The Problem
For each patient, staff could need to locate the record, open the correct encounter, verify its state, enter structured note content, add diagnosis codes, save the result, and update another system.
Practice Fusion is a dynamic browser application with loading delays, redirects, lock screens, verification prompts, signed encounters, stale browser state, and UI elements that do not always behave predictably.
Repeated chart work
Patient lookup, encounter navigation, SOAP entry, diagnosis coding, and status reporting required repeated manual steps.
Dynamic EHR state
Loading delays, signed encounters, unavailable elements, and stale sessions made a happy-path script insufficient.
Clinical data safeguards
Diagnosis-code entry required validation and duplicate checks before writing to the chart.
Partial failures
A missing encounter or rejected code needed a visible, recoverable outcome without stopping the full batch.
The Solution
1. Establish a usable session
A bot-specific Chrome profile is launched and the current authentication state is checked. Login, lock, and verification states are handled or paused for human completion.
2. Retrieve pending work
Pending patients are pulled from the backend API and stored locally to preserve recoverability.
3. Open the correct chart
The automation finds the patient and relevant encounter, then checks whether the encounter can be processed.
4. Enter structured content safely
Available Subjective, Objective, and Plan content is entered, while ICD-10 codes are checked for valid format and duplicates before attachment.
5. Sync and document the outcome
The patient status is updated through the API and success, incomplete processing, or failure details are preserved in logs and screenshots.
Patient-level jobs
Each patient is processed independently so one recoverable problem does not terminate the queue.
Session recovery
The workflow recognizes login, lock, redirect, and browser-verification states.
Validation before writing
ICD format checks and duplicate detection reduce the chance of repeating invalid data.
Operational evidence
API statuses, JSON records, CSV logs, and screenshots show what was attempted and where intervention is needed.
Key Features
These were the standout elements that made this solution effective.
Places available structured Subjective, Objective, and Plan content into the appropriate encounter sections.
Validates code format and checks for an existing code before attempting to add it.
Detects session drift and uses controlled recovery or a human verification pause.
Supports separately configured browser profiles, credentials, API settings, and active bot instances.
Records success, incomplete processing, and failure details for each patient.
Tech Stack
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