Medicomp Systems

Our clinical engine works seamlessly with any #EHR to deliver diagnostically relevant & actionable information to clinicians at the #PointOfCare. | #UsableData

[Medicomp Systems @MedicompSys]

.@ONC_HealthIT finalized a rule cutting 14 of 60 health IT certification criteria and shifting toward FHIR APIs. Most changes start Dec. 28.

With fewer federal requirements, it’s on vendors & health systems to keep exchanged data accurate & usable.

👨‍💻 https://t.co/g5Pb7wHtwS

[Medicomp Systems @MedicompSys]

One ICD-10 code for Charcot-Marie-Tooth disease leaves out 61 more specific variants.

Medicomp CMO @medicompdoc on why ambient AI should capture the clinical detail, not just the billing code.

https://t.co/XmPA48UQrN

[Medicomp Systems @MedicompSys]

72% of healthcare leaders say agentic AI tools are sometimes implemented without IT approval.

@AmerMedicalAssn’s new governance framework asks a key question: Who is responsible for the risks and outcomes?

Via @HealthcareDive:
https://t.co/HtBZVrxyyM

[Medicomp Systems @MedicompSys]

Usable clinical data starts with consistent, up-to-date terminology. Putting regulatory context, implementation guides, and terminology content in one place is a welcome step for interoperability.

[Office of the National Coordinator for Health IT @ONC_HealthIT]

Cartos is ONC’s Terminology Service that streamlines and simplifies the process of finding up-to-date and correct terminology assets by bringing together:

🔹 regulatory context
🔹 implementation guide references
🔹 terminology metadata
🔹 terminology content

...All in one convenient location. 📍

Learn more: https://t.co/vxttT0az4f

[Medicomp Systems @MedicompSys]

Only 6% of Americans would let AI read medical scans on its own, but 60% are open to it with human review, per @pewresearch via @BeckersHR.

AI works best with a clinician in the loop.

https://t.co/PfHQsIJprg

[Medicomp Systems @MedicompSys]

Accuracy is the top barrier to AI adoption in private practice, cited by 32% of providers in a new @Tebra report.

Patients have concerns too: 91% want their permission required every time AI is used for diagnosis or treatment.

https://t.co/kUZMJcQbSz

[Medicomp Systems @MedicompSys]

What happens when inaccurate AI-generated information ends up in a patient’s medical record?

Medicomp CMO @medicompdoc explains why governance has to be built into healthcare AI from the start, on the Provider’s Edge podcast.

https://t.co/fxNG9qdXKD

[Medicomp Systems @MedicompSys]

An AI tool can get the claim right and still miss what matters for the patient.

Medicomp CMO @medicompdoc explains why AI billing tools are failing patient care, via @MedEconomics.

https://t.co/Z7iCd0UDgw

[Medicomp Systems @MedicompSys]

AI agents could speed up clinical trial matching, but one study found LLMs hallucinated 21% to 49.5% of the time when turning eligibility criteria into database queries.

Accurate matching starts with structured, validated clinical and genomic data.

https://t.co/nHY4LQj3yl

[Medicomp Systems @MedicompSys]

Clinicians make better decisions when the data in front of them is accurate and structured.

That’s the goal behind our partnership with @greenway. #Engage2026

https://t.co/mhoRH4scEe

[Medicomp Systems @MedicompSys]

LLMs are powerful, but they aren’t the right tool for every job.

Medicomp CMO @medicompdoc explains where they fall short in medical coding.

https://t.co/39kD4pZSk3

[Medicomp Systems @MedicompSys]

Accountability starts with transparency. Clinicians can only stand behind an AI output if they can see the clinical evidence behind it.

[FierceHealthIT @FierceHealthIT]

Who’s responsible when clinical AI goes wrong? @AmerMedicalAssn weighs in
https://t.co/crfCkcrs6x

[Medicomp Systems @MedicompSys]

87% of patients who start answering ChronicCareIQ’s check-in questions are still responding a year later.

@ChronicCareIQ CEO Matt Ethington tells @medicompdoc how staying connected between visits changes chronic care on the Tell Me Where IT Hurts podcast.
https://t.co/0t7S4fEQAW

[Medicomp Systems @MedicompSys]

Only 59.4% of chronic conditions are captured consistently across diagnoses and problem lists, and that’s before AI is added.

Medicomp CEO David Lareau on why AI coding errors can spread fast, in @DOTmed.

https://t.co/S5U9uiGbOf

[Medicomp Systems @MedicompSys]

78% of organizations say they trust AI. Only 40% have invested in making it trustworthy.

@TechTargetNews on why transparency and explainability matter as much as accuracy.

https://t.co/GDYu6SXDuS

[Medicomp Systems @MedicompSys]

Is a human in the loop enough to keep generative AI safe? The @AmerMedicalAssn says not necessarily. In comments to the @US_FDA, it warned that clinicians can make errors reviewing AI suggestions or become over-reliant on the tools.

Via @HealthcareDive:
https://t.co/DUii7IRPtb

[Medicomp Systems @MedicompSys]

Only 3% of Americans are open to AI making a diagnosis on its own, and 60% are uneasy with doctors using AI for diagnosis and treatment, per a new @PewTrusts survey via @BeckersHR.

Patients want a human making the final call.

https://t.co/PfHQsIJprg

[Medicomp Systems @MedicompSys]

If physicians won’t seek care in their own health system because of privacy worries, what does that say about trust in the EHR? An important read from @medcitynews.

[MedCity News @medcitynews]

Physician Mental Health and Health System Privacy: Why Doctors Avoid Their Own EHR https://t.co/GkDuxfPrcP

[Medicomp Systems @MedicompSys]

“Clinical authority should be earned through evidence and maintained through demonstrated performance.”

That’s the core principle behind @AmerMedicalAssn’s new governance framework for agentic AI in clinical care.

https://t.co/WhDkJOnA1G

[Medicomp Systems @MedicompSys]

A billing code pays the claim. A diagnosis treats the patient.

Medicomp CMO @medicompdoc on the “clinical context gap” and why ambient AI should start with the clinical picture, not the code.

https://t.co/XmPA48UQrN