Pattern differentiation (pattern differentiation) organizes findings into a Chinese-medicine pattern that guides the treatment principle and point prescription. In a SOAP note, it usually belongs in Assessment—but its evidence is distributed across Subjective and Objective.
For licensed-practitioner education. This article is not patient-specific medical advice and does not recommend diagnosis or treatment.
The SOAP structure and pattern differentiation answer different questions
SOAP is a documentation architecture: what was reported, what was observed, what the practitioner concluded, and what was planned. Pattern differentiation is a clinical reasoning process within that architecture. The two can coexist when the note preserves the path between them.
Problems arise when the pattern appears as an unexplained label in Assessment or when theoretical language is scattered through every section. A clearer approach is to record findings where they belong, synthesize the proposed pattern in Assessment, and connect it to a treatment principle in Plan.
Build the pattern from explicit findings
A defensible Assessment names the findings that support the proposed pattern. Those findings may include symptom quality and timing, temperature preference, energy, appetite, sleep, emotional context, tongue appearance, pulse qualities, and other relevant observations. Not every finding has equal weight, and no fixed checklist replaces professional judgment.
When the evidence is incomplete, document that. “Findings suggest” is often more faithful than a categorical declaration. Mixed presentations can be represented as primary and secondary patterns or as a working pattern with alternatives to reassess.
Use frameworks as lenses, not automatic labels
Eight Principles (Eight Principles) can help characterize interior or exterior, cold or heat, deficiency or excess, and yin or yang dimensions. Zang-Fu (Zang-Fu) patterns organize functional relationships using Chinese-medicine theory. Root and branch (root and branch) can clarify the relationship between an underlying pattern and the immediate presentation.
These frameworks guide interpretation; they are not menu items to select because a few keywords match. Good software should surface why a possible pattern was considered and which findings do not fit, leaving the clinician to evaluate relevance.
Make the treatment principle the bridge
The treatment principle (treatment principle) is the bridge between Assessment and Plan. It states the strategic direction derived from the pattern. Without that bridge, a point list can appear disconnected from the reasoning that produced it.
A concise note may state the working pattern, supporting findings, and treatment principle in two or three sentences. The Plan can then list the point prescription and briefly explain the role of important point groups. The amount of detail should fit the clinical, legal, and educational context.
Preserve uncertainty and change over time
Patterns can evolve across visits as signs change and new information appears. Documentation should make that change visible. Copying the same Assessment forward can obscure whether the practitioner reassessed the presentation.
A useful longitudinal note identifies what changed, what remained stable, and whether the treatment principle was continued or revised. This is especially important for any AI-assisted draft: yesterday’s pattern should never become today’s conclusion by default.
What decision-support software should show
A pattern-support tool should separate patient-reported facts, practitioner observations, retrieved source excerpts, and generated suggestions. It should let the practitioner inspect the reasoning path, identify unsupported statements, and revise the output before it becomes part of the record.
ASKLEMER is being designed to assist with this structure and cited review. It is not intended to diagnose or replace the practitioner’s interpretation.
Key takeaway
Clinical AI is most useful when it keeps facts, inferences, sources, and practitioner decisions distinct. ASKLEMER is in development and makes no claim of clinical performance or availability.