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Disruption in Healthcare Innovation – What’s Trending

Published on - June 2017
Author - Rama Chandra Dash, Program Director, IBM Watson Health

Disruptive Innovation”- the inherent dichotomy in the phrase is what makes this phenomenon both exciting and disconcerting at the same time.

By its very nature, disruptive innovation “doesn’t fit” within our typical way of doing things and thus creates crisis. When business faces disruptive innovation, it forces organizations onto a “survive or die” pathway where they must scramble to either mimic that innovation or compete with it.

Healthcare and Disruptive Innovation

The healthcare industry is increasingly becoming vulnerable to disruptive innovation. We are biased towards safer methods. With healthcare this is especially true as it is essentially concerned with life and death, where people often opt for more conservative and traditional care models. Any disruptive innovation is often met with apprehension, sometimes crisis and dilemma.

Technology is a good example. If a technology or a practice shows great potential to save lives, doctors, clinicians and patients are readily willing to consider new treatment options. However new advancements and changes can cause resistance. Perhaps this is the reason why new plans often ‘land hard’ in the medical world. Also, time is needed to create safe processes, assess failure modes and develop quality measures.

If there is an industry that, above all others, needs to “see the future now” and which needs to do the needful for that future, it is healthcare.

What is considered a “disruptive innovation”?

An innovation will be disruptive if it involves:

  1. A central or key aspect of our work 
  2. Either a completely unheard of or new capability (“Functionality”) is brought about or a new process that completely transforms or changes things upside down

Such massive disruption is now happening within the healthcare industry through the explosion of data.

The great data disruption in healthcare:

India’s healthcare system is undergoing a radical change and has seen significant progress in recent years. Strong economy, availability of medical options and longer lifespan have increased the overall demand for high quality healthcare services. Healthcare spending in the Indian economy is forecasted to grow 16 percent per year, from INR 5 trillion in 2011 to INR 19 trillion by 2020.

Recent study from IBM Institute of Business Value shows:

- 92% of India’s healthcare executives expect costs to significantly increase in the next five years

- However, 85% of healthcare executives say existing infrastructure is inadequate to meet the growing demand

- Shortage of skilled medical professionals continues to be a key challenge in delivering quality healthcare, as India maintains fewer than one physician per one thousand of its population, compared to almost three physicians per one thousand in the United States and United Kingdom

The statistics highlight the need for a robust information management system which can be leveraged to bring unprecedented benefits to healthcare in terms of quality, availability, cost, care delivery and patient experience.

While disruption is the norm across industries, here are the three information management trends which need to be considered while designing the future healthcare system.

1. Shift from episodic to continuous care and monitoring:

Technology such as Internet of Things (IoT) devices and Mobile apps enable easy and frequent exchanges between patients and providers. Monitoring devices have also proliferated which enable timely intervention even in case of chronic diseases. The doctor is always in, and, by the way, it’s not going to be just a doctor anymore.

2. Multi-directional flow of information and making sense of the massive amount of healthcare data

The accepted model in medicine has been: Controlled trials to guidelines to doctor recommendation.

Now health information is flowing in unimaginable volumes from different directions via continuous monitoring (IoT) devices (e.g. fit bit, health apps on mobile phones). Patients are interacting with each other and doctors via technology (electronic medium) and creating massive datasets, which typically forms the healthcare ‘big data’. Patients are increasingly contributing directly to the Electronic Health Record (EHR) through bodily parameters, words or biometrics from their devices.

Healthcare research is at its peak, which contributes to massive amount of data themselves e.g. approximately 44000 oncology research papers alone were published in 2015-16.

Healthcare data is exploding. By 2020, it is expected to double up in every couple of years. Healthcare big data is great, but what can we do with it to improve healthcare? Big data is nothing new. But earlier, healthcare world did not have the proven Artificial Intelligence (AI) or cognitive capabilities to ingest the unstructured and voluminous data, curate them and put them into a condition where patterns can be recognized and meaningful insights can be derived within a very short period of time. IBM Watson is a great example of such a cognitive platform. IBM Watson For Oncology is a disruptive solution that can help augment the oncologist’s capacity multi-fold by providing insightful and evidence based treatment options.

3. Increasingly specific knowledge used in decision-making:

What am I? A microbiome, metabolome, a genome? Health systems are going to try to assess me “as I truly am” and assist me in “how I wish to be” for the sake of my health. This is individualization for the masses, which will have far reaching consequences.

Consider these trends with something like the development of a decision support tool. Does it support continuously updated knowledge? Can it handle more than just practice guidelines from Randomized Controlled Trials (RCT)? For example, will it incorporate the multiple data streams of predictive analytics, genomic data, monitoring data, and especially patient preferences or goals? Perhaps we could always retreat to the soothing image of a clinical guidelines flowchart that we simply encode into the EHR, with a final box that says, "Just tell the patient you're going to do this". But that really wouldn't reflect what healthcare IT systems are capable of in the 21st century, would it?

Can our current structures handle these trends in information? Are there other disruptive trends to consider? Will the tools being built right now in healthcare informatics remain useful as these trends evolve?

These are some questions that remain outside the scope of this article, but hopefully we have answers to these as a part of another conversation very soon.

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