It’s Transformers season, as we like to call it here at MM&M. That means we opened up nominations for the 2017 class of Top 40 Healthcare Transformers. We also asked past Healthcare Transformers honorees, as well as the winners of the Shark Tank competitions at the 2015 and 2016 MM&M Transforming Healthcare conference, to share their picks for health-tech trends to watch during the year ahead. 



As more hospitals merge and consolidate into health systems and share EHRs, very different medical staffs need to come together to agree on things like formularies and clinical decision support. When each hospital had its own EHR, it could decide these things for itself. Now, the linking of computers is beginning to force a degree of systemness and standardization that will challenge many multisite organizations.

The trend I’m watching is the rising billions — new healthcare market opportunities in emerging markets with billions of new customers and significantly different business and care delivery models. Even though the U.S. is the biggest healthcare market in the world — spending about $3 trillion a year — there’s a much bigger global opportunity as billions of new customers enter the healthcare market.

New infrastructure, including the ubiquity of mobile phones and increasing internet access and banking mechanisms, is paving the way for access to new affordable care and delivery models in places such as Asia and Africa.

Unencumbered by legacy infrastructure and regulatory complexities, emerging markets may become a hotbed for health innovation, experimentation, and leap-forward technologies and business models.

 


You know that feeling when you see someone who is struggling physically or emotionally and you want to be able to reach out and help because you’ve been there before and wished that someone had done the same for you? I’m no anthropologist, but it feels to me this powerful empathetic response must have developed from our underlying needs for community and acceptance.

Unfortunately, for anyone who has spent time looking at social media, comment sections, and forums or chat rooms, community and acceptance can be a mixed bag. As a result, we will see patients moving toward highly curated, personalized, and humanized online experiences to ensure each patient is getting the right information from knowledgeable and trusted sources, not just anyone with a keyboard.

In Web 1.0, patients flocked to the internet because they could find information that helped balance the asymmetric patient-physician relationship in ways that benefited both parties. Empowered patients could research their symptoms and pore over peer-reviewed, published materials to share with their physicians, while doctors could benefit from interacting with connected patients and easily searchable medical information to begin this journey into connected medicine.

In Web 2.0, social networks changed the way information was created, categorized, and discovered. As a result, patients were able to connect with each other at incredible scale with specialized communities for any given disease. Every patient had the ability to create an online persona in order to share his story and experiences with multitudes of other patients from around the world. The empowered and connected patient had more information at his or her fingertips than had ever been possible. That rush of information was followed immediately by the aftershock of not being able to parse it effectively.

As we move into Web 3.0 — the world of connective and predictive intelligence — patients will no longer seek out all the information on their condition; they will look for just the right information, personalized to their situation. Patients need to be able to trust the information is credible and accurate. And while a part of the next wave will be highly technical, the complementary part will be highly human. They will want to engage with healthcare professionals in more frequent, yet shorter interactions, balancing the technical with the personable.

To this end, the biggest opportunities for pharma, hospital systems, physicians, and payers will stem from embracing technologies enabling scalable, personal interactions in either one-on-one or one-on-many situations.

These technologies will help supplement video, live chat, messaging, and screen sharing with empathetic, trained professionals, easily consumed visualized data, and frequent interactions designed to provide all patients with just the right information when they really need it.

Photo credit: Erica Berger

One trend I see gaining momentum this year is using advanced analytics for patient insights, trends, and solutions. It’s all about the data and leveraging the new data available for delivering measurable improvements to medication adherence — and, ultimately, health outcomes.

As an example, in the diabetes space we see an exciting opportunity for organizations — such as Google, IBM Watson, and sensor makers — to capture blood-glucose and adherence information from patients and proactively use this data to alert a patient when they might hit a low based on their historical trends.

 

 

The one trend I’d like to note is the emergence of AI as a mechanism of risk stratification. A good example of this is chatbots, which can be used to engage patients, risk-stratify them appropriately, and intervene when necessary. There are a bunch of companies in this space. A good example is Patient IO, which was recently acquired by Athenahealth.

At the Shark Tank segment during the first MM&M Healthcare Transformers event in April 2015, I pitched 3D printing as the next big thing in healthcare. I lost.

Maybe it was because the other trends identified seemed more familiar, or maybe it was because there weren’t enough compelling examples yet — even though custom-fit Invisalign braces and individually printed, low-cost arm casts were becoming widespread. At the time, it was difficult to help others see how 3D printing might directly impact the biopharmaceuticals industry.

Nearly two years later, the application of 3D printing in healthcare has evolved. Also known as additive manufacturing, 3D printing has been around since 1984. However, designers, hackers, and companies really began to take notice in the past few years as the cost of printers and source materials dropped.

What hasn’t become mainstream is ownership of a high-quality 3D printer by every man, woman, and child as originally predicted. Indeed, many manufacturers have scaled back on their consumer models. Instead, companies, labs, schools, DIY shops, and even creative agencies have built workspaces, programs, and offerings around 3D printing to better spread the investment across teams and departments.

MarketsandMarkets, a research firm, forecasts the use of 3D printing for medical applications could surpass $2 billion by 2020. While the spotlight has been on other developments in technology and medicine, 3D printing has steadily made inroads into bioprinting, prosthesis manufacturing, customized medical implants, and pill design and manufacturing.

Bioprinting: Bioprinting artificially constructs living tissue by outputting layer upon layer of living cells, and 3D-printed skin for burn victims and airway splints for babies with tracheobronchomalacia are now widely available. Costs will likely fall as demand increases for government subsidy programs and medical bioprinting research grants. In March 2016, the Harvard Business Review predicted “as surgeries with exterior prosthe-
tics prove successful, possibilities such as 3D-printed livers, kidneys, and lungs could become a reality, cutting through long donor lines
to save lives.”

Prosthesis manufacturing: Simple and tech-enabled prosthetics to replace or augment damaged or missing body parts have been around for a long time. However, 3D scanning and printing have recently lowered their cost, decreased wait times, and increased the customization and fit of prosthetics for both humans and animals. Also, 3D printing has enabled companies such as Prosthetic Ink to help patients express themselves using chrome, wood, tattoos, and other alterations to their custom prosthetics.

Customized medical implants: Combining mass customization with 3D printing enables mass production of customized medical devices — dental implants, prescription glasses, and hearing aids. With more complex, custom-made items such as bones and spinal implants, surgeons can reduce operating times, lower risks from errors or complications, and produce better outcomes. Doctors can also improve accuracy and understanding of anatomical areas and use them to communicate with patients.

Pill design and manufacturing: In 2015, the FDA approved the first 3D-printed medicine, Spritam (levetiracetam), a tablet that rapidly disintegrates upon contact with liquid. In general, 3D printing enables new pill shapes and coatings that not only help to brand and differentiate, but may also change bioavailability and alter a drug’s release rates. Medical writer C. Lee Ventola believes “personalized, 3D-printed medications may serve particularly well for patients who respond to the same drugs in different ways.”

The technology has the promise to deliver a new type of personalized healthcare, one in which precise digital designs are customized and printed at the point of need. These core designs can be distributed and reused many times at low cost, provided intellectual property rights are clear and enforceable. As an additive process, 3D printing reduces the waste of materials, including expensive metals, designer polymers, and human tissues.

At a time when baby boomers are putting more pressure on the U.S. healthcare system, 3D printing may help reduce the cost of care while bettering health outcomes.

The one trend I’d like to note is the emergence of AI as a mechanism of risk stratification. A good example of this is chatbots, which can be used to engage patients, risk-stratify them appropriately, and intervene when necessary. There are a bunch of companies in this space. A good example is Patient IO, which was recently acquired by Athenahealth.

The one trend I’d like to note is the emergence of AI as a mechanism of risk stratification. A good example of this is chatbots, which can be used to engage patients, risk-stratify them appropriately, and intervene when necessary. There are a bunch of companies in this space. A good example is Patient IO, which was recently acquired by Athenahealth.

The one trend I’d like to note is the emergence of AI as a mechanism of risk stratification. A good example of this is chatbots, which can be used to engage patients, risk-stratify them appropriately, and intervene when necessary. There are a bunch of companies in this space. A good example is Patient IO, which was recently acquired by Athenahealth.