Healthcare Innovation: Tackling it head-on

Healthcare is on the brink of revolution, owing to the rapid industrialisation of medicine. We are not talking about ‘global challenges’, but far from meeting them. Healthcare is very splintered across the geography that it would be impractical to implement “technological advances” without giving due cognisance to socio-cultural issues. I find it surprising, because investors’ “money (either in the form of grants or venture capital) can be better used by working on modest goals, thereby scaling them.

Academia is highly risked averse in several ways; grant committees find it easier for a group think and there’s no funding of a breakout idea. Despite increasing the bureaucracy (and reams of paper), it bogs down the intellectual faculties which would otherwise scale up “reproducible science”, instead.

Scaling it up

The proof of concept in the lab is as valid as long as we can scale it up in the consumer domain. Hence, the “output” is more important than the workflows, which can be deemed iteratively through trial and error. The Walkman became a cultural phenomenon because it served a definitive need, and thus the network effects grew. The original prototype may have been clunky, but they grew better with time and spawned the idea for better portability through iPod’s. Similarly, the later “generations” of iPods were better than the previous ones, although they represented an incremental upgrade.

Likewise, healthcare is an abstractive layer because people understand its importance after they have lost it. I wonder why it can’t be turned into a subscription business! (Gym membership and health fitness apps represent a crude first generation iteration of this phenomenon). The biggest stumbling block to its the widespread introduction as a “lifestyle measure,” requires considerable marketing.

Thus, it is important to focus on the “micro” from the “macro”. From global to local- healthcare, domains can better be served by confluence of technology “smartly”. Mobile applications have to be custom served to work in tandem with the medical records. A good UI/UX should serve as a logical whole to avoid disruption to workflows. These are resident challenges- for the end users, namely hospitals and practitioners. These applications require having a value addition to individuals to repurpose a continual engagement.

In one of my preceding places of employment, there had been a significant policy push towards enactment of universal healthcare records. Despite the undeniable advantage, there was a substantial user resistance from healthcare practitioners who undervalued their role as glorified “typists”. When I suggest that technology has to be merged with healthcare delivery seamlessly, these are the friction points that need to be solved, rather than the moniker of “global health” that ordinarily involves SMS notification to end recipients in a remote village of Africa. It represents a criminal misuse of research funding as most of the publications cannot highlight quantitative outcomes. We can make it more valuable if the stakeholders accept the derived value for personal enrichment.

How do we define these end points?

I became appreciative of Pasteur’s quadrant given by the late political scientist Donald Stokes (Donald E. Stokes, Pasteur’s Quadrant: Basic Science and Technological Innovation, Brookings Institution Press, 1997)

Bohr’s Quadrant– Basic “curiosity” driven research without consideration of practical use.

Edison’s Quadrant: Applied research for finding practical solutions.

Pasteur’s Quadrant: Expands basic scientific research for pressing societal needs.

They left the fourth quadrant vacant. I think I can fill up that quadrant with the “idea funnel“:

The fiscal advantage that I am alluding to is the “returns on investment”. Frankly, the VC firms would bet on an idea, but it is laborious to monetise the presentation deck because of several unanticipated circumstances.

My personal endpoints:

I have several “proof-of-concept” solutions in mobile healthcare, and I began “small” with the increasing acknowledgement in conferences for a “peer recognition” to the concept.From a chatbot to mobile apps and eventually a conceptual idea to advance in machine learning for brain tumours. Each iteration inspired me to explore programming libraries, app development, and the need for constant communication to test them. A thrifty mentality revealed the easiest ways out. As an example, we base one of my bot on Telegram chat application, and we hosted it on a Raspberry Pi. Scaling them up, is a distinct challenge of execution. Alternatively, it was easier to entertain having a mobile application with an integrated NLP library and list it on the Play Store. I had to shoot down this idea – it’s too complex to determine its benefits for an end user.

The valid learning point is to go beyond the novelty value of a shiny end product to something that an end user would constantly engage and drive value. This value creation that builds a positive feedback loop to make it relevant to all stakeholders.

You can either have a great spin on a product or build a better product. 

It has helped to gain a solid idea in the “output” side of execution. And I have failed. Several times. Miserably. However, I am glad about it because I can now understand the failure points in virtually anything!

The role of Regulation:

Over the preceding few months writing this blog (and exceeding 500 posts), it has given me an extraordinary hindsight into artificial intelligence. It is a hammer looking for a nail in healthcare. It is very tempting to drift toward techno-optimism, calling it the age of “bionic robots,” but it does much to undermine the compelling field of machine learning. A scientist trains an algorithm in pattern matching, using multiple analytical constructs that require an increasing amount of data. It involves a fundamental overhaul of policy, networking and computing resources, and not least of ethics.

Regulation will find it tough to catch up with a rapid pace of asymmetric but sequential developments and exploring the edge use case scenarios. The total of an end product will depend on the weakest link. A commonsensical approach would use data localisation, on premise resources and help to create a regulatory framework (? lobbying). These pressing issues are beyond logical reasoning as the society has not encountered (and readied for) its absolute impact.

a writing on the wall
Photo by Daria Shevtsova on

Considering a speculative scenario wherein natural language processing gets an acceptable conversational interface. What would make a hospital group choose (and change) them according to their needs? Since users are gradually getting used to communicating with their watches, it is only a matter of time before they pass their problems onto bots instead. Automation is not sufficiently developed without the help of human moderators but is getting better with a new iteration of algorithms, it is only a matter of time. Will the primary care physicians be replaced? What would stop the institution to implement it for twenty-four hours healthcare?

End Goal

I’d like to highlight an interesting facet from the history:

The worthwhile problems are the ones you can really solve or help solve, the ones you can really contribute something to. A problem is grand in science if it lies before us unsolved and we see some way for us to make some headway into it. I would advise you to take even simpler, or as you say, humbler, problems until you find some you can really solve easily, no matter how trivial. You will get the pleasure of success, and of helping your fellow man, even if it is only to answer a question in the mind of a colleague less able than you. You must not take away from yourself these pleasures because you have some erroneous idea of what is worthwhile.

Richard P. Feynman

What is the way forward for healthcare innovation? As I said, image processing illustrates a peripheral scenario, but would serve as a kind of “revolution” if it could facilitate the concept of “industrialisation.” Medical professionals must appreciate the concept of “efficiency” and reinvent themselves to understand technological disruptions as and when they occur.

We cannot avoid the march of progress, but it would help us break its cadence.

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