AI Will Start Prescribing Medications in the USA: The Silent Revolution in Healthcare

Hello HaWkers, a historic change is happening in the American healthcare system: the FDA (Food and Drug Administration) is allowing artificial intelligence systems to prescribe certain medications without direct medical supervision. This decision marks a turning point in the relationship between technology and medicine.

Let's understand what's behind this decision and its implications.

What's Happening

The FDA made an unprecedented decision.

Authorization Details

The contours of the new regulation:

Scope of authorization:

Prescription of low-risk medications
Well-defined chronic conditions (type 2 diabetes, controlled hypertension)
Renewal of existing prescriptions
Dosage adjustments within pre-defined parameters

Important limitations:

Does not include controlled substances
Does not cover initial diagnoses
Requires prior medical history
Human supervision in exception cases

How It Works in Practice

The flow of an AI prescription:

Process steps:

Patient checks in via app
System analyzes health data (wearables, recent tests)
AI evaluates if condition is controlled
If within parameters, prescription is automatically generated
Medication available at pharmacy
Alerts triggered if anomalies detected

Typical cases:

Metformin renewal for controlled diabetic
Anti-hypertensive adjustment based on pressure readings
Refill of maintenance medications
Prescription of OTC drugs that require prescription

Why This Change Now

The context that led to this decision.

Healthcare System Crisis

The numbers that pressured the change:

Access to care:

25 million Americans without primary care physician
Average time for appointment: 26 days
Rural areas: up to 60 days wait
Average consultation cost: $250-400

Professional shortage:

124,000 physician deficit by 2034 (projection)
Medical burnout at record levels
50% of doctors considering reducing hours
Demand growing with aging population

Technological Advances

What made this possible:

Medical AI evolution:

Models trained on billions of medical records
Accuracy above 95% in specific diagnoses
Integration with monitoring devices
Validation in robust clinical studies

Infrastructure:

Interoperable electronic medical records
Medical-grade wearables
Ubiquitous connectivity
Automated pharmacies

Impact on the Healthcare System

What this change means in practice.

Expected Benefits

The projected advantages:

For patients:

24/7 access to prescriptions
Elimination of unnecessary appointments
Continuous monitoring
Reduced costs

For the system:

Doctors focused on complex cases
Reduced waiting lists
Resource optimization
Prevention of complications

Projected numbers:

40% fewer routine appointments
$50B saved annually
15% better treatment adherence
20% fewer preventable hospitalizations

Concerns and Criticisms

Not everyone is convinced:

Medical associations:

Risk of losing clinical nuances
Undefined legal liability
Dehumanization of care
Dangerous precedent

Ethics specialists:

Algorithmic bias in vulnerable populations
Unequal access to technology
Privacy of sensitive data
Patient autonomy

Patients:

Preference for human contact
Distrust of technology
Fear of automated errors
Loss of doctor-patient relationship

⚠️ Alert: The American Medical Association expressed "serious reservations" about the speed of implementation.

International Comparison

How other countries are handling it.

Global Scenario

Different approaches around the world:

Country	Status	Approach
USA	Implementing	FDA regulation
UK	Pilot	NHS testing in 3 regions
Germany	Study	Feasibility analysis
Japan	Planning	Framework for 2027
Brazil	Observing	ANVISA monitoring USA
China	Advanced	Already implemented in rural areas

Lessons from China

The country that has advanced the most:

Chinese implementation:

Started in 2023 in rural areas
500 million AI prescriptions in 2025
Error rate: 0.3% (similar to doctors)
Massive adoption in pharmacies

Challenges faced:

Initial resistance from doctors
Interoperability problems
Error cases amplified in media
Frequent regulatory adjustments

Opportunities For Developers

An area of explosive growth.

HealthTech Market

Sector numbers:

Market size:

2025: $45 billion (AI in healthcare)
2026: $62 billion (projected)
2030: $188 billion (estimate)
CAGR: 35%+

Investments:

$12B in medical AI startups in 2025
45% year-over-year growth
Largest rounds: $500M+

High-Demand Positions

Emerging careers:

Technical roles:

Clinical AI Engineer
Health ML Specialist
Medical Data Scientist
Regulatory Tech Specialist
Healthcare Integration Developer

Salary ranges (USA):

Junior: $90k - $130k
Mid-level: $130k - $190k
Senior: $190k - $300k
Principal: $280k - $450k

Required Skills

What to develop:

Technical:

Python/R for ML
Knowledge of LLMs
Healthcare APIs (FHIR, HL7)
Security and compliance (HIPAA)
Systems integration

Domain:

Basic medical terminology
Clinical workflows
Healthcare regulations
Ethics in medical AI

How to Get Started

Roadmap for the field:

Short term (1-3 months):

Study health informatics fundamentals
Learn about regulations (HIPAA, FDA)
Explore public health datasets
Take medical terminology courses

Medium term (3-6 months):

Build projects with health data
Study implementation cases
Network in HealthTech communities
Seek relevant certifications

Long term (6-12 months):

Apply for positions at HealthTechs
Develop specialization
Publish about experiences
Consider master's in health informatics

The Future of Automated Medicine

Where we're heading.

Expected Evolution

Projections for the coming years:

2026-2027:

Expansion to more medication classes
Integration with telemedicine
Medical-grade wearables mainstream

2028-2030:

Automated diagnosis in simple cases
AI-assisted surgeries
Truly personalized medicine

2030+:

AI as first medical point of contact
Generalized predictive prevention
Continuous vs episodic medicine

Ethical Reflections

Questions we need to discuss:

Open dilemmas:

How far to automate health decisions?
How to ensure equity of access?
Who is responsible for errors?
How to preserve humanity in care?

The authorization of AI prescription in the USA is a milestone signaling the future of medicine. For developers, it represents a unique opportunity to participate in a transformation that will affect billions of people.

If you want to understand more about AI in healthcare, I recommend checking out another article: OpenAI Launches ChatGPT Health where you'll discover how big techs are entering this market.