(A personal aside: Dear community, I hope you can forgive the long delay since my last post. Just as I started writing this post back in July 2024, the now-ousted Sheikh Hasina regime started a brutal crackdown on my fellow Bangladeshis — firing live rounds at students, children, bystanders indiscriminately. For a period of about a month, Dhaka — the city I grew up in and have lived in for over 35 years of my life — became a war zone. At least 1000 people were killed, and many times more maimed or blinded for life. A 7th grade student of Teach for Bangladesh, an organization I sit on the board of, was among the martyred protesters. All of this sent me into a vicious downward spiral, and for the last few months, I have been struggling to climb back up. Despite all the excitement and energy I started this blog with, everything seemed to feel pointless against what was going on in my beloved country.

After months of reflection and recovery, I am finally returning to this blog with renewed determination to envision a better future for healthcare. I hope to do you justice and bring you at least one post a month for the next few months, before getting back to my bi-weekly schedule. I am deeply grateful for your patience, and the many kind souls who reached out through this trying time.)

In my last three posts, I reflected on current gaps in health systems, how AI is both stretching the limits of our current systems and opening up novel opportunities, and the central role of self-care that is currently ignored in our health systems. A logical next step would be to try to envision a 21st-century health system that leverages all we know from our historical mistakes, and the emerging technological opportunities, to deliver a truly people-centered, integrated, and outcomes-oriented care experience for all. I’ll peg the timeline at 2040 to be more specific, but also (hopefully) to leave sufficient time for some of the behavioral and regulatory inertia to be overcome.

The Design challenge

I am going to approach this as a constrained optimization problem starting from first principles (my econ professors may finally be proud!). I will first set up my criteria, assumptions and optimization function, and then try to outline the design that this leads me to. Please note that I am intentionally NOT including as constraints the inertia of existing systems — comprising of regulatory barriers, lobbies, special interests, etc. — which benefit from and try to protect and perpetuate the status quo. I will touch on this again a bit at the end.

Optimization Objective:

Maximize physical and mental health outcomes while ensuring “positive experiences” during care.

Design constraints:

1. Must be applicable with contextual adaptations to most low-and-middle-income countries (excluding those that devolve due to man-made or natural calamities).

2. Must address the healthcare needs of the masses within these countries, and not just within the wealthiest segment of the population that can afford concierge services or fly to another country for care. Please note that this definition may or may not include the most marginalized, such as refugee populations.

3. Must address the three prevailing challenges of fragmented, poor quality, and perverse incentives (post with details here).

4. Must be feasible to accomplish using existing resources or less in most developing nations.

Assumptions:

• Current rate of development in technology, especially digitization and AI, will continue linearly (need not be exponential) at least for next 15 years until 2040.

• Current rates of socio-economic progress in LMICs continue.

• The overall amount of development assistance going to health programs at least remains steady.

Healthcare 2040 - foundations and design

Person-centered healthcare is impossible without a holistic view of the person and their health and wellbeing. In 2040, two fundamental objective sources of truth about each human being will enable this holistic view:

1. Their genome: Extrapolating cost reduction trends (which happen to outpace Moore’s law) in human genome sequencing, a full human genome sequence will cost ~$10 in 2040. As a one-time cost yielding significant lifetime dividends, all but the poorest countries will find it worthwhile to sequence everyone’s genome at birth.

2. Their longitudinal health history: Projecting forward current and emerging trends, each individual can have a biometrics-based, comprehensive health record that stays with the individual from birth to death, and aggregates information about every care encounter, self-care conversation, biomarkers (from wearable devices, biochips, etc.) and hospitalization record throughout their lifetime.

This firm grounding in each individual’s unique and continuously evolving health profile will enable healthcare in 2040 to be fully personalized, and form a life-long care continuum that starts at birth and ends only in death.

Such extensive data aggregation about personal genomics and health, while extremely promising, certainly also poses ethical and logistical challenges, particularly in ensuring data privacy in LMICs. I strongly believe this individual level health profile or record must be biometrically encrypted and legally owned and controlled by each individual (not their government or some private entity like EPIC), to enable maximum aggregation while minimizing risk of breach/exploitation. Here is another article where I dive deep into this:

Health Data Done Right

Rubayat Khan

·

Apr 10

Read full story

Overall architecture

By 2040, we must flip 180 degrees the existing top-down and provider-and-system-centered design of healthcare (e.g. emphasis on hospital-based care and vertical disease oriented programming) and amplify the role of individuals, families, and communities as the central engine of health, going even beyond the original vision of Alma Ata. Most of the resources in this new model will be used to strengthen the care continuum at the community level, enabling local health systems to handle as much as 90% of lifetime health needs of the community. Referral linkages to facilities will only handle the remaining 10% of cases that cannot be addressed locally.

Instead of the often blurred boundaries between primary, secondary and tertiary care (which frankly always confused me, and leaves out the all-important role of self-care), I propose a simpler and more comprehensive categorization, in terms of home-based, community-based and facility-based care. Below I will flesh out each in more detail.

1. Home-based care

This would include:

1. Educating and supporting people on all the self-care activities people do (or could do) at home

2. Supporting (and even compensating) families and caregivers to take care of their dependents (children, elderly, disabled, post-operative or terminal patients, etc.) in the best way possible

3. Routine doorstep check-ins by community health workers (CHWs) for things like ANC, PNC, family planning, HIV ART, NCD follow ups, disease surveillance, etc.

4. New technologies like patient-to-doctor teleconsultations, rapid self-testing (such as the COVID home test), cheap bio-chips (e.g. blood glucose monitoring patches), e-pharmacies and medicine home delivery, and most importantly AI personal health companions, will all greatly enhance the range, continuity and fidelity of care that can be provided at home.

As I discussed in my earlier AI post, let me re-articulate the central role of AI in this shift. By 2040, AI health companions with better medical training than the best doctors on the planet today will become virtually free in terms of cost-of-inference (price-performance ratio of LLMs is decreasing by 10x each year). With any internet connected device, a family could have the assistance of such an omnipresent family health companion (closest analog may be the Google Assistant/Alexa of today) that is accessible at any time to answer queries, track vitals and flag deviations, triage a new symptom, manage a chronic disease, and more, individually for each member of the household. And all of this can happen over voice in the natural language of the user.

It’s 3 AM, and your child is coughing hard? You can ask your AI in Bangla what to do. Based on just the sound of the cough, the AI will be able to triage if it is something you need to worry about, and automatically alert your community nurse if so. You’re not sleeping too well lately? It will advise you to take a warm shower, manage your stress, and guide you through a breathing exercise before sleep time. You need an antibiotic for a bacterial fever? It will be able to do effective triage (vs. a viral infection), write a prescription if necessary and order home delivery for you (as long as the supply chain exists). It could even initiate and facilitate telemedicine encounters with the community nurse or the specialist doctor in the city, summarizing the case history for the provider and explaining their recommendations to you afterwards.

The affordability of the AI will enable most governments to distribute this assistant for free to any household with a device. For those without devices, it might still be available over a phone call, or via a kiosk at the local pharmacy (Babyl’s AI tool was available at kiosks at Rwanda’s community clinics and powered the national health helpline before its mother company went bankrupt last year).

Not only that, every conversation with AI companions will incrementally populate the health history for each household member, and create the most granular, rich and continuous health record we have ever seen. As a result, unlike today, home-based care will become a completely visible, transparent process, making rich personal health and behavioral data available to inform community- and facility-based care interactions if and when escalation is needed.

2. Community-based care

Not everyone can manage self-care effectively. Some are too young, elderly, burdened with chronic conditions, or may not have anyone to care for them. Even otherwise healthy people sometimes fall sick from infections, trauma/accidents and other extraneous causes.

People will therefore need health providers and facilities in the community to handle such cases, without needing to travel long distances. Many community-based providers already support patients in their health journeys, such as pharmacies and drug shops, public sector/NGO community nurses and community health workers, and more. However, many of them are currently undertrained, poorly equipped, not digitized, and poorly paid. This must change by 2040, and we must empower local providers with the knowledge and tools to take care of their communities optimally.

With strategic investments, by 2040, in most parts of the world we can have local mini-clinics such as a publicly funded/subsidized Community Health Center (CHC) — staffed by a qualified nurse or paramedic from the same community who can provide the vast majority of outpatient care with support of AI clinical decision support tools, basic lab tests and ultrasounds, and high-bandwidth video tele-consultations with remote doctors and specialists. These technologies will greatly amplify the range and accuracy of medical services these non-physician providers are able to provide, and hence eliminate the need to have physicians be physically present at the community altogether. Indeed, container-clinic models like AccessAfya or North Star Alliance or pharmacy++ models like Ilara Health’s AfyaNzima franchises or mPharma’s Mutti pharmacies already provide a glimpse of what these CHCs might look like.

The vastly superior experience of seeking care at such a CHC (assuming we can fix the “incentive problem”, which I will tackle in future posts), as opposed to traveling to distant facilities like hospitals for outpatient care, are manifold:

• Convenient and more accessible at any time of day

• Savings in travel time and cost

• More respectful, responsive, empathetic, and “equal” encounters from someone you already know from the community.

• Greater accountability of a local provider as opposed to an impersonal doctor who might never meet this patient again

• Option to request house calls for the sickest patients

Not only will each individual interaction with such a health provider be more rewarding, but better interoperability and linkages between providers will ensure that the total is greater than the sum of the parts. At present, you might go to your local pharmacy for routine blood pressure checks for hypertension, but the public clinic nearby has no clue that you have suffered from uncontrolled hypertension for a decade (that is, until you show up at the hospital with a stroke). By 2040, I anticipate that we will have resolved data interoperability challenges (including resistance from private sector, lack of technical capacity in-country, etc.) and established national standards be able to facilitate seamless flow of data and information between all different types and sectors of providers within an ecosystem. An early test of this that we are supporting from Endless is D-tree’s Afyatek model in Tanzania, which seamlessly connects pharmacies, community health providers, and facilities through a unified data structure and platform. Another example is the FHIR-based standardization of health records within both the government and BRAC community health systems in Bangladesh, which for the first time is allowing an unified view of over 120 million patients’ health journeys and helping avoid duplication of efforts.

Of course, community awareness events and outreach campaigns such as immunization drives, diabetes camps, etc. will also fall technically under community based care, and may be managed and executed by this same “care team” comprised of the CHC nurse/paramedic and loosely affiliated CHWs and pharmacies.

3. Facility-based care

Only for the remaining few complicated or emergency cases would people need to travel long distances to the hospital, clinic or diagnostic lab with its specialized doctors, radiology equipment, surgical facilities, and inpatient setups. Currently, hospitals are often overwhelmed with outpatient cases causing provider burnout; in this future model they will not serve outpatient cases without referrals.

Bringing it together

This is “task shifting” at its best, where the goal is to do as much of it possible closest to the home (even at home!) and with the lowest skilled personnel available (even the patient themselves!). Below is an illustration of what this ecosystem might look like:

Note that any specialized care pathways (HIV, TB, etc.), rather than having their own vertically integrated and siloed infrastructure, gets embedded into this infrastructure using intelligent protocols. For example, a patient might get flagged as high risk for HIV by their AI companion, walk to the pharmacy for a rapid test, and referred to the CHC for confirmatory tests and ART enrollment if they test positive. Once they come back home, they are reminded to take their ART pills regularly, and if they do not refill their prescription on time as expected, an flag is created on the CHW’s platform who makes sure to check on the patient during their next household visit.

Let’s look at another example of a condition current systems struggle to manage — NCDs, in particular hypertension and diabetes. In this new model, anyone over 35 with any risk factors will be routinely screened by the CHW for high BP or blood glucose. If flagged, they will be referred to the CHC for a confirmatory test, and an AI or virtual doctor will help determine the personalized care plan for the patient, setting scheduled reminders to both the patient and their various providers to ensure the right steps are being taken on time. And at home, the AI care companion will always be ready on a moment’s notice to answer any questions, guide people through diet and lifestyle modifications, and more.

Because it is a closed loop system, you can design the system to be proactive and intelligent in this way, and orchestrate providers’ workflows and schedules around the patient’s needs, preferences and behaviors. I am calling this “ambient systemic intelligence” (which complements and builds on the “personal intelligence” in everyone’s pockets). Of course we have implemented rule-based scheduling for many years, but they tend to be rigid and one-size-fits all. AI can make these much smarter and more clinically informed, enabling completely novel capabilities such as personalized care planning and orchestration.

And indeed, the vast majority of experts I have spoken to seems to agree that such a system would generate much greater bang for the buck than the fragmented, convoluted mess we have in place today.

Is this realistic?

Before I conclude, let me turn to the all important question on everyone’s mind who is reading this — is this vision really feasible given all we know about how global health works today?

I would posit that all of this is plausible, within the constraints laid out at the very beginning. However, there is a reason I left out the inertia and rigidities of “how we do things around here” out of my list of constraints at the very beginning of this design exercise. What stands on the way of implementing this vision is indeed our own conventional wisdom, biases and prejudices, and systemic inertia. Conversely, by unlearning past mistakes and adopting new approaches (e.g. reorient global health funding flows from vertical disease programs towards systems strengthening, acknowledge that insurance is not the best way to fund primary care, etc.), changing our culture of care (e.g. passive to proactive and transactional to relational), and letting go of our unconscious biases and prejudices (such as that towards private drug shops and pharmacies, assuming we as experts know better than patients what they need), this vision is indeed very much possible to bring to reality.

Even if we are unable to make all these profound paradigm shifts globally, I strongly believe that some countries, especially those in the Global South with innovative and prescient leadership and a blissful lack of legacy infrastructure and systemic rigidities, will invest and successfully build out similar compelling models of care. I was tremendously inspired by Costa Rica’s localized and highly proactive care teams, proving to the world for the first time with evidence that holistic primary care can indeed produce unprecedented results (in this case 13% reductions in all-cause mortality). Sadly political shifts have since dampened much of the success there, but I am certain we will see others step up (my best bet would be on countries like Indonesia, Malawi and Rwanda). However, sustaining political will in these pioneering countries, and measuring results to generate evidence systematically to inform the global conversation, will be key.

In the meantime, the clock has started ticking, and we don’t have time to waste. As innovators, funders, and practitioners, we collectively hold the power to examine our own blind spots, disrupt this dysfunction, and chart a new course for global health.

It all begins with a simple declaration: “We can do better!”

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I intentionally left out some important questions in this post for brevity’s sake — such as about financing and incentives, or the public-private split of this model — which I will try to tackle in future posts. But in the comments, please let me know if I have missed any other obvious aspects of public health and care provision that is unaddressed by this model. Your feedback and insights will be invaluable as we refine this vision together.