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Referral-to-Treatment Intake Experience Survey

Measures how patients experience the intake journey between referral and first treatment — communication clarity, wait-time transparency, and booking friction — for clinics and healthcare providers managing referral-to-treatment pathways. An AI follow-up interview reconstructs exactly where the process broke down or worked well, beyond a satisfaction score.

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Sample questions

A preview of what’s in the template. Every question is editable before you launch.

13 questions · ~7 min
Q01
Message

Thanks for taking a few minutes to share your experience so far. We'd like to understand what it was like between your referral and your first appointment or treatment — there are no right or wrong answers. This should take about 5 minutes.

Q02
Multiple ChoiceRequired

How were you referred for your current treatment pathway?

  • GP referral
  • Self-referral
  • Referred by another specialist
  • Online or digital referral form
  • Other
Q03
Multiple ChoiceRequired

How long ago were you referred?

  • Less than 2 weeks ago
  • 2-4 weeks ago
  • 1-3 months ago
  • 3-6 months ago
  • More than 6 months ago
Q04
Opinion ScaleRequired

How clear was the communication you received about what would happen next after your referral was submitted?

Scale: 1 – 5
Min:Not clear at allMax:Extremely clear
Q05
MatrixRequired

Please rate each part of your intake experience so far.

4 rows × 5 columns
  • Time to first contact from the service after referral
  • Clarity of information about expected wait times
  • Ease of reaching someone with questions
  • Reassurance provided while you waited
Columns: Poor · Below average · Average · Good · Excellent
Q06
Rating ScaleRequired

How would you rate the ease of booking your first appointment?

Range: 1 – 5
Min:Very difficultMax:Very easy
Q07
Multiple Choice

Did any of the following happen during your intake process? Select all that apply.

  • No delays or issues
  • Appointment was rescheduled
  • Referral was lost or had to be resubmitted
  • Long wait for initial contact from the service
  • Unclear next steps at some point
  • Other
Q08
Opinion ScaleRequired

Based on your intake experience so far, how likely are you to recommend this service to someone else needing similar care?

Scale: 0 – 10
Min:Not at all likelyMax:Extremely likely
Q09
AI Interview

Reconstruct the respondent's actual timeline between referral and now: what communication they received, when, and from whom. If they reported any delay, rescheduling, or unclear next steps, probe exactly what happened, how they found out, and what they had to do to move things forward. Anchor especially on gaps between the clarity rating and the recommend-likelihood score — if communication was rated poorly but they'd still recommend the service (or vice versa), ask why.

Q10
Short Text

What one change would have made your wait between referral and treatment easier?

Q11
Multiple Choice

Which age group do you fall into?

  • Under 18
  • 18-24
  • 25-34
  • 35-44
  • 45-54
  • 55-64
  • 65+
  • Prefer not to say
Q12
Multiple Choice

How do you describe your gender?

  • Woman
  • Man
  • Non-binary
  • Prefer to self-describe
  • Prefer not to say
Q13
Message

Thank you for sharing your experience. Your answers help this service identify where the referral-to-treatment process needs to improve, and will be reviewed alongside other patients' feedback to guide changes to communication and scheduling.

What’s included

  • AI follow-ups

    Adaptive probes on open-ended answers that pull out detail a static form would miss.

  • Attention checks

    Built-in safeguards against rushed answers and low-quality respondents.

  • AI-drafted copy

    Wording, ordering, and branching written by the AI — tuned to your research goal.

  • Auto report

    Themes, quotes, and a plain-English summary write themselves once responses come in.

How it compares

We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.

Why this template

  • Purpose-built to measure the referral-to-treatment journey itself (communication clarity, wait-time transparency, booking friction) rather than just collecting patient details
  • Combines structured questions (multiple choice, opinion scale, matrix, rating) with an AI follow-up interview that reconstructs the respondent's actual timeline and where the process broke down
  • Captures concrete friction points via a 'select all that apply' checklist and a short-text question asking what one change would have eased the wait, giving both quantifiable and narrative data
  • Includes recommend-likelihood and demographic questions plus opening/closing chat messages, so it fields as a complete, ready-to-run survey rather than a bare form

Jotform

Psychedelic Experience Intake Form Template

This is a clinical pre-session intake form for a specific treatment modality (psychedelic therapy), used to collect patient background and health information before a session begins. It is not designed to measure how patients experienced the referral-to-treatment journey, wait times, or booking friction. Useful mainly as a data-collection form rather than an experience/satisfaction survey.

What it does well

  • Healthcare-specific template with fields tailored to a clinical intake context
  • Drag-and-drop form builder with standard field types (checkboxes, text, signature, etc.)

Where it falls short

  • Static form with fixed fields — no adaptive follow-up questioning to explore why an answer was given
  • Focused on collecting patient background data, not on reconstructing or scoring the referral-to-treatment experience
  • No mechanism to probe communication breakdowns or booking friction the way an AI follow-up interview would

SurveyMonkey

Client Intake Form Template

A generic client intake form meant to onboard a new client and gather contact/service details, not a survey about the experience of moving from referral to treatment. It could be manually adapted for healthcare use, but as published it isn't scoped to wait-time transparency, communication clarity, or booking friction. It's a fielding-ready form, but for a different purpose than an experience study.

What it does well

  • Simple, quick-to-deploy template on a well-known survey platform
  • Broadly customizable for various client-onboarding use cases

Where it falls short

  • No adaptive AI interviewing — follow-up questions require manual branching logic set up in advance
  • Not built around healthcare referral pathways or wait-time/booking-friction measurement specifically
  • No automated per-response quality scoring or auto-generated diagnostic reports

Ready to launch?

Open this template in the editor. Every part is yours to change before the first respondent sees it.

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