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MHRA Class I for AVT (AI Scribe) Tools


Each minute of our life is a lesson but most of us fail to read it. I thought I would just add my daily lessons and the lessons that I learned by seeing the people around here. So it may be useful for you and as memories for me.

Over the last several years working in healthcare technology, I have had a front-row seat to the industry’s accelerating relationship with artificial intelligence.

From primary care analytics and NHS interoperability programmes to leading AI-driven product development, I have watched organisations move from curiosity to urgency. Today, commissioners, clinicians, digital leaders, and software vendors are all trying to answer the same question:

How do we use AI to improve care without creating new risk?

The reality is more complex than most roadmaps admit.

Healthcare is adopting AI faster in ambition than in operational capability.

I have seen teams demand “an AI solution” before the problem is defined. I have watched pilots stall because workflows were not ready, governance was misaligned, and data quality could not support the promised outcomes. I have also seen the opposite — where structured safety frameworks, disciplined operations, and clinical ownership produced measurable improvements in care quality, safety, and efficiency.

Nowhere is this contrast more visible than in Ambient Voice Technology (AVT) — AI scribes that listen to consultations and draft clinical notes.

Why AVT Forces the MHRA Class I Conversation

NHS England guidance and multiple NHS-adjacent safety and assurance discussions increasingly position summarisation-capable AVT tools within MHRA Class I medical device scope at minimum.

This is because AVT systems do not merely store information — they influence the clinical record itself. And the clinical record is care.

The NHS has said that any AI scribe that provides summaries for physicians must at a MINIMUM be a MHRA Class I medical device.

Previously, many AI scribes in the UK and EU could be used in hospitals without a medical device designation.

There is still a ton of uncertainty around what qualifies software as a medical device in the UK and EU as well as what features change a software’s risk class from a low risk Class I device into the higher risk territory of Class IIA+.

This NHS notice sets a regulatory floor in the UK for AI scribes, making most, if not all, medical devices.

While I’m sure this is alarming for many AI scribe companies, having this level of clarity on regulatory classifications is refreshing.

I might be a lone in that sentiment but it is a benefit in knowing exactly what your regulatory requirements are.

To dive into the details a bit more, the NHS has declared the following:
– Scribes that generate summarization must have at least MHRA Class 1 medical device status.
– Solutions aiming to produce generative diagnoses or management plans require at least MHRA Class IIa approval.
– Suppliers must provide evidence of real-world clinical validation within a care setting, demonstrating benefits such as enhanced efficiency, reduced administrative burden, and improved patient care and data quality.
– Patient data from clinical sessions should be automatically deleted unless legally or operationally required

Class I is not a registration hurdle.

It is the threshold at which regulators, commissioners, and NHS assurance bodies effectively ask:

Can we trust this company to behave like a medical device manufacturer — particularly when something goes wrong?

Anyone who has handled real incidents — logging safety concerns, coordinating root cause investigations, running calls with frontline clinicians, and closing corrective actions — understands that compliance is not theoretical.

It is operational muscle.

What Class I Readiness Actually Requires (Across the Organisation)

1. Product: Turning Features into Medical Claims

AVT companies must explicitly define:

  • Intended purpose and non-purpose
  • Outputs (transcripts, summaries, structured notes, coding suggestions, letters, write-back boundaries)
  • Users and workflows
  • Medical vs administrative positioning
  • Traceability: feature → hazard → mitigation → test → release

Reality:

If your product generates “clinical summaries,” you must show how you prevent omissions, hallucinations, misattribution, and medication/allergy errors.

2. Development: Building Evidence, Not Just Code

Class I requires:

  • Documented SDLC
  • Risk-based testing
  • Controlled release management
  • Audit trails
  • Enforced human-in-the-loop review

Reality:

Edge cases such as accents, interruptions, and noisy environments must have test evidence — these are not theoretical risks.

3. Clinical Safety: Designing for Real Workflow

Deliverables include:

  • Formal hazard logs
  • Clinical safety cases and sign-off governance
  • Human factors analysis
  • Clear “not for” boundaries

Reality:

A confident-sounding summary can be more dangerous than an obviously incomplete one.

4. Operations: Running a Regulated Service

This means:

  • Incident runbooks
  • CAPA governance
  • Post-market surveillance
  • Controlled change impact assessments
  • Audit-ready evidence retention

Reality:

“Missed medication changes” are safety events, not feature requests.

5. Support: Safety Surveillance at the Front Line

Support must:

  • Triage for clinical risk
  • Escalate within defined timelines
  • Trigger safety investigations
  • Communicate advisories when needed

Reality:

This is where most AVT companies quietly fail.

6. Security & Privacy: Cyber Is Clinical Safety

AVT tools must demonstrate:

  • DPIAs and mapped data flows
  • RBAC and least-privilege access
  • Encryption and vulnerability management
  • UK-aligned breach response

7. Legal & Compliance: Becoming a Manufacturer

Class I readiness requires:

  • Manufacturer registration
  • Declaration of Conformity
  • Supplier qualification
  • Record retention governance
  • Contractual clarity

Why So Many Companies Fall Short

In my experience, failure rarely comes from lack of talent.

It comes from underestimating the organisational transformation required.

Common failure patterns:

  • Vague intended use
  • No traceability
  • Uncontrolled model updates
  • Support teams not safety-trained
  • Weak post-market surveillance

For AVT, tolerance for these gaps is shrinking rapidly.

A Practical Class I Readiness Test

If a clinician asks:

“This note was wrong — what happens now?”

Can your organisation answer in under 60 seconds — clearly, safely, and with ownership?

If not, Class I readiness does not exist yet.

Final Thought

MHRA Class I is not about compliance theatre.

It is about proving your AVT product can operate safely inside real clinics — under pressure, interruptions, and imperfect data — without making clinicians the safety net for your technology.

That is the real standard.

References:

https://www.cbs42.com/business/press-releases/ein-presswire/834019307/nhs-ready-ai-medical-scribe-augnito-omni-ai-among-first-to-fully-meet-new-nhs-england-ambient-voice-tech-guidelines/

https://www.heidihealth.com/en-us/blog/ai-medical-scribe-legal-implications

https://www.healthcare.digital/single-post/nhs-england-issues-guidance-on-ambient-voice-technology-ensuring-safe-and-assured-adoption-of-ai-scr

If you wanna share your experiences, you can find me online in all your favorite places  LinkedIn and Facebook. Shoot me a DM, a tweet, a comment, or whatever works best for you. I’ll be the one trying to figure out how to read books and get better at playing ping pong at the same time.

 
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Posted by on November 25, 2025 in Experiences of Life.

 

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Why Healthcare IT Graveyard Is Getting Crowded


Each minute of our life is a lesson but most of us fail to read it. I thought I would just add my daily lessons and the lessons that I learned by seeing the people around here. So it may be useful for you and as memories for me.

I’ve spent more than a decade building healthcare products across Europe, Asia, and the U.S. I’ve led Quality, Product, and Delivery at scale. I’ve watched companies grow explosively, and I’ve watched companies vanish overnight literally.

And after 15 years working in healthcare, the pattern is painfully clear:

Healthcare tech doesn’t fail because of weak engineering. It fails because founders fundamentally misunderstand healthcare.

Here’s the uncomfortable truth — backed by recent, spectacular collapses.

The Graveyard Is Getting Crowded

These aren’t small startups. These were the darlings of global healthcare tech:

  • Forward Health – $660M raised, shut down with zero patient transition
  • Olive AI – $850M raised, sold for parts after failing to justify ROI
  • Babylon Health – $4B valuation, blew up across multiple continents
  • Pear Therapeutics – FDA-cleared digital therapeutics, bankrupt
  • Quibi of Healthcare: Haven (Amazon–JPM–Berkshire) – shut down despite unlimited resources
  • Google Health (v1) – closed after failing to reach provider adoption
  • Microsoft HealthVault – shut down due to low user engagement and system complexity
  • Sense.ly (AI nurse avatar) – essentially disappeared after poor provider uptake
  • 23andMe Therapeutics spinout – quietly scaled back after no viable clinical revenue stream
  • Walgreens / Theranos fallout – major proof that hype beats due diligence in this sector
  • Proteus Digital Health (smart pill) – raised $500M, then bankrupt
  • Practice Fusion – sold for pennies after criminal investigations and failed EHR monetization
  • ZocDoc expansion failure – pivoted multiple times after failing to win provider-side economics
  • Oscar Health (several failed geographic launches) – struggled due to regulatory economics
  • IBM Watson Health – $3B+ investment, divested for $1B after clinical failures

This list is long. And growing.

The Core Misunderstanding: Healthcare Is Not a Tech Problem

Engineering-driven founders consistently misdiagnose the domain.

They believe healthcare = complex workflows + messy data + outdated UI.

Solve that and… success.

But healthcare is not a systems problem.

It is a trust problem wrapped in regulation, economics, and risk.

  • Lives are at stake — not convenience.
  • Medical decisions require validated evidence — not beta features.
  • Clinicians rely on reliability and accountability — not iteration velocity.
  • Patients don’t adopt new care models without months or years of trust-building.

Every failed company ignored these constraints.

The Integration Trap: The Silent Killer

This is where most companies die.

Healthcare runs on a brittle spine of EMRs, APIs, and legacy systems.

If you don’t integrate, you don’t exist.

  • Forward’s CarePods were genuinely innovative. But without seamless EMR connections, they became operationally useless.
  • Olive AI automated tasks internally… but could not standardize ROI across EMRs.
  • IBM Watson Health promised AI-driven oncology decisions. But the recommendations were inconsistent with evidence-based guidelines.

The rule:

If you don’t reduce workload inside the existing workflow, clinicians will ignore you.

No integration = no adoption.

No adoption = no revenue.

No revenue = shutdown.

Why Consumer Tech Logic Fails in Healthcare

Tech founders try to import playbooks from SaaS, marketplaces, and fintech:

  • “Move fast and break things”
  • “Launch MVP, iterate later”
  • “Acquire users, figure out monetization later”
  • “Data is the new oil”
  • “AI will replace inefficiencies”

These logics collapse immediately in healthcare:

  1. Healthcare data is not clean; 80% is unstructured.
  2. Interoperability is not an optional feature — it is the foundation.
  3. Clinicians require evidence, not velocity.
  4. Patients are not early adopters; they are risk-averse by necessity.

The market punishes anyone who treats healthcare like another consumer vertical.

The Reimbursement Illusion: Where Startups Bleed Out

This is the part Silicon Valley consistently ignores.

In healthcare, value is NOT determined by the end user.

Value is determined by:

  • payors
  • reimbursement codes
  • medical necessity rules
  • regulatory status
  • clinical outcomes data

A product can delight users and still die if:

  • there’s no CPT code
  • insurers won’t reimburse
  • the product doesn’t reduce provider workload
  • there’s no proven cost savings

Olive AI is the textbook example.

Automation sounded brilliant — but if hospitals can’t bill for it, the business collapses.

Pear Therapeutics had FDA clearance, efficacy data, and clinical logic.

Still died because payors refused to reimburse at scale.

Healthcare economics — not innovation — determine survival.

What Actually Works (and Why It Looks “Unsexy”)

The successful products in healthcare are almost never glamorous:

  • Automated population stratification
  • Scheduling optimization
  • Revenue cycle improvements
  • Medication adherence
  • Secure messaging
  • Chronic disease workflows
  • Interoperability middleware
  • Claims cleaning and fraud detection

Unsexy wins because it integrates, it reduces workload, it fits reimbursement, it avoids clinical risk, and it solves one painful problem extremely well.

The companies that succeed do the following:

  • Integrate seamlessly with EMRs
  • Prove ROI early
  • Reduce clicks, not add them
  • Earn clinical champions, not marketing awards
  • Build for the system as it is, not the system they wish existed
  • Grow slowly but sustainably — not explosively and unsafely

Healthcare rewards evolution, not revolution.

Forward Health’s Shutdown Is the Perfect Case Study

Forward turned off the lights overnight:

  • No transition pathway
  • Canceled appointments
  • Patients left stranded
  • Systems turned off immediately

This is what happens when a company:

  • optimizes for investor excitement instead of clinical safety
  • designs for TechCrunch instead of clinicians
  • prioritizes disruption over integration
  • treats healthcare as a retail subscription business instead of a regulated service

Patients pay the real cost of these failures.

The Real Pattern Behind Every Healthcare Tech Collapse

Let’s stop pretending these are isolated incidents.

The failures follow the same template:

  1. Overpromise with polished demos
  2. Underestimate the complexity of clinical workflows
  3. Blow capital on growth before solving integration
  4. Fail to secure reimbursement pathways
  5. Struggle to prove clinical and financial ROI
  6. Lose trust from clinicians
  7. Run out of money
  8. Collapse suddenly
  9. Patients and providers are left scrambling

Money and engineering talent are not substitutes for:

  • clinical insight
  • regulatory design
  • healthcare economics
  • trust-building
  • real-world workflow alignment

The Hard Truth

Healthcare rewards reliability over innovation.

Simple solutions outperform brilliant ones.

Integration beats disruption every time.

I’ve watched billion-dollar firms fail and small scrappy teams succeed.

The winners understood healthcare is a trust-based, evidence-driven system.

The losers thought they could brute force the market with capital and code.

They were wrong.

Your Turn

What healthcare product promised everything and delivered nothing?

If you wanna share your experiences, you can find me online in all your favorite places  LinkedIn and Facebook. Shoot me a DM, a tweet, a comment, or whatever works best for you. I’ll be the one trying to figure out how to read books and get better at playing ping pong at the same time.

 
 

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Top 20 Electronic Health Records (EHR) Systems in the World


Each minute of our life is a lesson but most of us fail to read it. I thought I would just add my daily lessons and the lessons that I learned by seeing the people around here. So it may be useful for you and as memories for me.

Digital transformation in healthcare continues to accelerate in 2025, with electronic medical records (EMR) and electronic health records (EHR) at the core of operational efficiency, patient engagement, and regulatory compliance. For healthcare businesses—ranging from multi-specialty hospitals to outpatient clinics—open source EHR/EMR platforms provide a unique combination of affordability, scalability, and adaptability.

In today’s healthcare ecosystem, Electronic Health Records (EHRs) are no longer just digital files they are the backbone of modern patient care. They provide clinicians with real-time access to a single, unified patient record, ensuring safer decision-making, fewer delays, and more time focused on patients rather than paperwork.

https://www.doctorsapp.in/blog/top-ehr-vendors

From my own work in healthcare, I’ve seen firsthand how difficult it can be for clinicians to deliver quality care without proper EHR systems. Consultations often get slowed down by flipping through scattered files, repeating lab tests because past results aren’t visible, or relying purely on memory to track complex patient histories. These gaps don’t just frustrate clinicians they can compromise patient safety and the overall patient experience.

An Electronic Health Record (EHR) is a type of healthcare software that digitally collects, organizes, and shares patient information. It ensures that medical data is available in a structured format and can be accessed by all authorized parties involved in patient care — from doctors, labs, and pharmacies to hospitals, registries, and patients themselves.

The idea of an electronic patient record isn’t new. More than 50 years ago, the first prototype — called the Problem-Oriented Medical Record (POMR) — was introduced. It brought together a patient’s full clinical history, a list of health problems, a treatment plan, daily progress notes, and a discharge summary. This framework set the stage for the EHRs we use today, with their focus on comprehensive records and continuity of care.

This is where effective EHRs make the difference. They:

  • Centralize patient data across clinics, hospitals, and pharmacies.
  • Reduce errors with accurate records of labs, allergies, and prescriptions.
  • Improve efficiency, freeing up more time for clinicians to engage with patients.
  • Enable population health insights, helping health systems manage risks and improve long-term outcomes.

In short, EHRs empower providers to deliver better, safer, and more connected care. Below is a look at the Top 20 EHR systems worldwide, their origins, and standout features.

1. Epic Systems

  • Country: United States
  • Developer: Epic Systems Corporation
  • Features: Large hospital and academic medical center focus; interoperability; analytics and population health management; widely recognized leader in usability and scale.

2. Oracle Health (Cerner)

  • Country: United States
  • Developer: Oracle Health (formerly Cerner)
  • Features: Millennium platform; strong in hospitals and government health projects; open APIs; global presence; AI-driven decision support.

3. MEDITECH

  • Country: United States
  • Developer: MEDITECH Inc.
  • Features: Acute/community hospital focus; scalable for small hospitals; strong workflows for clinicians; growing international footprint.

4. Athenahealth

  • Country: United States
  • Developer: Athenahealth, Inc.
  • Features: Cloud-based; practice management, billing, telehealth; population health insights; ideal for ambulatory/outpatient practices.

5. NextGen Healthcare

  • Country: United States
  • Developer: NextGen Healthcare, Inc.
  • Features: Specialty-specific templates; patient portal and telehealth; revenue cycle management; good fit for mid-sized practices.

6. eClinicalWorks (eCW)

  • Country: United States
  • Developer: eClinicalWorks
  • Features: Cloud/mobile EHR; telehealth and patient engagement tools; affordable for small-medium practices; population health integration.

7. Greenway Health

  • Country: United States
  • Developer: Greenway Health, LLC
  • Features: Ambulatory EHR; built-in RCM; customizable workflows; responsive customer support.

8. Veradigm (Allscripts)

  • Country: United States
  • Developer: Veradigm (formerly Allscripts)
  • Features: Ambulatory solutions with open APIs; scheduling and billing; modular design for specialties; broad adoption across practices.

9. Practice Fusion

  • Country: United States
  • Developer: Veradigm (Practice Fusion)
  • Features: Affordable, web-based EHR; e-prescribing; lab integration; best for small practices.

10. AdvancedMD

  • Country: United States
  • Developer: AdvancedMD, Inc.
  • Features: SaaS-based EHR; telemedicine; customizable templates; analytics; tailored for small-to-mid practices.

11. Dedalus

  • Country: Italy
  • Developer: Dedalus Group
  • Features: Europe’s largest health IT vendor; integrated EHR, lab, and imaging systems; focus on interoperability across EU; strong NHS presence.

12. InterSystems TrakCare

  • Country: United States
  • Developer: InterSystems Corporation
  • Features: Global EHR with strong adoption in Europe, Middle East, APAC; unified patient record; advanced analytics and FHIR support.

13. EMIS Health

  • Country: United Kingdom
  • Developer: EMIS Health (part of Optum)
  • Features: Market leader in UK primary care; EMIS Web widely used; prescription ordering, patient portals; integration across GP and pharmacy.

14. SystmOne (TPP)

  • Country: United Kingdom
  • Developer: The Phoenix Partnership (TPP)
  • Features: Widely used in UK NHS primary and community care; real-time record sharing; mobile access for clinicians.

15. Vision (Cegedim)

  • Country: United Kingdom
  • Developer: Cegedim Healthcare Solutions
  • Features: Primary care EHR in the UK; intuitive prescribing; data sharing across practices; strong GP usability.

16. CareCloud

  • Country: United States
  • Developer: CareCloud, Inc.
  • Features: Cloud-based EHR + practice management; RCM and billing; telemedicine; customizable and user-friendly.

17. DrChrono

  • Country: United States
  • Developer: DrChrono, Inc.
  • Features: Mobile-first on iPad/iPhone; appointment scheduling; telehealth; ideal for small-mid practices.

18. Kareo Clinical

  • Country: United States
  • Developer: Kareo, Inc.
  • Features: Cloud-based; integrated billing and RCM; patient engagement; affordable for independent practices.

19. ModMed (Modernizing Medicine)

  • Country: United States
  • Developer: Modernizing Medicine, Inc.
  • Features: Specialty-specific EHRs (dermatology, ophthalmology, etc.); AI-powered coding/documentation; telehealth and analytics.

20. GE Healthcare (Centricity / Virence)

  • Country: United States
  • Developer: GE Healthcare
  • Features: Enterprise hospital deployments; integration with imaging; clinical documentation and order entry; still influential in hospital IT.

Final Thoughts

EHRs are not one-size-fits-all. While giants like Epic and Oracle Health dominate global hospitals, regional leaders like EMIS, SystmOne, and Vision play a vital role in UK primary care. Similarly, agile systems like DrChrono or Kareo empower small practices with affordable, cloud-based tools.

The real value of an EHR lies in how well it supports clinicians and patients together — enabling safer care, reducing waste, and building trust. As healthcare continues to digitalize, these systems will shape the future of how we deliver care worldwide.

If you wanna share your experiences, you can find me online in all your favorite places  LinkedIn and Facebook. Shoot me a DM, a tweet, a comment, or whatever works best for you. I’ll be the one trying to figure out how to read books and get better at playing ping pong at the same time.

 
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Posted by on September 2, 2025 in Technical, Work Place

 

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