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Electronic Health Records (EHRs) and Electronic Medical Records (EMRs) were initially developed to substitute for physical files, render patient information traceable, and accelerate access to medical history. Today, however, healthcare has moved past information technology systems that simply house information, healthcare needs digital platforms that can think, assist, and act.
That shift is already well underway. Globally, 86% of healthcare organisations report that they are already using or actively planning AI-driven capabilities within their EHR or EMR systems, while more than 73% are piloting or deploying AI in core functions such as clinical decision support, risk prediction, automation, or patient communication. At the leadership level, over 80% of health executives say AI, including generative AI, will significantly reshape care delivery by the end of 2025, and 84% specifically believe AI will influence clinical decision-making in the near term. Meanwhile, 80% of organisations expect AI to reduce manual administrative labour, signalling a shift from data entry systems to true clinical assistants.
The scale of data behind this transformation is immense. Healthcare already generates around 30% of the world’s total data, and the volume is growing at 36% per year, making AI not just an advantage, but the only practical way to extract real-time insights from rapidly expanding patient datasets. Areas such as Europe are now among the leading global adopters as a result of various national digital health mandates, while newer health systems are leveraging AI-enabled EHRs to address staffing challenges, automate triage and increase access to care. Early adopters have already seen impact: 40% report measurable operational improvements due to AI-enabled EHR workflows, ranging from faster coding to shorter wait for diagnoses.
The UK is rapidly progressing towards an AI-enabled healthcare model. The NHS England 10-Year Plan clarifies the critical need for AI and data to help reduce pressure on staff, improve clinical accuracy and provide care that is more predictive and personalised. Across the system, more than half of NHS Trusts are currently piloting or rolling out AI tools, with an additional hundreds of trials supported by the NHS. An NHS report of productivity also recently highlighted that staff could save up to 43 minutes each person each day with the use of AI tools, demonstrating the real impact on the day-to-day operation in care delivery.
Artificial Intelligence is no longer an optional add-on to health records, it is redefining digital healthcare. Instead of passive repositories, AI enables digital healthcare to become active clinical partners that predict risk, guide decision-making, prevent errors, automate repetitive workflows, and personalise care at scale.
As NHS Trusts, hospitals, and healthcare providers move toward fully connected care ecosystems, the question is no longer “Do we need AI in healthcare?” but “How intelligently is AI being built into our EHR and EMR systems, and is it truly improving care?”
AI is bringing a wide range of capabilities into modern EHR and EMR systems — and the examples below are just a few of the many ways it is reshaping digital healthcare. All of them focus on reducing manual work, improving clinical accuracy, and turning raw data into meaningful, real-time insight for care teams.
AI Capability | What It Means in Real Care Settings |
Predictive Analytics | Identifies high-risk patients, readmission probability, disease progression |
Clinical Decision Support | Suggests evidence-based interventions and flags risks before they occur |
NLP (Natural Language Processing) | Converts free-text notes into structured, usable data |
Workflow Automation | Auto-handles referrals, reminders, coding, authorisations |
Patient Engagement Intelligence | Sends smart alerts, follow-up prompts, remote check-ins |
Clinical Documentation – Ambient Voice AI | Listens during consultations and automatically generates structured clinical notes, dramatically reducing documentation time |
AI-Enabled Revenue Cycle Management | Auto-captures charges, predicts potential claim denials, validates coding accuracy, and supports faster billing cycles |
This shift is no longer futuristic. It’s already visible in radiology reporting, oncology treatment pathways, early diabetes risk modelling, population health dashboards, etc.
In other words, AI is not replacing clinicians, it’s removing everything that gets in their way.
Where Traditional EHRs Still Fall Short
Even some of the most widely used EHRs today suffer from:
This is the exact gap AI-filled EHRs are built to solve, and it’s the space where platforms like Cellma are already delivering results.
Cellma isn’t just a digital record system, it is an AI-enabled healthcare platform built to support clinicians, engage patients, and help organisations move toward predictive and personalised care.
This is how AI operates within Cellma:
AI-Based Clinical Decision Support
Cellma supports clinicians by:
The outcome? Safer care, fewer clinical errors, and quicker decision-making.
Predictive Analytics for Risk & Population Health
Cellma uses past and real-time data to help identify:
This enables both preventative care and future NHS long-term planning.
NLP for Clinical Notes
Natural Language Processing (NLP) is one of the most impactful AI capabilities built into modern EHR and EMR systems. Instead of forcing clinicians to rely on heavy typing, rigid templates, or endless dropdowns, NLP allows them to document in the way that feels most natural, while the system does the structuring in the background.
How it works:
Automated Workflows
Cellma applies AI logic to route:
What was once manual becomes automatic, saving hours of administrative time per department.
AI + Power BI Integrated Dashboards
Unlike static reporting, Cellma offers live intelligence dashboards. Healthcare leaders can track:
Eliminates manual data exports and spreadsheets, providing validated, real-time clinical insight.
Patient Engagement Using Automated Alerts
Patients receive intelligent SMS, email, or portal reminders for:
Using AI, we target the right message to the right patient at the right time.
AI Triage
With Cellma, we can prioritise patients based on:
This supports safer referral management and reduces time-to-care.
Artificial intelligence in healthcare cannot be technology that operates in a “black box” setting.
At Cellma, we follow international and NHS standards for safety and data governance, which include:
All AI models used within Cellma are auditable, transparent, and designed with patient safety in mind.
The Future: From EHR Systems to Intelligent Health Platforms
In the coming decade, AI integrated systems like Cellma will facilitate:
✅ Auto trigger alerts from remote monitoring
✅ Early warning scores derived from live vitals
✅ AI triaged waiting lists
✅ Personalised long term condition pathways
✅ Fully automated discharge/referral flows
✅ Predictive workforce/bed management
The hospital of the future will not only be paperless – it will be data driven, predictive and clinically contextualised.
AI is not just another healthcare software ‘trend’. It is the pillar for our next era of clinical care. The EHR will not only be a record keeping tool anymore: it is becoming an intelligent, adaptive system that supports clinicians, promotes patient safety and supports NHS strategy.
With AI-powered decision support, predictive analytics, automated workflows, and real-time insight dashboards, Cellma is already shaping this future, not waiting for it.
Curious how AI actually changes clinical workflows? Let us show you. Book a demo and experience Cellma in action.
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Cellma features tools that are powered by AI and clinical decision support that reviews patient data in real time to offer evidence-based interventions, recognise and flag risk, facilitating clinicians in making quicker, safer, and better-informed decisions.
Cellma's intelligent automation supports time-consuming and repetitive activities, including referrals, coding, and reminders. It also employs predictive analytics and NLP to interpret clinical notes, allowing clinicians to save time and provide more direct patient care.
Cellma enables clinician and patient engagement through AI prompts, alerts, triage support, and follow-up. Additionally, clinicians are able to identify higher-risk patients sooner, which leads to increased patient satisfaction and improved outcomes.
