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Clinician Satisfaction With AI Documentation Tools

Measures how satisfied clinicians are with AI-assisted clinical documentation tools — accuracy, trust, time saved, and workflow fit — for health systems and vendors evaluating scribe or note-drafting technology. An AI follow-up interview reconstructs a specific recent encounter where the tool helped or failed, surfacing concrete fixes that a satisfaction score alone can't show.

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Sample questions

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

14 questions · ~7 min
Q01
Message

Thanks for taking a few minutes to share your experience with AI-assisted documentation. Your honest feedback shapes whether and how this tool keeps being used. This should take about 8 minutes.

Q02
Multiple ChoiceRequired

Which type of AI documentation tool do you primarily use for clinical notes?

  • Ambient voice-recording scribe (listens during the visit)
  • Template or smart-phrase based note generator
  • Fully automated note drafting integrated with the EHR
  • Other
  • Not sure / don't know which type
Q03
Opinion ScaleRequired

Overall, how satisfied are you with this AI documentation tool?

Scale: 1 – 5
Min:Very dissatisfiedMax:Very satisfied
Q04
MatrixRequired

How much do you agree with each statement about the tool?

4 rows × 5 columns
  • The AI-generated notes accurately capture clinically relevant details
  • I trust the AI-generated note enough to sign it with only minor edits
  • Using this tool has improved my ability to focus on the patient during visits
  • The tool fits smoothly into my existing documentation workflow
Columns: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q05
Number

In a typical week, about how many hours does this tool save you on documentation compared to before you used it?

Q06
Multiple ChoiceRequired

In the last 30 days, how often did you need to correct the AI-generated note before signing off?

  • Never
  • Rarely
  • Sometimes
  • Often
  • Every time
Q07
RankingRequired

Rank these issues from the one that most hurts your satisfaction with the tool to the one that matters least.

  1. Inaccurate or fabricated clinical details
  2. Missing important context from the visit
  3. Time spent editing notes before signing
  4. Poor integration with the EHR
  5. Lack of specialty-specific terminology
  6. Concerns about cost or billing implications
Drag to rank
Q08
AI Interview

Anchor on the satisfaction rating and the correction frequency the clinician gave. Ask them to walk through one specific recent encounter where the tool's note either clearly helped or clearly went wrong — what it got right or missed, how long fixing it took, and whether they'd have trusted it unedited. If they rated satisfaction low, probe what single change (accuracy, speed, integration, oversight workflow) would move them to 'satisfied.' If they rated it high, probe whether there are edge cases (complex patients, rare diagnoses, difficult conversations) where they still don't trust it.

Q09
Opinion ScaleRequired

How likely are you to recommend this AI documentation tool to a colleague?

Scale: 0 – 10
Min:Not at all likelyMax:Extremely likely
Q10
Message

Last, a few quick details about you — these help us compare results across specialties and settings. All optional.

Q11
Dropdown

What is your primary clinical specialty?

  • Primary care / Family medicine
  • Internal medicine
  • Emergency medicine
  • Surgery
  • Psychiatry / Behavioral health
  • Pediatrics
  • OB/GYN
  • Other specialty
  • Prefer not to say
Q12
Multiple Choice

How long have you been using this AI documentation tool?

  • Less than 1 month
  • 1-6 months
  • 6-12 months
  • More than a year
  • Prefer not to say
Q13
Multiple Choice

What is your primary practice setting?

  • Inpatient / hospital
  • Outpatient clinic
  • Emergency department
  • Telehealth
  • Other
  • Prefer not to say
Q14
Message

That's everything — thank you for the candid feedback. Your responses will be combined with your colleagues' to guide fixes and decisions about how this tool is used going forward.

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

  • Includes an AI follow-up interview that reconstructs a specific recent encounter, anchored on the clinician's satisfaction rating and correction frequency, to surface concrete fixes a score alone can't show
  • Covers accuracy, trust, time saved, and workflow fit through a dedicated matrix question plus opinion scales for overall satisfaction and likelihood to recommend
  • Includes a ranking question isolating which issue most hurts satisfaction, a numeric estimate of weekly hours saved, and a correction-frequency question to quantify trust in the AI output
  • Captures specialty, practice setting, and tool tenure so health systems and vendors can segment results by clinical context

Jotform

200+ Customer Satisfaction Evaluation Forms

This is a broad category/directory page of generic customer satisfaction form templates, not a fielding-ready survey built for clinicians or AI documentation tools. It would require substantial rebuilding to fit a clinical-workflow use case. Useful mainly as a form-builder starting point rather than a domain-specific instrument.

What it does well

  • Large library of customizable form templates and a drag-and-drop builder
  • Established form-hosting and basic reporting infrastructure
  • Easy to adapt generic satisfaction questions to many industries

Where it falls short

  • Static rating-scale forms with no adaptive AI follow-up to probe a specific clinical encounter
  • No healthcare or clinical-documentation-specific question logic or terminology
  • No automated quality scoring of open-ended responses

SurveySparrow

FREE Customer Satisfaction Survey Template

A free, single generic customer-satisfaction template with SurveySparrow's conversational chat-style format. It is ready to field quickly but is written for general customer feedback, not clinician evaluation of AI documentation tools, so questions on accuracy, trust, and workflow fit would need to be authored from scratch. No healthcare-specific branching or scoring is present.

What it does well

  • Conversational, chat-like survey experience that can feel more engaging than static forms
  • Free to use and quick to deploy
  • Simple customization within SurveySparrow's builder

Where it falls short

  • No adaptive AI interview to reconstruct a specific clinical encounter or surface root-cause fixes
  • Not built for clinical audiences—lacks specialty, practice-setting, or documentation-tool-specific questions
  • No transparent, published methodology for how follow-up questions (if any) are generated

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