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Experience the Future with Cellma

AI-Powered Voice Recognition Technology in Healthcare for Faster, Smarter Clinical Documentation.
Schedule A Walkthrough

Experience the Future with Cellma

AI-Powered Voice Recognition Technology in Healthcare for Faster, Smarter Clinical Documentation.

Schedule A Walkthrough

EHR’s Smarter Documentation with Voice Recognition Technology in Healthcare

RioMed’s Cellma Voice Recognition & Documentation Solution integrates advanced voice recognition technology in healthcare to improve how clinicians and healthcare practitioners around the world capture and document patient information. Fully integrated with CellmaEHR and CellmaPMS, this intelligent speech recognition healthcare solution allows clinicians and healthcare practitioners to dictate notes, orders and reports naturally – reducing administrative burden and increasing the time spent on patient interaction.

Built for global healthcare environments, Cellma’s voice recognition healthcare platform understands medical terminology, regional accents, multilingual speech patterns and specialty-specific language. The solution supports a wide array of international healthcare delivery models and regulatory frameworks to provide secure, compliant and scalable documentation for hospitals, private practices and community care organisations worldwide.

Clinical Voice Recognition Features - Inside Facility

Seamless Dictation, Instant Documentation

Cellma’s in-facility voice recognition technology in healthcare accelerates documentation workflows across hospital departments, outpatient clinics, diagnostic units, and speciality centres worldwide.

Use Cases Covered:

Real-time dictation of clinical notes during the consultation

Voice-driven prescription and medication order entry

Automated creation of discharge summaries, care reports and referral letters

Operative and procedural reporting in the surgical setting

Radiology, pathology, and diagnostic reporting via dictation

How It Works via Cellma EHR:

  • AI-enabled speech recognition engine embedded directly into the Cellma EHR user interface

  • Medical vocabulary is context-aware and also adapts specialty-specific dictionaries for cardiology, orthopaedics, paediatrics, and more

  • Notes, discharge summaries and letters are autoformatted  based on user defined templates

  • Use voice commands to navigate patient records, enter data and initiate workflows

  • Multi-user adaptive voice profiles learn and improve with each use

Clinicians, nurses and staff within healthcare settings can experience documentation that is high-accuracy and hands-free, resulting in reduced
typing time and improved consistency regardless of location.

Remote Voice Documentation Capabilities - Outside Facility

Mobile Voice Documentation for Community and Remote Care

The Cellma solution extends the power of speech recognition healthcare outside of traditional healthcare settings and supports community care teams,
mobile clinicians, outreach units, telehealth providers, and emergency response staff across the globe.

Use Cases Covered:

Telehealth and virtual consultation documentation

Mental health and behavioural health field assessments

Care home, long-term care, and residential facility evaluations

Outreach and follow-up programme documentation

How It Works via Cellma EHR:

  • Secure cloud-based voice processing with full offline functionality for limited-connectivity areas

  • Mobile friendly interface for smartphones, tablets and portable clinical devices

  • Automatic syncing of dictated notes once back online

  • Prompted questions based upon a patient’s history and care pathway context

  • Voice initiated prompts for decision support while documenting notes
This feature-rich mobility allows clinicians the ability to quickly and securely document care, keeping patient records updated in near real time and comprehensively over their care teams.

Efficiency, Accuracy, and Integration for Modern Healthcare

Cellma empowers healthcare organisations internationally to improve clinical productivity, strengthen documentation quality, and enhance patient care delivery.
  • 40–60% reduction in clinical documentation time through natural voice input 
  • Enhanced accuracy with specialty-aware medical terminology and adaptive learning 
  • Improved clinician satisfaction and reduced burnout from repetitive data entry 
  • Seamless integration with CellmaEHR and CellmaPMS, no switching between systems 
  • Full compliance with NHS Digital, GDPR, and data protection regulations 
  • Significant cost savings through reduced transcription services and faster turnaround 
  • High scalability for large hospital networks, multi-site providers, and national healthcare systems 

Frequently Asked Questions (FAQs)

How accurate is the voice recognition technology with medical terminology and global accents?
The Cellma engine delivers over 98% accuracy, trained on extensive clinical datasets and capable of understanding global accents, multilingual contexts, and specialty-specific terminology. Adaptive learning improves accuracy for individual users over time.
Does the speech recognition healthcare solution integrate with existing EHR systems?
Yes. It is a native component of Cellma EHR, operating directly within its interface. No application switching is required, ensuring smooth integration with current workflows and templates.
Is patient data secure when using voice recognition for healthcare documentation?
Absolutely. All data is securely encrypted end-to-end and processed using infrastructure aligned with international data protection regulations. For the UK, processing complies with NHS Digital’s DSP Toolkit and GDPR. Data is never stored as raw audio — only the final transcribed text is saved.
Can the system be used in noisy clinical environments like emergency departments?
Yes. The solution incorporates advanced noise-cancellation algorithms and hardware compatibility with clinical-grade microphones, ensuring reliable performance in busy wards, emergency units, operating theatres, and outpatient clinics.
How long does it take for clinicians to adapt to using voice recognition technology in healthcare?
Most clinicians achieve proficiency within 2–3 weeks. With built-in adaptive learning, specialty-specific command sets, and global training support, users quickly experience productivity gains and improved documentation speed.