[This is a subset of the original Story published in a pre-pandemic world : https://www.linkedin.com/pulse/365-days-health-ten-predictions-decade-ahead-siddhartha-chaturvedi/ — also the views are mine, not my employer’s]
I had spent my Christmas (and the turn of the decade) in my bedroom, with antibiotics and bronchodilators. I had just been diagnosed with pneumonitis.
Well, if there was ever a place for me to fall ill, I would do so at home, surrounded by doctors who have known me for the last 3 decades. There was a point of time when I had more doctors in my room than I could count, discussing and dissecting my reports, sipping cups of tea. Ah, a good family reunion.
It did give me an opportunity to reflect on the work that I am doing, and more broadly the health-tech ecosystem. The conversations with my friends and family (who today are working tirelessly on the pandemic response) led to a definite broadening of my perspectives, especially around the nuances of societal and access gaps in health — and led me to pen down some of the areas where I see the growth in this decade.
#Trust — The cornerstone of any interaction in this domain. Doctor-Patient Confidentiality. The Hippocratic Oath.
It all starts with Trust. A lot of doctors (and patients) don’t trust the AI models. There are a handful of medical practitioners (in comparison to the total population out there) who truly understand what AI can, and more importantly can’t, do.
There is also a whole other conversation around data, that we have seen ongoing debates around — who owns the data, who gets paid for the data, and how that data is used. One of the topics that kept coming up in my various conversations was the transparency around the use of data, and the notion of not knowing whether the doctors / patients / organizations might be penalized for the data that they share — from hikes in insurance premiums — to being denied care by a hospital / organization based on the ‘survivability index’. There were other conversations around fake news and being able to trust the information that you see online. One of the famous internet quotes succinctly captured this for me — ‘Don’t replace my medical degree with your internet search’. I tried to search for my own symptoms (once the data-curfew in the state of UP was lifted), and within minutes I found out that I had a (slight) probability to die from at least 3 different causes. I decided to spend my final moments on an online shopping spree but was rudely interrupted by a crowd of doctors dismissing my carefully collated (read as : quickly searched, and indexing the top results) research.
#InformationAsATherapy — when you get the right information, and the right amount of information.
Fake Information can be a major stressor, especially to the people who have limited access to validated medical information or medical professionals. It could lead one to be under a lot of stress, affecting productivity, emotions and relationships — all of which could be the beginning of a downward spiral potentially resulting in General Anxiety Disorder (yep that was researched online), while being out of a job, with no one to share that frustration with. Information as a therapy is one of the ideas that I see taking off in the coming decade, with relevant, validated and abstracted information being made available through the channels to patients who need them, while enabling them to seek additional knowledge from a medical professional.
#Interop — for data to be useful, we need systems to talk to each other, to convert insights to knowledge.
For this trust, we would need robust frameworks that govern the policies and practices that enable both the veracity and the efficacy of technology that finds its way into the health domain. The coming decade might be the beginning of the health continuum — going beyond the traditional health records to include lifestyle data as well. And for that to happen, interoperability and standards are vital.
#DataSavesLives — a movement by some of the leading minds in the UK, explores the importance of the intent to educate the public about how data saves lives.
My dad has the-disease-that-shalt-not-be-named. So do a couple of my aunts. If you were to approach my extended family of probably 50+ people — we all would happily give our information, for furthering the research in that domain. This is where I think the next data-aggregation opportunity lies. We would potentially see an augmentation of Personal Health Records not only with personal wellness and lifestyle data, but also linked-familial data, with the formation of multi-generational datasets that would unlock previously untapped insights into a variety of health conditions, and potentially furthering cluster-personalization of medicine ( a hybrid state of sorts ). As one of my mentors would say — we are moving from a PHOS-Me (Personal Health Operating System) to PHOS-We (Population Health Operating System).
#ClimateChange — it’s real. It affects me. And a ton of people with breathing issues.
Imagine if your maps app could tell you to reroute your morning run, to minimize pollen exposure. When we add the (ever changing) environmental data to augment our personal health information, there are a plethora of opportunities to personalize interventions, with a slight more direct action (or nudge) than just public advisories. As the weather gets more, umm, volatile, there would be a deeper integration of medical and environmental ecosystems. [From pulling your meal plans from wellness apps, and recommending restaurants tailored to your choices, or highlighting the ones where you might have allergies, the possibilities are endless.]
#OneHealth — the health of the environment is intrinsically tied to the health of the humans that reside in it.
Somehow, we are still rely on lagging-indicators to a lot of health-risks and epidemics, primarily due to a reliance on reactive workflows that were created years, if not decades ago. Public Health is getting more intelligent, and I see a fair amount of both investment and opportunity to unlock the understanding of One Health. Learning from the health of the animals and the environment that we live in, could provide crucial insights, and early indicators to hopefully plan preventive interventions.
According to the CDC definition — ‘One Health is defined as a collaborative, multisectoral, and transdisciplinary approach — working at the local, regional, national, and global levels — with the goal of achieving optimal health outcomes recognizing the interconnection between people, animals, plants, and their shared environment.’
#MobileDiagnostics — as the smartphones get more powerful, and USB C becomes slightly more pervasive, we might see the clunky machines getting replaced by medical device modules.
Coming back to me being denied shopping rights in bed; I had a Bluetooth blood pressure monitor, an SPO2 monitor, and a digital thermometer. Not a long time ago, if automated, these were found to be in a hospital (as opposed to my bedside), and if mobile, they needed a trained person to make sense of it ( I still can’t use a mercury based blood pressure instrument — apparently I am inept at systolic readings). With the present devices, not only could I self-monitor the tests, but they’d sync to the app, which could then be shared easily with others. But as I see the present ecosystem of diagnostics evolve, there is a possibility to do a lot more- either by miniaturizing the existing tech ( EKG, Ultrasound ) — or finding new ways to achieve similar results (like the researchers did here with a laser based ultrasound). As we build more distributed systems and modular diagnostics, sometimes whole new sensor systems embedded in everyday life, we will see the continued rise of Internet of Medical Things.
#SocialConstructs — when culture eats technology for breakfast.
While discussing this, I realized that the lack of use of mobile ultrasounds in remote areas of India is not a technological challenge — rather it is a societal one. It pains my heart, but female foeticide is still a thing — and the Pre-Conception and Pre-Natal Diagnostic Techniques Act, 1994 to stop the foetal sex determination and sex-selective abortion. The social constructs of the societal norms, and the lack of awareness (in certain cases) has led to certain technologies being banned or highly regulated — whereas they could potentially provide vital support in reducing maternal mortality in other parts of the country, where health access is a major issue. My dad has spent a fair bit of his adult life dedicated to working with organizations that further sexual education, bust myths, engage in community building and awareness — and it physically pains me to see that there are communities that value one life over another, despite both being their flesh and blood. To enable better health outcomes, we need to educate the society and in certain cases champion for change.
#HealthAccess — availability, awareness, affordability.
In the traditional terms of access, it means connecting a doctor to a patient. But a more nuanced take on health access for me spans infrastructure, literacy and fiscal capacity. The infrastructure lens is the one that we have seen the most advancement in — be it outreach health camps, tele-medicine or creating a middle layer of accredited social health activists (ASHA). The literacy lens has seen an influx of a variety of community building initiatives by various government and non-government organizations. When I ran my start-up in rural health, I happened to pass by a village which hadn’t seen a doctor for a fair few years, and believed that illnesses were evil-spirits that needed to be shooed away (usually involving some incense sticks and getting beaten with a broom). I mean, before we even get them to see a doctor, we sometimes have to educate them what a doctor is.
As the costs of healthcare keep rising, there must be an alternate framework to boost affordability. I know that in a few developed countries, there is an increasing disparity between the insured and the uninsured, and I see business model disruption sooner than later to remedy that. As my strategy professor said — when the enterprises focus too heavily on value capture, and not so much on value creation, they open the doors to disruption, or potential bankruptcy.
#TechDisparity — how do we reduce bias going forward? When are biases important? I don’t have the answer, but let’s start a conversation.
Another discussion that this devolved into was that of the disparities that the ecosystem presently has, and the conversation coming back to Artificial Intelligence and Machine Learning in certain cases lacking the demographically disparate data-sets to provide equitable health outcomes. Now, coupled with the growth in privacy awareness, there is a slight chance that with the lack of diverse data-sets, there may be certain AI based interventions and solutions that address only a certain demographic or gender. For this, we will need to build technology platforms that can increasingly guarantee the safety and privacy of individual data, allowing for dynamic consent, while enabling responsible and trusted consortium of researchers to derive insights and knowledge, to eventually reduce the bias and tech-disparity.
This brings us back to where we started — trust.
It is imperative that the tech-health ecosystem builds trust with the people that it serves. And in that journey — we have to be empathetic, inclusive, collaborative, and vie to create value. Together.
Shameless Plug — It dawned upon me that to solve some of the hardest challenges we need a healthy dose of empathy — of understanding and working on problems that the society faces. That, in my humble opinion, leads us to a more equitable, and a more understanding society.
We look towards building an understanding of the ecosystem to reduce the potentially growing tech-disparity, starting with Women’s Health.
When I ran my own start-up, I realized that Women’s Health has the most direct and significant impact on the health of a family in the areas that I worked in. It is one of the most effective ways to break the inter-generational transfer of disadvantage.
If you would like to learn more about the initiative, or support us to do the baseline exercise on the disparity in Women’s Health from a Data/AI perspective, or are doing one yourself where we can support, please reach out to me.