Transforming Medicine


The last two posts focused on disruptive scenarios driven by the future introduction of autonomous vehicles. However, the context for viewing disruptive potential must be broad – not just one possible scenario. With that in mind, let’s take a look at the Healthcare industry with a broader lens. The authors (Chunka Mui and Paul Carroll) of The New Killer Apps do a masterful job of doing just that. They make a rather bold statement in a chapter dedicated to the Healthcare industry – specifically: 

“Without a course correction, hospitals will lose their central place in medicine and many will disappear.”

Strong maybe, but not hype. The risk is real and not limited to Healthcare. The visual below is a great representation of the law of disruption. The progression of technology is riding an exponential curve. With this acceleration comes a progression of disruption where incremental business change can no longer keep pace. Disruption and the need for transformative actions occur when this scenario takes hold, and the enterprise has not taken steps to respond. A failure to respond in this fast paced, change oriented world is likely catastrophic, but the opening for killer apps depicted in the visual presents both risk and tremendous market opportunity.

The Law of Disruption

The Law of Disruption (source: Unleashing the Killer App)

How do companies respond? A good road map is outlined in the previously mentioned book, where the authors focus on the need for large companies to out innovate start-ups. They wisely advise companies to understand the technology road map that may threaten key revenue streams in the future. Let’s take a look at some perspective in the context of Healthcare. In a related Forbes Article, Chunka Mui states: “making care convenient, universally available and efficient through technological innovation is seen as more promising around the world than increasing the number of physicians or funding more academic research.” These sentiments – and other supporting Research by Intel should signal to health care leaders everywhere that massive disruption to the health care system is not only possible, but supported.

One major area of technological innovation is presented in this article on Personalized Medicine, where two trends are used to describe its possible impact. First, this year, over 580,000 Americans – 1,600 people per day – are expected to die of cancer. Second, one in twenty babies born in the United States is admitted to the neonatal intensive care unit (NICU), and 20 percent of infant deaths are a result of congenital or chromosomal defects. Both of these trends can be fixed with the rise of personalized medicine.

The interpretation of the human genome has the potential to transform medicine – and advances are coming rapidly. As described in The Second Machine Age, three forces (Exponential, Digital, and Combinatorial) are enabling the coming transformative period, and they are driving rapid acceleration in realizing this human genome potential. Processing power is doubling rapidly, and decreasing costs along with increasing speeds have genome applications exploding. DNA sequencing advances are making it easier to discover links between DNA sequence variations and human disease. We’re at an inflection point – and according to Narges Bani Asadi – author of the article referenced above, technological and medical advances are still needed to realize the vision of personalized medicine:

  • Ultrafast, accurate, and low-cost DNA sequencing
  • Rapid, low-cost, and accurate secondary analysis
  • Injecting genetic information into medical care
  • Getting the big guys to pay for it

Is the world ready for the transformation of medicine?  The previously mentioned Research by Intel provides some perspective. The research concludes:

“Most people appear to embrace a future of healthcare that allows them to get care outside hospital walls, lets them anonymously share their information for better outcomes, and personalizes care all the way down to an individual’s specific genetic makeup.”

Eric Dishman, Intel fellow and general manager of the company’s Health and Life Sciences Group believes that “Care must occur at home as the default model, not in a hospital or clinic. New technologies can bring decision support, health monitoring and health coaches into the home.” Additional Findings from the study include:

  • What people want most is more personalized care based on their own behaviors and biology, enabling the freedom to get healthcare wherever and whenever it’s convenient
  • More than 70 percent of respondents are receptive to using toilet sensors, prescription bottle sensors, or swallowed monitors to collect personal health data.
  • Sixty-six percent prefer a personalized healthcare regimen designed specifically for them based on their genetic profile or biology
  • 53 percent said they would trust a test they personally administered as much or more than if it came from a doctor. Almost half of respondents (43 percent) globally would trust themselves to monitor their own blood pressure and other basic vitals
  • When given a choice between getting the same care as others who have their symptoms or getting care based on their own genetic profile, two in three respondents choose customized care
  • A higher percentage of people said they are more willing to share their health records (47 percent) than their phone records (38 percent) or banking information (30 percent) to aid innovation
  • Fifty-seven percent believe traditional hospitals will be obsolete in the future and technology innovation holds the promise of unburdening people from having to see a healthcare provider in person for many aspects of their healthcare management
  • Half of those surveyed would trust a diagnosis delivered via video conference from their doctor
  • Seventy-two percent are receptive to communication technologies that allow them to remotely connect to their doctor
  • The innovation least likely to be incorporated by the global population is a robot performing surgery

Technology advances are on a course to make remote healthcare and self-monitoring viable. As this materializes, people can connect with caregivers in new ways, such as sensor technology that transmits health data in real time. In addition, social networks and video conferencing help people embrace new behaviors – a medical system of engagement if you will. These developments could change the world of medicine, and regulations like Obamacare could have dramatic consequences. For a number of reasons these changes will likely take years to materialize, but they are transformative drivers nonetheless. Keeping in line with my previous posts, let’s examine both the challenges and possible impacts to the ecosystem, as well as the possible responses. First the impact and challenges:

  • Healthcare today is hampered by complicated and inefficient hospitals, rising healthcare costs, and increased complexity of care due to demographic changes like aging population, and obesity
  • Future business models could be disrupted by a system shift to reward prevention versus treatment
  • Smartphones carrying medical Apps could have profound implications on hospitals
  • U.S. Hospitals could lose more than two million emergency room patients and 220,000 overnight hospitalization stays per year – as car related injuries plummet
  • Pursuing specialization strategies, competitors move to grab the most profitable treatments. Procedures like hip surgery move to facilities that specialize in certain types of elective surgery, delivering better results at less expense
  • Smaller and more affordable diagnostic machines could move downstream into doctor’s offices, clinics, and homes. Combined with telemedicine – enabled by mobile devices, cameras, and sensors – various diagnoses and care can be provided without the need for a hospital
  • Medical expense transparency enabled by emergent knowledge may have a profound effect on the healthcare ecosystem
  • $30 billion revenue loss due to the reduction in unnecessary U.S. hospitalization. Algorithms that spot patients heading towards hospitalization enable proactive action that mitigates the need for hospital visits
  • $300 billion revenue loss due to the reduction in ineffective or dangerous use of prescription drugs in the United States. Using predictions based on genetic information, algorithms in the future prevent this ineffective or dangerous use
  • Revenue loss due to better informed patients pushing back on treatment. Access to previously inaccessible knowledge enables patients to make informed decisions
  • A major competitive threat emerges as an insight broker with control of patient data enters the space to seize control
  • A data versus symptoms approach revolutionizes medicine 

Responding to these and other challenges is growing increasingly difficult as the pace of change accelerates. I have long believed that the ability to continually Sense and Respond to stimuli in the environment is critical to both short term success and long term strategy. I will repeat this thinking here:

Strategy is now an iterative process driven by ongoing scenario analysis and constantly informed by real time insight. Insight is not the byproduct of traditional rear view mirror reporting, but the result of on-going forward looking analysis that leverages the growing volume of data for its insight. The successful company is an emergent company that continually looks across a growing ecosystem to enable this scenario analysis. It embraces an experimental mindset that allows for the rapid advancement of ideas to inform strategy. Through this process, possible responses to disruptive threats can be formulated. 

With this in mind, using several of the sources referenced in this post, here is a possible list of ecosystem response to these potential threats:

  • Geoffrey Moore, famous author of “Crossing the Chasm”, has often talked about specialization. His advice to focus on the core and outsource the context comes into play in one possible Hospital response. Using this approach, the new hospital core becomes facilities for emergency rooms, operating rooms, intensive care, and maternity wards – as the rest becomes the core for specialized service providers within the ecosystem
  • In response to emerging threats, new business models arise that pay for prevention not cure. In this scenario, Hospitals could provide alternative services like preventative care
  • Hospitals lead the efforts to digitize the human, while becoming an App provider for various medical use cases
  • Healthcare ecosystem participants embrace an aggressive consolidation strategy that acquires physician practices, hospitals, imaging facilities, labs, extended care facilities, and others
  • Healthcare ecosystem participants embrace an insight broker strategy that controls all patient data and related insights. This positions the entity as the hub for new information flows. Value creation comes in many forms such as: using algorithms to identify at risk patients and proactively recommend treatment, or using genetic information to predict drug effectiveness
  • Hospitals move to the forefront of remote medicine design and become hubs for remote diagnosis and treatment
  • Hospitals introduce and invest in new models to deal with increasing demand and complexity of care

One of the questions I get most often goes back to the notion of sense and respond. How do leaders pursue appropriate responses – or for that matter a technology road map – when everything moves so fast. In the previously referenced book The New Killer Apps, the authors talk specifically about approaches that some in the healthcare industry are using to tackle this issue. Examples include experiments with IBM Watson, setting up digital medicine centers focused on health and prevention, and experimenting with Telemedicine. At the heart of all these approaches, lies a set of Characteristics that every leader should strive to emulate. Staying close to the stimuli in the environment, rapid analysis, experimentation, iteration, failing fast, and overcoming paralysis are just some of the characteristics that enable the determination of effective responses.

I’ll focus on another disruptive scenario in my next post.

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