lost time in a world where rapid disruptive innovations are increasingly necessary to just stay ‘in the game’.

Monday, October 19, 2015

The Future of Our Market

By Jeff Champagne
Director of Business Development
MPR Product Development Group

Astronomers say that in 4 billion years, our Milky Way galaxy will collide with the Andromeda Galaxy to produce a super galaxy. The post merger integration will take about 2 billion years.  Medtronic and Covidien should be fully integrated by then.

There are similar yet smaller collisions that are happening today in real time, right under our noses.  Massive consumer and medical technology companies are colliding every week.

So what does that mean for the future of the life science industry?

Mega deals seem to be in the news on a weekly basis.  Some of the largest medical device companies around are converging with little overlap between them. Much of the value that is being created today in the life sciences industry is a result of the convergence of technologies.  Telecommunications colliding with Rapid Diagnostics will produce real time monitoring and mediated remote treatment of patients. The miniaturization of devices, not previously possible, is happening with an increasing frequency.

Batteries that last for almost a decade are being placed inside the body to create safer and less cumbersome answers to our most challenging health problems. One example that illustrates where we are headed is the Micra, a leadless pacemaker from Medtronic, the size of a Mike and Ike® with a 9 year battery life. 

The rapid changes  and solutions that we see all around us are the result of the connecting of technologies from multiple, seemingly disparate industries.
In recent studies of the collisions that seem to spark serendipitous innovation, it’s clear there are a number of factors contributing to them. One of the largest factors is the diverse talent pool that our industry draws from. Individuals are being hired from adjacent industries because of a technical know -how but with zero previous exposure to life sciences. Talent is moving across industries with ease, full of transferable job skills and a fresh outside perspective. This collision of outside talent and new industries creates many meaningful products.

Maybe “collision” is too dramatic. As suggested in this blog post about “what happens when galaxies collide?” it is perhaps more of a merger. There is so much whitespace in our industry that it does not necessarily mean that direct competition is created as these giants of industry become closer together. Not too long ago, Medtronic and Samsung announced a joint partnership to develop future solutions for diabetes patients to better manage their disease. The product of this collaboration will create a new ecosystem for patients to learn about their condition and improve their health outcomes.

Other tech players that have jumped from Tech to MedTech have had some growing pains and you will continue to see those missteps. Qualcomm, well known in the Medical Technology world for its 2Net solution, is seeing trouble with adoption, as hardware solutions in a connected environment become increasingly obsolete. Bluetooth Low Energy has become widely adopted as an alternate way to connect devices up to the cloud, collecting patient data for eventual predictive modeling.

Because of the smaller, cheaper, faster, models that collide with the established regulatory bodies there is still a bottleneck that forms downstream in the innovation process, especially in biotech and medical device space. If we are to truly develop breakthrough products that utilize cutting edge technology, this bottleneck will have to be solved.

The FDA, USPTO and other regulatory bodies around the world are re-evaluating priorities, to help fast track key developments that can help vast patient populations. The race to develop an artificial pancreas is just one example of this special class of development that merits a fast track.

Hopefully these special cases will help the FDA to develop a new norm that leads to faster approvals and clearances. Recently, the FDA announced that a number of devices would be downclassified, from class III to class II, creating a faster pathway to clearance as there are a number of predicate devices now that satisfy their need for safety and efficacy.  This trend to break down barriers for innovation should continue.

In this picture of colliding worlds, we have a unique view of recently developed, breakthrough products in medtech, consumer, and industrial applications.  This helps us to find synergies and make connections.  For example, helping medical device companies are currently leveraging cloud computing and big data analytics to get better metrics on health outcomes.  Connecting low cost automotive sensors with wearables for on-the-go health monitoring Is another interesting pairing.  We'll see more of these gravitational attractions going forward.

Over the next few years, you will continue to see more mergers, more collaborations, more breakthrough products and a lowering of barriers for speed. It is an exciting time to be in the medtech space. Hold on tight. This is gonna be fun.

So You Want to Do a Telehealth Pilot Program…

By Nancy T. Rector and Hugh Rector
Chief Operations Officer and Chief Executive Officer

Kickstand Business Concepts, Inc.

Decisions….decisions…decisions. Telehealth is all the buzz right now. Plenty of “toys” exist in the marketplace for not only wellness & fitness but also for true medical devices. For right now, we’re going to focus on medical devices for vital sign measurement.

The Beginning

Where do you start? There are many starting points: you may have had a request by your team or you recently read that your facility outcomes could use some improvement and you want to try a tangible process to measure the possibility of real benefits. Wait--but first, what are the state and federal regulations that will affect your reimbursements? Before you consider a pilot, check the following link to familiarize yourself with your state regulations:

A Process, Not a Product

The first important aspect of a telehealth pilot requires that you remember that it is a process, not a product, and that the right team is essential to overall, sustainable success.  Then what?  You must ascertain what questions need to be asked and answered when setting up the pilot.  During this stage, the following should be thoroughly considered and analyzed:

Identify your goals. What do you want to achieve?

A few quick thoughts:

  • A process change or quality initiative to measure basic process improvements: after-hours monitoring in a skilled facility or the implementation of a new process for home monitoring for your practice or facility
  • A non-scientific study with specific measureable objectives that will be utilized to institute broader change or utilized for facility marketing purposes
  • A peer-review study with a scientific protocol for the purpose of publication in a professional journal

Pilot Team

Who will participate in the study? Who will be a part of the team? Once you have determined what pilot type is right for your type of facility, it is necessary to develop the team you wish to use. These members will need to be detail-oriented, forward-thinkers. They will need to understand the process and specifically how to develop and execute a process. Without Process and Team there is no success. This team will need to set specific goals and goal time frames; they will need to understand how to put the goals into motion and further how to continue to motivate others to assist in the implementation of the How and What, which is discussed later in this article.

Patient Population

One of the most critical aspects of the process is determining the “where?” and/or the “who?”.  Specifically, where is the desired impact and/or what patient population will be utilizing the new process? In coming to this determination, it can be broken down to a specific patient DRG (Diagnosis Related Group), a segment of facility population (e.g., wing, floor, etc.), or any other defined set of patient circumstances. Once you identify this critical aspect, it will guide you in identifying the appropriate process and equipment.

Current Process vs. New Process

Now we revisit the How and What in greater detail. How do you envision changing your current process? Understanding what you want to change and where that change will enter into the current processes is critical to understanding the specific product requirements for accomplishing your identified objectives.

Consider the following examples:

  • If your goal is RPM (Remote Patient Monitoring) only, this will impact the system you choose. Specifically, RPM won’t require 2-way HIPAA secure video.
  • If you want active patient/clinician interaction, you’ll need a video system, but not necessarily one that is built into an RPM system. 
  • If your clinician’s process is cardiac-related, the process will typically require specific devices, such as a stethoscope.

Telehealth Tools

After identifying the How and What, you’ll need to identify the specific tools required to achieve your stated objectives.  So you must ask yourself: What telehealth tools do I need for the process? You have already assembled your team, analyzed your patient population, and identified your process goals and initiatives.

Your next step? Now you must investigate the various products that you feel would be a possible fit into your program.  Sounds easy, right? Sure; until you realize you have no concrete information on the specific product or the company you’re investigating. Enter: FDA registration. During your investigation, FDA registration will come into full view. Why? Because no products utilized in these programs or processes should be utilized without the government’s approval, or without being FDA cleared or registered, unless your program is a “wellness only” program.

As there are different devices utilized to perform an array of tasks, it is important to understand what type of “clearance” will be required. For example, “Class I clearance” is required for devices that will be performing “observation only” functions, while “Class II clearance” is required for devices that will be used to assist with “clinical decisions”, or diagnoses. Each of the foregoing clearances have varying requirements. A quick review of classifications can be found at the two following FDA web links:, 

By way of illustration, if the product is a “Class I” device/product, it is imperative, or at least to your great advantage, to verify that the product was developed within “Good Manufacturing Practice” or GMP guidelines, a set of standards aimed at ensuring a controlled manufacturing process based on quality and safety.

Once the quality has been assured, you must then determine whether the functionality of the devices will work within the pre-determined parameters of the pilot. “Trial and Error” rules this aspect of the process, I’m afraid. So be sure to choose carefully and attend conferences and tradeshows such as ATA, HIMMS, and the mHealth Symposium, in order to increase your knowledge and to further network with others who are trying to accomplish the same, or similar, goals as your Team has established.

Most manufacturer-based telehealth systems will not have everything you require for your process. Don’t be afraid to use several different companies together. One of our studies in progress utilizes 3 different products for the program that run together seamlessly.

On To Pilot Execution!

Ultimately, the key aspects to success are “Process and Team.” The products you choose will be improved upon quickly by the manufacturers, and new telehealth sensors and software are introduced into the market on a routine basis. As with the weather, those telehealth tools will be ‘ever-changing” with the lightning speed advances in technology. Your success is dependent on your team, your goals, and the identified process.

What Comes After The 'Uber For Healthcare' Model?

By Reenita Das

Partner and Senior Vice President
Transformational Health

Frost & Sullivan


New model can save time and money when treating chronic care patients 

Much has been written on the “Uberization” of healthcare and the potential benefits this model could provide in terms of cost reduction, improvement in efficiency of care, and judicious use of both manpower and resources. The prevalent consensus thus far is the Uberization of healthcare will be one of the defining healthcare trends of the 21st century.

The core objective of this model is widely assumed to be the facilitation of primary care physician home visits. These home visits expect to benefit patients who are not ambulatory because of a disability or ailment. With two-thirds of the American population using a smartphone, coupled with network connectivity and high rate of Internet penetration, healthcare providers can target this large home care market. Patients can access custom apps allowing them to view doctors in the area, select a visit from a particular general physician (GP) and make an appointment.

However, use of the Uber model for primary care home visits is debatable. A survey conducted by the American Academy of Family Physicians in 2013 shows home care visits declined from 19% a week in 2010 to 13% in 2013. This trend indicates patient mobility may not play as large a role in home visits as previously thought.

Another major issue limiting Uberization of primary care is the current physician shortage in the U.S. Despite the number of primary care physicians increasing over the past five years, the number of primary care visits a year is a staggering 1 billion annually, making an average of 3,000 patient visits per physician. Conservative estimates expect the primary care physician shortage to go as high as 12,000 by 2025, with other estimates projecting a shortage of 31,000. The most acute shortages are currently seen in rural areas, with a current deficit of 4,000 primary care physicians. Only 10% of primary care physicians in the U.S. practice in rural areas, home to one-fifth of America’s population.

With an existing primary care physician shortage expected to widen over the next decade, using physicians for house calls would adversely impact time between consultations and make a poor case for smart utilization of primary care physicians.

Virtualization – Healthcare’s New White Knight?

While Uberization of primary care through use of smartphone technology does not seem viable, the same technology can be leveraged toward virtual health services. A survey conducted by the American Hospital Association two years ago shows 76% of responders prioritized access to care over the need for human contact with providers. This survey showcases strong potential for growth in virtual healthcare.

An international survey conducted in the U.S. shows only 29% of physicians indicated their practices made arrangements for ensuring after-hours care for patients, other than automated phone referral to the emergency department. Only 30% of patients in this survey described getting care on nights and weekends as “very” or “somewhat” easy.

In another national parent survey conducted by Joseph S. Zickafoose, only 47% of patients reported access to their child’s primary care office on the weekend, 23% reported access to primary care after 5 p.m., and only 13% reported access to primary care physicians via email. Creation of virtual platforms enables patients to contact primary care physicians over video calls 24 hours a day will ensure greater real-time access to physicians.

Virtual care could also reduce cost per consultation to about $40 to $50 over time and eliminate doctor visits. This would benefit insurers looking to reduce costs and improve efficiency of care provision. Primary care physicians could see more patients on a daily basis, as well as manage patients more effectively.

For example, patients who are scheduled to see physicians for regular check-ups can do so over a virtual video call, while more serious patients can visit the doctor’s office in person. This practice allows primary care physicians to allocate more time and effort on patients requiring in-person care to improve health outcomes.

This, of course, does not mean virtualization will completely replace the Uberization of healthcare. Virtualization can work with Uberization to create comprehensive patient management solutions, which will greatly benefit chronic care patients.

Virtualization and Uberization of Healthcare – A Hybrid Solution to Patient Management in the 21st Century

Chronic care management is perhaps the most critical component in the U.S. health system. Chronic diseases are on the rise and expect to kill approximately 64 million people each year in the U.S. Four-fifths of healthcare spending is driven by chronic conditions, most of which are lifestyle diseases. Chronic care requires continuous patient management as opposed to one-off surgical or medical intervention. Currently, 71% of chronic patients are managed through face-to-face meetings with primary care physicians and specialists, while 50% of chronic patients are also supported by home visits.

To facilitate efficient patient management, it is essential to monitor patient health in real time and share this information along the care continuum. While wearable technology is currently used to monitor and share a range of health parameters such as blood pressure, heart rate, oxygen saturation, etc., without requiring a doctor or caregiver to be physically present, monitoring for some chronic conditions will require high-end imaging solutions.

In such a scenario, Uberization of health can create an extension model of care provision. In this model, specially trained diagnosticians can partner with ride-sharing services to bring portable imaging services to the patient’s home. Portable ultrasound, MRI and CT devices can be leveraged to improve efficiency of diagnosis, with results transmitted via encrypted networks to doctors and patients post-analysis. Doctors can then make an appointment with the patient either in person or virtually, based on the results.

The Tricoder – From Star Trek to Med Tech

For fans of the Star Trek series, the Tricoder needs no introduction. For the uninitiated, the Tricoder is a handheld device used to record, store and analyze data. To this end, there has been interest in creating a medical Tricoder allowing patients to self-diagnose, store and analyze health data. While there has been resistance to the idea of patient self-diagnosis, including from the FDA, there is tremendous potential for medical Tricoder adoption among care providers.

Care providers can work with device firms to create Tricoders that capture multiple parameters of health data and store for later analysis. Diagnosticians can partner with ride-sharing services to reach patients who are unable to visit the diagnostic lab. Tricoders can be used to record health data not already captured by wearable technology. Data on these devices can then be transmitted to cloud-based servers for analysis and then to the doctor.


Virtualization of health has and will continue to revolutionize the way care is provided. However, physical human presence will remain the backbone of the care provision spectrum. To this end, Uberization will have a huge role in connecting caregivers and patients outside of doctor’s offices, hospitals and diagnostic labs.

With a shift in focus from intervention to patient management, aggressive monitoring without putting a strain on already limited resources and manpower is necessary. To achieve this goal of aggressive monitoring, it is essential caregivers utilize both virtualization and Uberization to create hybrid solutions to meet current and future demand.

This article was written with contribution from Sowmya Rajagopalan, Research Manager with Frost & Sullivan’s Transformation Health Program.

Wednesday, July 15, 2015

Healthwear – Beyond Bracelets and Watches

By Bhargav Rajan
Senior Research Analyst
Healthcare Division, Technical Insights

Frost & Sullivan

When Norman J Holter developed the world’s first ambulatory cardiac monitor, and arguably the world’s first wearable device, it weighed 85 pounds and it had to be worn like a backpack. Since the modern transistor had not been invented then, the electrical data that the device picked up from the patient’s heart had to be transmitted through radio signals. For the very first time, a patient’s electrophysiological activity was recorded while he was mobile, although Holter himself noted that the form factor of his revolutionary device was “not practical”. By the end of his lifetime, he had successfully managed to shrink the device to the size of a briefcase.

Even a visionary such as Holter, who dreamt of a device that would measure cardiac activity on “skiers, parachute jumpers and runners”, would be surprised to find today’s explosive growth and rapid innovations in the field of wearable devices.

The Plateau

Yet, in spite of the pace of innovations, it appears that the field of wearable devices has hit a plateau in the technology adoption cycle. The effusive reception that smart watches and wristbands were welcomed with a few years ago, has been replaced by a bit of a disappointment with their capabilities. Every product launch is preceded with great anticipation and is met with grumbling acceptance of the new product’s incremental improvements. Nearly all forms of wearable devices – wristbands, watches and glasses – have been touted as the “next big thing” in consumer electronics, only to settle down in public memory as a “work in progress”.

A major reason for this adoption plateau is that the current crop of wearable devices does very little other than track physical activity. In other words, wearable devices have become synonymous in the minds of the users - and perhaps developers as well - with activity trackers. Wearables are indeed a great tool for tracking physical activity (FitBit,  Misfit, Moov) and sleep patterns (Pebble, Jawbone), but it would be a great travesty if they end up doing just that. Beyond fitness tracking is an ocean of medical and wellness applications for wearable devices that is yet to be explored.

We have identified emerging and future healthcare applications of next-generation wearable devices, Wearables 3.0, classified under diagnostics, monitoring and therapeutics. The delineation between monitoring and diagnostics is a thin line in the case of wearables. Diagnostic wearables are used to confirm the presence of a particular health condition, an erratic heart rhythm, or brain signals indicative of seizures. Wearable devices used for monitoring measure and store physiological data continuously, usually to gauge the progress of a treatment. Therapeutic wearable devices refer to their use in the treatment of clinical conditions.

Wearables 3.0

Wearable devices are built on a simple technological foundation – record physiological data and use them to monitor the overall well-being of the user. So why limit to just measuring electrophysiological data from the wrist to calculate pulse, or use the gyroscope to measure the steps taken in a day?

Health Diagnostics and Wellness Monitoring

EEG Headsets

A particularly interesting wearable device that is on the cusp of mass adoption is the wearable EEG device. No less than a dozen companies (Emotiv Lifesciences, Neurosky, Interaxon, Advanced Brain Monitoring, Thync to name a few) are developing lightweight, wireless and portable EEG headsets. Designed as simple headbands or helmets, these devices can record the brain activity and wirelessly transmit the readings to a paired phone or a computer. In a manner of functioning, portable EEG headsets work the same way as heart monitors and wrist bands. Continuous monitoring of brain activity can of course provide information about the quality of sleep, but beyond that, it can warn of impending seizures, give insights into mood swings, cognition and emotional states of the user. Given the growing awareness of mental health, wearable brain activity monitors can play an important role in the years to come. Wearable EEG headsets are the foundation on which the promising and much-researched field of brain-computer interfaces rests on.


Around 2013, just as critics were panning the Google Glass for being “gimmicky”, news tricked out that Google was developing a far more cutting-edge wearable eye device - a smart contact lens or an electronic lens. The lens was supposed to be lined with electronic sensors that could measure the level of glucose in the wearer’s tears and transmit it to a receiver nearby. In rapid succession, companies such as Sensimed and Johnson and Johnson and a host of university research groups revealed that they too were working on electronic lenses. Electronic contact lenses are very much in the prototype stage, and make take a few years to enter the market, but their potential is undeniable. From monitoring glucose levels without drawing blood, measuring the intra-ocular pressure, perform routine eye tests and augment vision, their applications are myriad, based only on the sensors that form the lens architecture.

Smart Fabrics

One of the disappointments with the current generation of wearable devices is that they are bulky, conspicuous by their design and positioning, and not always fashionable. The most intuitive solution to these concerns is of course to completely integrate the electronics and sensing capabilities into the wearer’s fabric. Enter smart fabrics. Smart fabrics are a class of textiles that can, among other functions, communicate, monitor, transform and even conduct energy. The variety of players who are investing in and actively researching the smart fabrics landscape is staggering and speaks to the potential of the technology. Sportswear experts such as Nike and Adidas, sensor companies such as BeBop Sensors and clothing companies such as AiQ Smart Clothing, Levis and many more along the technology chain are working on intelligent, interactive and functional fabrics.   


Perhaps the ultimate form of technology integration would be to have the wearable devices embedded on to the skin of the user – sort of an electronic tattoo. Firmly in the realm of academic research, these “devices” are actually stretchable skin-like material with electronic Okcircuits and sensors printed on them. These “tattoos” can sense electromyographic signals, measure blood toxicity levels, pick up the precise electrical data from the heart or brain, accurately measure core body temperature and so on. Aided in no small due to the rapid innovations in flexible electronics and ultrathin sensor systems, these skin-hugging wearables may be the final destination that began with an 80-pound wearable device.


Drug Pumps

A truly niche wearable medical device would be wearable drug injectors, or pumps. As the name suggests, these are body-worn cartridges or reservoirs of essential drugs – monoclonal antibodies, immunoglobulins, biologics and so on – drugs that cannot be administered orally due to pharmacokinetic complications. An effective, and automated, method of delivering medications would be body-worn devices that would subcutaneously deliver medications at pre-set quantities and at the appropriate time. Such wearable devices would greatly benefit patients on chronic medications, such as insulin, and patients with a propensity to forget medications ensuring compliance to prescribed medication. Already companies such Amgen MedImmune and Unilife have wearable drug injectors. Given the wearable injectors are in the interest of the multi-billion dollar biologics market, this class of wearable devices are also likely to be an area to watch out for in the near future. 


Electrical stimulation of the brain and the peripheral nervous system has been a clinical practice for several decades now. This involves the use of wired electrodes supplying mild electrical impulses to manage pain, restore hearing, manage and control seizures, tremors and so on. With the advent of wearables, neurostimulation can be made available as over-the-counter use, outside the clinical setting. Belgium-based Cefaly Technology has developed portable headbands that supply micro-impulses that stimulate the trigeminal nerve, as a way of compensating for electrical activity that leads to migraine headaches. Massachusetts-based NeuroMetrix has two wearable products that are designed to provide non-invasive neurostimulation to provide relief from chronic pain caused due to diabetes, sciatica, fibromyalgia, and other conditions.

Enabling Technologies

Throughout the year, Technical Insights, the technology consulting arm of Frost & Sullivan, identifies and profiles innovations in various industries, keeping our finger on the pulse of the global innovation landscape. Of the hundreds of technologies, products and platforms that we write about, we identify 50 technologies that we believe will make a big impact in the following year. When we did this exercise earlier this year, we noticed that no fewer than 10 technologies that made it to our top 50 list were directly driving innovations in wearable devices. Technical Insights’ TechVision 2015 identifies and provides a multi-dimensional profile of technologies such as flexible electronics, smart sensors, smart fabrics, lightweight composites, sensor fusion, cloud computing, neuroprosthetics and brain-computer interface, each of which are key to the burgeoning field of wearable devices.

Beyond Quantified Self

Earlier in the article, I mentioned that the term wearable devices have come to be associated with activity tracking. The plethora of technologies that were subsequently described throws light on the possibilities beyond quantified self. Wearable devices are certain to change the nature of fitness, health monitoring and drug delivery. But even these do not describe the picture in its entirety.
Every aspect of healthcare – surgery, medical imaging, wound care, diagnostics, health informatics, population health management – stands to be benefitted by wearable devices. It would not be an exaggeration to view wearable healthcare devices, or healthwear, as the single biggest enabler of personalized healthcare delivery.

Bhargav Rajan is a Senior Research Analyst working with the Healthcare Division of Technical Insights, Frost & Sullivan. He tracks innovations in medical devices, medical imaging, clinical diagnostics and healthcare practices. Bhargav holds a Master’s degree in Biomedical Engineering from the University of Florida, Gainesville, and has academic and industry experience in regenerative medicine and tissue engineering. He can be reached at  

TechVision is the flagship research service of Technical Insights. The TechVision program profiles and analyzes the growth dynamics of 50 cutting-edge technologies. To know more about these technologies, how they converge with each other and how you can use this information to your growth advantage on our website.

Look for Bhargav Rajan and other Frost & Sullivan Analysts at our next
Medical Technologies 2016: A Frost & Sullivan Executive MindXchange event.

Tuesday, July 14, 2015

Facilitating Drug Development:
Optimizing the Person-Provider Encounter

By Frederick A. Curro, D.M.D. Ph.D.
Director, PEARL Clinical Translational Network
Clinical Professor, New York University

The Affordable Care Act (ACA) has broadened the responsibility of health and healthcare to include the person as well as when they become a patient. It has also widened the perspective on how we view health and healthcare recognizing that they are dependent variables where the outcome of one affects the outcome of the other. It can be viewed as a continuum where the person may experience becoming a patient many times in the course of their life but for the most part their health would be dependent upon what they do as a person.

This movement from healthcare to health and away from disease management has the person becoming an active participant in the outcome of their own healthcare. This concept of shared responsibility has the patient responsible for their compliance to both their health and healthcare. Medications can no longer be a substitute for a lifestyle that brought on the condition without the patient becoming more aware of lifestyle changes to possibly avoid the condition in the first place. The ACA has caused the present healthcare system to be introspective. Considering what the fixed variables would be in a new healthcare paradigm the person/patient encounter is the single most important aspect that one can consider to be a starting point. Other aspects of health and healthcare such as cost of drugs and drug development can be affected by this encounter if they are considered as dependent variables in an integrated system. 

Integrating the principles of clinical research with clinical practice to conduct person-centric clinical trials is one way of optimizing the person/patient encounter for an integrated system. Such a system can reduce drug development costs, facilitate the dissemination of current information to optimize clinical practice by closing the scientific gap from bench to practice, and provide an infrastructure for quality assured data that can be used for decision making purposes and incorporated in the “big data” concept.

Raising the person/patient/provider from an observational encounter to the level of a quality assured data point translates the medical encounter to a usable data point for best practice, submission to regulatory agencies for phase III and IV clinical studies, and creates an audit trail for both the provider and person/patient. It also provides a means for transparency and health care literacy. The audit trail for the provider can be used to lessen multiple claims that contribute to cost increases and fraudulent claims. The audit trail for the person keeps the person/patient informed to maintain a level of continued compliance to reduce further complications and/or to increase the treatment outcomes.

The missing component from many health care programs is an infrastructure that connects patients/persons with providers and third party payers. All of these moving parts should be in sync to optimize the efficiency of the system. Point-of-care quality assured data can lower the developmental costs for pharmaceutical companies to conduct clinical studies, provide meaningful patients that would be on the medication with a known medical history. Patients would be informed for their assessment and input, and side effects would be more interpretable to providers reporting the effects of the medication as the patient’s medical history would be transparent. In addition, patient compliance on the use of the medication would be improved as they have a vested interest under the concept of person/patient-centered care, recruitment costs to a study would be reduced to a minimum, and the data generated by the providers would be more readily accepted by the profession at large. 

Improving the person/patient encounter to a quality assured data point reduces the intensity and costs of oversight and the data can be cross referenced by many of the healthcare partners. This model proposes to integrate many of the steps in health and healthcare that are currently discrete and make them continuous and dependent upon each other so that the system is optimized and readily utilizable by the profession and the person/patient. The process would contribute to lessening the scientific gap by facilitating information transfer to the practitioners. 

Frederick A. Curro, D.M.D., Ph.D.

Frederick A. Curro is currently a Clinical Professor at New York University where, under the auspices of an NIH grant he and two colleagues built and directed “Practitioners Engaged in Applied Research & Learning” (PEARL) a Practice Based Translational Network. PEARL conducts person-centric clinical trials to improve health and healthcare delivery and conducts comparative effectiveness clinical studies for best practice.

Curro’s pharmaceutical career has included positions as Vice President of GlaxoSmithKline; Corporate Vice President of Clinical, Medical & Regulatory Affairs at the Block Drug Co. Inc.; Head of Reed & Carnrick Pharmaceutical, a division of Block Drug; and Executive Director of Clinical Operations & Research at Transkaryotic Therapies (TKT) Inc. of Cambridge, MA.

Curro was also a former Professor and Chairman, Department of Pharmacology at Fairleigh Dickinson University and has held faculty positions at the University of Texas at Houston and SUNY/Buffalo. His clinical expertise is in pain management.

Building Engagement Through Analytics

By Shawn Miller
Director of Market Analytics
Philips Healthcare North America

Let’s help our Medical Device organizations build engagement through powerful analytics.   In other words, let’s not just provide data, but rather, help drive action planning to improve top line performance.  But how do we do that? 
First – let us define and use a common terminology:

Analytics – industry data and market intelligence related to market size, trends, growth, market share, win/loss, “visibility” (percentage of deals your sales team sees), competitive analysis and related information
Engagement – understanding and action based on the data
You want your clients to be engaged in your output – your clients or stakeholders being senior management including marketing and sales leadership and the sales organization down to the individual Account Manager.

Building engagement
Here are some things I have learned to build engagement:

  1. It’s like playing golf.  You need to keep score, you need immediate feedback and you need to provide your organization with a good scorecard.    Examples would be providing quarterly market size and share data, providing quarterly win/loss and visibility metrics, customer satisfaction data, etc.
  2. Don’t “high 5” too early.  Have a great quarter?  I would argue the bigger question is, “how did you do bumped up against the market?”  That is, if you grew 5% in a particular segment, and the market grew 10%, you lost.  You lost market share.  You may have “high 5’d” each other for a great quarter that met plan, but you lost to your competitors.  So include in your analysis, not just company performance, but company performance compared to market performance.   This is hard to do in practice because sometimes the data just isn’t available.  More on that below.  And this analysis should be provided at regular intervals; I recommend quarterly.
  3. Execute.  I have seen a lot of people over-promise and under-deliver when it comes to providing data and analytics.  For example, we have been promising “dashboards” to the field sales organization for several years but have not yet been able to provide a workable solution.  This sounds simple, but I’m more convinced than ever that execution, doing what you say you will do, is a skill and an art that less and less people have.     You’ve heard the adage, “Under promise, over deliver”.  This is true with analytics.  Promise something you can’t deliver and you and your team will lose credibility.
  4. Don’t say “No” twice.  You can say it once – “No, I don’t have that information now”.  Or no I can’t figure it out.  I once had a manager say, “figure it out, or I’ll find someone who can” (he eventually tried with an outside consultant and the consultant failed).  But the point is valid – say no…once…that’s OK, but caveat it with “I’ll figure it out”.   Find the data.  If you don’t have the data, put together a budget, an RFP and do the research.  If that won’t work, which is often the case for market sizing efforts, figure out a way to model or forecast it.
  5. Go to Vegas.  If you don’t know the answer, model it.  There are great skills to be learned in Vegas.  Poker and black jack are about estimating, and making educating judgments and betting based on the odds and your likelihood of winning.  This isn’t much different from estimating in business and building robust models based on outcome probabilities.  My Dad taught me poker and chess, and there are embedded life lessons and skills I use every day in building market models and planning.
  6. Discuss it, don’t just send it.  Email is not a great forum for sharing complex data.  Even simple data can be often misinterpreted because it is read quickly and often not understood in context.  It’s OK to send it out initially, but setup a meeting to discuss it, especially if it is new data or new analysis.  It will take more time on your part, but there is tremendous value in the discussion
Following these straightforward guidelines will make a dramatic difference in the credibility and usefulness of our analytics and market intelligence functions.  So go ahead, play some golf, gamble in Vegas and learn not to say “No” and then apply these skills to your analytics and see what amazing things happen!

Shawn Miller is the Director of Market Analytics at Philips Healthcare.   Shawn has held a variety of positions in Marketing, Sales, Market Analytics, Market Intelligence and IT.  He doesn’t play golf, but he does play chess, poker, likes betting on horses, build models and gives lots of “high 5’s” when company performance exceeds market performance.