Why the West Needs a New Model for Medical Decision-Making
For years, we’ve been told the healthcare crisis is about not having enough doctors. The solution, we’re told, is to train more of them.
But what if that’s not the real problem?
What if the issue isn’t the number of doctors but how we use the workforce we already have?
The Problem
Modern healthcare is designed to funnel every medical decision through a doctor.
Whether it’s a routine check-up, a prescription refill, or a diagnosis, a physician is expected to make the call.
This makes sense for some cases.
But most healthcare decisions don’t need a fully trained doctor.
And yet, our system is set up so that only doctors have the authority to prescribe, diagnose, and make final medical decisions. Meanwhile:
- Nurses, caregivers, and community health workers who interact with patients far more frequently are forced to operate within restricted scopes of practice.
- Patients are waiting weeks or months for basic medical decisions that should take minutes.
- Rural and remote communities struggle to access care at all.
The result?
Overworked doctors, an underutilized workforce, and patients who suffer because of unnecessary bottlenecks.
Meanwhile, the developing world is solving these problems using a different model entirely.
How the Developing World is Doing It Differently
In many resource-limited countries, there simply aren’t enough doctors to go around.
So instead of forcing everything through a physician, these systems have built structured decision-making pathways for non-doctors.
Take the WHO’s IMCI (Integrated Management of Childhood Illness) and IMAI (Integrated Management of Adolescent & Adult Illness) guidelines.
These frameworks allow nurses, community health workers, and frontline caregivers to make structured medical decisions without needing a doctor’s approval for every step.
They work like this:
- Instead of relying on "gut instinct," healthcare workers follow structured flowcharts and clinical decision trees to assess, diagnose, and treat common conditions.
- If a case falls outside the standard pathway, the system automatically escalates it to a doctor.
- Workers operate within strict, evidence-based guidelines, ensuring decisions are made safely.
The result?
More care gets delivered faster, safely, and without unnecessary barriers.
And it’s working.
Bringing This Model to the West
If the developing world can use structured guidelines to expand the capacity of non-doctors, why can’t we?
What if we adapted this model for the Western world?
That’s exactly what I proposed in my white paper:
1. IMEI: A Structured System for Elderly Care
We have IMCI for children. We have IMAI for adults.
But elderly care? It’s a mess.
Despite the fact that age-related illnesses make up the majority of healthcare spending, there is no single structured framework to guide frontline workers in geriatric decision-making.
My proposed IMEI (Integrated Management of Elderly Illness) would fill that gap.
It woudl provide a structured system for caregivers, aged care nurses, and support workers to safely assess, manage, and escalate elderly patients.
It would give a clear scope of practice that enables workers to operate independently within evidence-based guidelines.
And most importantly, it would have defined decision-making rules to ensure that care is delivered efficiently without unnecessary hospital admissions.
We already trust structured guidelines in pediatrics. It’s time we did the same for elderly care.
2. The Diploma in Restricted Medicine
Not everyone needs to be a full doctor to provide safe, structured care.
A "Diploma in Restricted Medicine" would create a new category of medical professionals.
These professionals would operate within well-defined limits but with greater autonomy than traditional caregivers.
It would train individuals to:
- Diagnose and treat common conditions using structured decision-making tools.
- Prescribe medications from a restricted list tailored to their scope.
- Order and interpret specific diagnostic tests without requiring a physician.
- Work within a clear escalation framework, knowing when to refer, when to treat, and when to ask for help.
This wouldn’t replace doctors.
It would fill the massive gaps in our current system by allowing trained decision-makers to handle routine cases safely and independently, while freeing up doctors to focus on more complex cases.
Structured Decision-Making
One of the biggest concerns about allowing non-doctors to make medical decisions is the risk of errors, inconsistency, and missed diagnoses.
But what if AI could make restricted-scope workers safer, smarter, and more effective?
AI in healthcare isn’t about replacing doctors. It’s about enhancing decision-making by helping caregivers, nurses, and community health workers operate within a structured framework while reducing risks.
Here’s how:
AI would work as a Clinical Co-Pilot
Instead of making independent medical decisions, AI can cross-check symptoms, suggest differential diagnoses, and flag potential misdiagnoses. It can identify subtle signs that human decision-makers might miss, providing an extra layer of safety.
AI could have predetermined Escalation Pathways
AI doesn’t need to have all the answers. It just needs to know when to escalate. If a case falls outside normal clinical guidelines, AI can prompt a second opinion, recommend further tests, or escalate to a physician.
We could use a custom AI for Limited-Resource Environments
AI can adapt to local conditions, offering guidance based on available medications, lab tests, and clinical tools. In rural settings, it can provide alternative treatment pathways when resources are scarce.
AI can learn
AI can analyze outcomes over time and learn from real-world data to improve recommendations. Unlike traditional training, where workers only improve through experience, AI can provide ongoing, real-time feedback.
By integrating AI into structured medical decision-making, we can expand safe healthcare access without increasing risk.
How to Build Trust in Non-Doctor Decision-Makers
Even if structured guidelines and AI make restricted-scope workers safer, there’s still a deep-rooted trust issue in medicine.
For decades, the system has been built around the idea that only doctors can make real medical decisions.
Changing that means changing mindsets.
Here’s how we can build trust in non-doctor decision-makers:
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Clear Scope of Practice
- People trust defined roles. If we set clear limits on what restricted-scope workers can and can’t do, they become more accepted.
- Example: A nurse practitioner in a rural clinic isn’t replacing a doctor. They are working within strict, structured protocols.
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Mandatory AI & Clinical Decision Support
- Trust increases when mistakes are caught before they happen.
- AI-assisted clinical decision-making can provide a second layer of validation, ensuring safe, consistent care.
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Gradual Expansion Through Proven Success
- Trust builds over time. Instead of making a sweeping change overnight, we start with pilot programs and demonstrate success.
- Example: If nurses prescribing within a restricted list reduces hospital strain without increasing risk, trust grows.
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Data-Backed Risk Reduction
- The biggest argument against non-doctor decision-makers is safety. But what if outcomes prove they work just as well?
- By tracking and publishing real-world data, we can demonstrate that structured, AI-supported decision-making is safe.
Trust isn’t built through theory. It’s built through results.
The Government Rejected It. But it Still Has Legs.
When I first proposed these ideas to the Health Minister, they weren’t accepted. Maybe the ideas were too radical or not backed by enough researched. (You can only write so much in a 100 page document)
But that doesn’t mean they were wrong.
If anything, the global healthcare crisis has made them even more relevant.
- Doctors are burning out.
- Patients are waiting longer than ever.
- Healthcare costs are spiraling out of control.
We don’t need more doctors. We need a better way to use the workforce we already have.
A system where trained, structured decision-makers can provide care without unnecessary restrictions.
A system where AI, structured guidelines, and escalation pathways keep those decisions safe, consistent, and efficient.
A system that puts patients first instead of putting bureaucracy first.
Where Do We Go From Here?
It’s time to stop pretending we can keep doing things the same way.
The healthcare system is not working.
But the solution isn’t just more doctors, more hospitals, or more funding.
The solution is rethinking how we train, empower, and trust the people already on the frontlines of care.
If we don’t change, the system will collapse.
If we do, we might just save it.
