ACC & ICD-10-AM Billing Suggestions
Prevent clinical coding leakage. Scan consultation notes ambiently and suggest compliant ACC injury codes and diagnostic codes at point of care.
Live ACC Billing Audit suggestions
See how our AI extracts claim codes from clinical transcripts.
GP Consultation - Accident Compensation Claim
Patient presented with ankle sprain from a recent slip, requiring initial filing of ACC45 form.
Sprain and strain of ankle joint ligaments
Supports ACC45 classification for ligamentous damage of the lateral ankle.
ACC Billing Code & ICD-10-AM Suggestion Generator
Kiwi healthcare professionals are all too familiar with the daily administrative challenge of filing Accident Compensation Corporation (ACC) claims. In New Zealand’s universal, no-fault accident insurance system, General Practitioners, specialists, and allied health providers must file an ACC45 injury claim form for every patient who presents with a trauma-related condition. Completing this documentation requires matching the patient’s narrative to specific clinical codes.
However, searching for and selecting these codes manually is time-consuming and prone to errors. DocReport introduces an AI-powered billing suggestion engine that analyzes the natural spoken dialogue of a patient consultation to instantly suggest the correct ACC billing codes, ICD-10-AM classifications, Read Codes, and Southern Cross Easy-claim codes.
Streamlining Accident Compensation Claims (ACC45) for Primary Care
In a typical primary care setting, the filing of an ACC45 claim happens under intense time pressure. A patient might present with a complex range of injuries from a motor vehicle accident, a sports injury, or a workplace slip. To submit the claim, the clinician must document:
- The date and time of the injury.
- The specific location and setting where the accident occurred (e.g., home, work, sports field).
- The exact mechanism of the injury (e.g., twisting, falling, lifting).
- The clinical diagnosis, mapped to the correct diagnostic codes.
Ambient Scribe Capture
Identify Mechanism & Sites
Local Coding Mapping
ACC & Southern Cross Codes
Clipboard Copy-Paste
Automated Injury Code Selection & Read Code Mapping
GPs and primary care clinics in New Zealand still rely heavily on the legacy Read Code (v2) system within Practice Management Systems like Medtech and MyPractice. When a doctor has to manually search the PMS code database for a diagnosis, they are often faced with an overwhelming list of search results. For example, typing "wrist sprain" might return dozens of choices, ranging from specific ligamentous tears to generic pain codes.
DocReport’s ambient AI eliminates this manual searching. As the patient explains how they tripped on a garden path and landed on an outstretched hand, the AI processes the context of the injury. It automatically identifies the affected anatomy (the wrist) and the mechanism (fall from standing height).
The system then displays the correct Read Code suggestions (e.g., S51.. for sprain of wrist) and the corresponding ACC injury classification code directly alongside the consultation summary. This allows the clinician or administrative staff to quickly select the correct code and move on to the next patient.
Reducing Claim Rejections and Audit Flags
Incorrect coding has direct financial and administrative consequences. When an ACC45 is submitted with a code that does not match the clinical description of the accident, the claim is often flagged for review or declined. For example, if the clinical note describes a laceration but the billing code indicates a contusion, ACC may reject the claim, triggering an administrative review.
This requires the clinic to spend time resubmitting forms and delays the funding of necessary patient treatments, such as physiotherapy or specialist assessments. DocReport helps prevent these rejections by ensuring that the suggested codes are always consistent with the documented clinical narrative, lowering rejection rates and protecting clinics from administrative audits.
Support for Hospital and Specialist ICD-10-AM Clinical Coding
For specialists, private surgical clinics, and private hospital facilities, coding requirements are even more complex. These organizations do not use GP Read Codes; instead, they must code diagnoses using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) and classify procedures using the Australian Classification of Health Interventions (ACHI).
| Code System | Main User Base in NZ | Purpose | DocReport Automation |
|---|---|---|---|
| Read Codes (v2) | General Practitioners | Legacy GP consultation logging | Contextual extraction of primary & secondary diagnoses |
| SNOMED CT NZ | Modern GP Clinics & PHOs | Standardized terminology transition | Direct mapping from narrative terms to SNOMED codes |
| ICD-10-AM | Specialists & Private Hospitals | Diagnostic coding for private insurance & ACC | Automatic suggestion of primary, secondary, and external cause codes |
| ACHI | Surgeons & Surgical Centers | Procedure coding for private billing | Matches procedural transcript to standard intervention codes |
Australian Modification (ICD-10-AM) and ACHI Classifications
Surgical and specialist coding requires identifying the primary diagnosis, any co-morbidities (secondary diagnoses), and the specific surgical interventions performed. For example, a specialist performing an arthroscopic repair of a torn rotator cuff must document the tear (e.g., M75.1 - Rotator cuff syndrome), the external cause of the injury (e.g., Y92.3 - Sports area), and the procedure itself (e.g., 90320-00 - Arthroscopic reconstruction of shoulder).
DocReport’s clinical coding engine is trained on the ICD-10-AM and ACHI classification systems. As the surgeon dictates their post-operative report or discusses the surgical findings with the patient during a follow-up, the AI identifies the anatomical structures, the pathology, and the specific surgical techniques used.
The software then generates a list of suggested ICD-10-AM diagnostic codes and ACHI procedure codes. This provides the clinic's billing team with a clear starting point, reducing the time spent searching through coding manuals.
Southern Cross Easy-claim Verification
Southern Cross Health Society is New Zealand’s largest private health insurer. For many common procedures, Southern Cross offers the "Easy-claim" service, which allows clinics to submit claims electronically on behalf of the patient at the point of care. However, for a claim to be processed through Easy-claim, the clinic must use the precise billing codes and descriptions specified by Southern Cross.
DocReport features a dedicated Southern Cross verification module. The system flags procedures that qualify for Easy-claim—such as minor skin excisions, consultations, and diagnostic tests—and highlights the exact Southern Cross billing codes and descriptors.
This helps administrative staff process payments immediately, reduces the need for patients to pay upfront and seek reimbursement later, and helps ensure that the clinic is paid correctly and promptly.
How the AI Billing Suggestions Engine Operates
The DocReport billing engine does not replace the clinician’s judgment; instead, it acts as a real-time clinical assistant. It processes the conversation, identifies the relevant clinical details, and presents the most likely codes for the clinician to review.
During the consultation, with the patient's consent, the clinician activates the ambient recorder. The AI looks for specific language patterns related to the injury and the patient's medical history. Within seconds of the recording ending, DocReport parses the transcript, extracts the key details, and generates suggested ACC45 codes, Read Codes, and ICD-10-AM codes alongside the clinical note.
Complete Anonymization & Local Mapping Safeguards:
In accordance with New Zealand’s Health Information Privacy Code 2020 (HIPC 2020), privacy is maintained at every step of the process. Personally identifiable information (PII) and National Health Index (NHI) numbers are redacted directly within the local web browser before the transcript is analyzed by the coding engine. The extraction of clinical entities and the mapping to coding databases are performed on fully anonymized text, ensuring complete compliance with Rules 5 & 11.
Direct Comparison: Traditional Search vs. AI-Assisted Selection
| Operational Step | Traditional Manual Coding | DocReport AI-Assisted Workflow |
|---|---|---|
| Search Method | Typing search terms into PMS; scrolling through generic diagnostic lists. | Automatic extraction of codes based on the ambient consultation transcript. |
| Time Spent | 3 to 6 minutes per patient lookup. | Less than 5 seconds (review and select). |
| Accuracy | Prone to selecting general or incorrect codes under time pressure. | Highly specific, context-aware coding suggestions. |
| Claim Rejections | Common, due to mismatches between the clinical narrative and billing codes. | Minimal, as suggestions are directly tied to the documented clinical notes. |
| Audit Risk | High, when generic codes are consistently used for complex cases. | Low, due to detailed and specific documentation and coding. |
ACC45 and Southern Cross Billing Code Quick Reference
| Clinical Presentation | Typical ACC Injury | Suggested Read Code | Suggested ICD-10-AM | Southern Cross Category |
|---|---|---|---|---|
| Acute Lumbar Strain | Sprain of lumbar spine | S312. | S39.0 | GP Consultation |
| Rotator Cuff Tear | Sprain of shoulder / rotator cuff | S570. | S46.0 | Specialist Consult / Joint Injection |
| Laceration of Index Finger | Open wound of finger | S553. | S61.0 | Minor Surgery / Excision |
| Lateral Collateral Sprain | Sprain of ankle | S532. | S93.4 | Physiotherapy Assessment |
| Osteoarthritis of Knee | Degenerative joint disease (Knee) | N091. | M17.9 | Specialist Assessment |