Oct 5, 2025
6
min read
Medically Reviewed
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The Limitations of Generic Prompts
To understand how to customise output effectively, one must first understand why standalone tools often fail in this regard. Most basic AI scribes function as "wrappers" for general-purpose Large Language Models. They take the transcript of the conversation and summarise it based on a generic prompt, such as "write a medical note." Because the AI lacks any external context, it defaults to a standard, often Americanised, average of medical writing. It tends to include every detail mentioned, regardless of relevance, resulting in "wall of text" notes that obscure the clinical signal.
Attempts to customise these standalone tools are often limited to simple toggles for length or format. They do not integrate with the specific templates that a clinic uses for a mental health care plan versus a skin check. They do not know the patient’s history, so they cannot filter new information from old. This forces the doctor to perform the cognitive load of formatting the note manually after the AI has generated the text. In contrast, a unified platform approaches customisation structurally. It does not just generate text; it populates specific, customisable fields within the clinic’s established workflow.
Customisation Starts with Context
The secret to a note that matches your style is context. A doctor writes differently when seeing a new patient with a complex undefined presentation compared to a regular patient attending for a routine script renewal. A standalone scribe cannot tell the difference until the consult is over. MediQo, however, utilises its unified architecture to establish this context before the consult begins.
This is achieved through CALLA, the platform’s AI telephony module. CALLA handles the patient booking and captures structured pre-visit intake data. It identifies the intent of the visit—whether it is a standard check-up, a chronic disease review, or an acute injury. This data flows into the History-at-a-Glance feature, which presents a unified clinical timeline to the doctor. When the Clinical Assistant begins to document the consult, it is already informed by this intake data. If the intent is a "routine blood pressure check," the AI knows to prioritise the objective metrics and the medication plan, matching the brevity a doctor would employ for such a visit. If the intent is "complex abdominal pain," the AI prepares for a detailed subjective history. By aligning the AI’s focus with the visit type, the platform mimics the doctor’s own prioritisation filter, producing a note that feels natural and relevant.
Expert Tips
"The goal of an AI scribe isn't to replace your voice; it's to amplify it. The problem with many tools is that they try to guess your style from zero context. That's a guessing game you will always lose. The 'Platform Advantage' is that we don't guess. We know the patient, we know the template, and we know the workflow. When you have that level of integration, the AI stops writing generic summaries and starts writing your notes. It becomes an extension of your professional identity, not just a dictaphone." — Arash Zohuri, CEO, MediQo
Leveraging Customisable Note Templates
The most powerful tool for matching an AI scribe to your personal style is the use of customisable note templates. Every clinic has preferred ways of documenting specific conditions. For example, a skin cancer clinic will have a specific structure for documenting lesion characteristics, while a family practice might have a specific template for a 45-year-old health check.
MediQo’s Clinical Assistant is designed to work within these constraints. Rather than generating a free-form block of text, the AI can be directed to populate specific clinic-approved templates. This means the doctor defines the structure—the headings, the required fields, the order of information—and the AI does the heavy lifting of filling it in based on the ambient conversation. This is "structural customisation." It ensures that the note looks exactly how the doctor expects it to look, because the doctor defined the scaffolding. This approach ensures consistency across the practice while allowing individual clinicians to rely on the templates that match their clinical focus. It transforms the AI from a creative writer into a disciplined administrative assistant that follows your specific instructions.
Key Takeaways
AI can be trained to mimic your preferred structure and formatting for clinical notes.
Customisation significantly reduces the time spent on manual editing post-consultation.
Use specific prompts to adjust the tone, ensuring notes are as formal or concise as required.
Maintain high standards of clinical documentation consistency, even when using an automated assistant.
For a General Practitioner, the medical record is far more than a legal requirement or a repository of facts; it is an extension of their clinical reasoning. Every doctor develops a unique "fingerprint" in their documentation style over years of practice. Some prefer succinct, bullet-like brevity that highlights only the critical deviations from the norm. Others prefer a rich, narrative prose that captures the patient’s story in detail. There are those who structure their notes rigidly around the SOAP format, and those who organise by physiological systems. When clinics began adopting early AI scribing tools, the most common complaint was not about accuracy, but about voice. The AI wrote good notes, but they did not sound like the doctor. They were often verbose, overly formal, or structured in a way that clashed with the clinician’s mental model.
The frustration of spending time rewriting an AI-generated note to make it "sound right" defeats the purpose of automation. If you have to edit the output extensively, the efficiency gains are lost. This challenge has led to a demand for greater customisation in AI tools. However, true customisation requires more than just telling a chatbot to "be more concise." It requires a system that understands the context of the consultation, the specific templates of the clinic, and the workflow of the practitioner. This is where the distinction between a standalone scribe app and a unified clinical automation platform becomes critical. A standalone app listens to audio in a vacuum, whereas a platform like MediQo listens with the benefit of deep integration, allowing it to align its output not just with your words, but with your way of working.
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