A new vs. existing patient decision tree is a guided workflow that helps healthcare staff quickly determine whether a patient should be treated as new or returning - and ensures the correct registration, verification, and intake process follows. Instead of relying on memory or manually checking multiple systems, the decision tree walks schedulers through a clear sequence of questions: Does this patient already have a medical record? Is their information up to date? Do they need to complete new intake forms or insurance verification?
Each answer automatically directs the scheduler to the right next step, such as creating a new patient record, retrieving an existing chart, or verifying eligibility before confirming the appointment. This structured process reduces duplicate records, prevents billing errors, and keeps patient data accurate across systems.
Built with PixieBrix, the workflow runs directly inside existing tools - like Epic, Athenahealth, or Salesforce - so teams can standardize intake logic without switching platforms. The result is faster, error-free patient registration and a smoother experience for both staff and patients.
Accurately classifying new vs. existing patients sounds simple - but in high-volume clinics and multi-site systems, it’s one of the biggest sources of downstream inefficiency. A single misidentified patient can create duplicate records, insurance denials, or lost clinical context. When intake staff rely on memory, manual lookups, or inconsistent naming conventions, errors compound quickly across EHRs and billing systems.
The decision tree transforms this process into a guided, rule-based workflow. It ensures every scheduler or intake coordinator follows the same verification logic: check identifiers, confirm record existence, and route the patient through the correct next steps. That means cleaner data, fewer duplicates, and faster registration - all without adding complexity to your existing systems.
When staff manually search for existing patients, slight name or spelling variations can create duplicates that cause major billing and compliance headaches.
Without standardized prompts, intake teams often miss key details like DOB, insurance IDs, or referring provider information.
Skipping verification or using outdated payer details leads to rejected claims and wasted administrative time.
New hires need weeks to memorize patient classification rules - slowing down front-desk productivity.
Staff toggle between multiple applications for lookup, verification, and registration, increasing cognitive load and mistakes.
Decision trees solve these problems by encoding your rules into a clear, guided process that lives directly inside your existing tools.
The New vs. Existing Patient Decision Tree helps staff follow clear intake logic inside their current systems. When a scheduler starts the workflow, it prompts them to confirm patient identity, match identifiers like DOB or phone number, and select the right path - either creating a new record or retrieving an existing one.
Built in PixieBrix, the workflow runs directly in your browser, overlaying systems like Epic, Athenahealth, Salesforce, or custom scheduling apps. It can auto-populate fields, open patient charts, and trigger actions like eligibility verification or consent form checks. No backend integration required - just in-flow intelligence that keeps your data clean and your team efficient.
PixieBrix runs inside your existing scheduling platform or EHR, guiding staff without needing to open another window or toggle between systems.
The tree helps staff identify the correct visit type, appointment length, and required provider qualifications - based on reason for visit and clinic rules.
Use PixieBrix’s no-code builder to define workflows for new visits, follow-ups, telehealth, or specialty consults. You can update rules as protocols change.
Trigger actions like:
Reduce rework and rescheduling by guiding staff to the right booking every time.
Track how often scheduling errors occur and which flows are used most. Use the data to improve training and reduce call center load.
From small clinics to large networks, PixieBrix helps standardize scheduling logic while allowing customization per site or specialty.
Outline how your organization defines new vs. existing patients - matching criteria, required fields, and escalation paths.
Add the PixieBrix extension, sign in, and import the New vs. Existing Patient Decision Tree template into your browser.
Customize prompts for identifiers, verification questions, and data sources. Add context tips (e.g., “Check referring provider” or “Verify payer code”).
Connect the decision tree to your EHR fields and internal databases through in-browser selectors or APIs. Auto-populate common fields like MRN or insurance ID.
Run pilot sessions with schedulers, front-desk, and billing teams. Confirm accuracy and refine unclear prompts.
Deploy clinic-wide and monitor:
Ensure every patient is identified correctly and every data field is validated before submission. Clinics using guided verification have seen duplicate records drop by 40% within weeks.
Schedulers no longer toggle between multiple systems or guess patient status. Each interaction follows the same structured path, shortening intake time by up to 25%.
Decision trees remove ambiguity, allowing new and experienced staff to schedule and verify patients with confidence. This shortens onboarding cycles and raises first-call resolution rates.
By enforcing required verification steps and audit trails, PixieBrix helps clinics maintain HIPAA compliance and meet payer documentation standards.
Runs as a browser-native overlay. Works with your existing EHR or scheduling system without IT projects, APIs, or downtime.
A new vs existing patient decision tree is a guided intake tool that helps front desk or scheduling staff determine the correct workflow based on a patient’s visit history. Rather than guessing or relying on memory, staff follow a structured path to confirm whether a patient is already in the system or needs to be registered for the first time. This reduces duplicate records, ensures accurate documentation, and speeds up patient intake.
Front-desk staff use the decision tree to confirm returning patients before registration, reducing duplicate records by 42% and cutting intake time by 18%.
Automated verification across states ensures new patients complete digital registration while returning patients skip redundant forms - improving booking speed and compliance accuracy.
Multiple sites deploy identical intake logic through PixieBrix, giving leadership unified data visibility and reducing registration discrepancies between departments.
PixieBrix empowers healthcare teams to bring automation and standardization directly into the browser - without costly EHR customization. Each workflow is configurable, version-controlled, and instantly deployable across teams.
The result:
For operations leaders, PixieBrix bridges the gap between human judgment and process automation - turning intake into a repeatable, measurable, and scalable workflow.
It’s a guided workflow that walks staff through patient verification and record classification, ensuring correct routing for registration or existing chart lookup.
Yes - PixieBrix runs directly in the browser on top of any web-based EHR or scheduling system. No APIs or backend integrations required.
Absolutely. You can clone and customize versions per site while keeping shared logic for identifiers and verification rules.
Yes. PixieBrix operates entirely within your browser session and inherits your system’s security. No PHI leaves your environment.
Most clinics can configure and launch within a single day.
