Oct 5, 2025
6
min read
Medically Reviewed
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The Root of the Problem: Why Under-Billing is So Pervasive
Under-billing is not a result of clinical negligence; it is a direct consequence of a high-pressure environment and inadequate tools. A GP's primary focus during a consultation is, and should be, the patient. Their mental energy is dedicated to listening, diagnosing, and formulating a plan. By the end of the appointment, their cognitive resources are depleted. At this point, they are expected to switch from being a clinician to being a medical billing expert, accurately translating the complex, nuanced service they just provided into a series of numeric codes.
This is where the errors occur. A GP might spend 25 minutes on a complex mental health issue but, in the rush to move to the next patient, they default to billing a standard Level B consultation, missing out on the more appropriate and higher-value mental health or prolonged consultation item numbers. They might conduct a comprehensive health assessment for an eligible patient but forget to bill the specific item number associated with it. They might create a GP Management Plan but fail to bill for the plan's creation. These are not deliberate choices; they are oversights driven by a system that places an unreasonable administrative burden on the clinician at the most stressful point in their workflow. This lost revenue, aggregated over hundreds of consultations per week, has a significant and detrimental impact on the practice's bottom line.
The Failure of Non-Contextual "Solutions"
The market has seen the emergence of standalone coding apps and "cheat sheets" designed to help GPs with billing. These point solutions, however, fail to solve the core problem. They require the GP to stop their workflow, open a separate application, and manually search for the relevant information. They are still relying on the GP's memory of what occurred during the consultation. They have no direct, automated knowledge of the consultation's content, duration, or complexity. For example, the app has no way of "knowing" that the GP just performed an iron infusion or created a chronic disease management plan. It is a digital rulebook, not an intelligent assistant. It is still a passive tool that places the entire burden of context and initiation on the clinician. It is a slightly better version of a broken workflow.
Expert Tips
"The key to maximising MBS revenue is not to bill more, but to bill accurately. True accuracy can only come from context. An integrated AI that can analyse the content of the clinical note in real-time is the only tool that can provide the context-aware suggestions needed to ensure your billing perfectly and compliantly reflects the value of the care you provide." - Arash Zohuri, CEO, MediQo
The Unified Platform Advantage: Real-Time, Context-Aware Billing Suggestions
The true solution lies in an AI that can see and understand the full context of the consultation as it happens. This is a capability that is exclusive to a unified clinical automation platform. The "Platform Advantage" is that the billing assistant is not a separate, blind tool but a deeply integrated module that works in concert with the clinical documentation engine. This is the function of MediQo's Smart MBS Billing Assistant.
Here's how this seamless, context-aware workflow unfolds:
Real-Time Consultation Capture: During the consultation, the GP is not typing extensive notes. They are focused on the patient, while the Clinical Assistant module is working in the background. Using sophisticated ambient documentation and Natural Language Understanding, it is capturing the key elements of the conversation as structured, FHIR-aligned data.
Intelligent Content Analysis: The AI is not just transcribing; it is understanding. It recognises clinical concepts. It "knows" when the conversation is about mental health, when a chronic disease management plan is being formulated, when specific procedures like an ECG are mentioned, and it accurately logs the consultation's duration.
Context-Driven Suggestions: At the conclusion of the consultation, the Smart MBS Billing Assistant uses this rich, structured data to provide a list of highly relevant, compliant item number suggestions. It is not guessing; it is making a data-driven recommendation.
For example, the AI might have detected that the consultation lasted for over 20 minutes and the notes created by the Clinical Assistant contain extensive details about managing the patient's anxiety and depression. Based on this context, the Smart MBS Billing Assistant will proactively prompt the GP to consider billing a Level C consultation or a specific Mental Health item number, rather than the default Level B. It can present these options to the clinician for their final review and one-click approval. The system has done the heavy lifting of analysis and recall, leaving the GP to perform the simple, high-value task of confirmation.
Key Takeaways
Prioritizing Ethical AI Implementation
Optimizing Practice Efficiency and Revenue
The Power of Unified Platforms
Strategic Innovation for Sustainable Growth
Running a successful medical clinic in Australia is a complex balancing act. At its heart, it is a mission-driven endeavour focused on providing the highest quality of patient care. At the same time, it is a business that must remain financially viable in an environment of rising costs and increasing administrative complexity. One of the most significant challenges in maintaining this financial health is the intricate and often bewildering nature of the Medicare Benefits Schedule (MBS). The MBS is a vast and constantly evolving rulebook, and for a time-poor General Practitioner, navigating it at the end of a busy consultation is a major source of cognitive load. This complexity inevitably leads to under-billing—a chronic and costly problem where clinicians, either through lack of time, fear of non-compliance, or simple oversight, fail to claim for the full value of the services they have provided.
The traditional tools for billing, typically the basic billing modules within a Practice Management Software (PMS), are passive and unhelpful. They are "dumb" databases that require the GP to know exactly which item number they are looking for and to enter it manually. This is not a support system; it is a simple data-entry tool. In response, a new generation of AI-powered coding assistance has emerged, promising to solve this problem. However, the effectiveness of these tools is entirely dependent on one critical factor: context. A standalone billing app or a simple "point solution" that is not connected to the clinical record is operating blind. True, accurate, and compliant MBS maximisation can only be achieved through a deeply integrated AI assistant that is a native part of a unified clinical automation platform, where it has the unique ability to analyse the rich context of the consultation in real-time.
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