Here are some of the best questions for a patient survey about shared decision-making, plus practical tips on creating them. With Specific, you can generate an effective, conversational patient survey in seconds—start collecting deeper feedback in minutes.
Best open-ended questions for patient survey about shared decision-making
Open-ended questions tap into genuine patient perspectives, revealing experiences that structured questions can miss. They're especially valuable when you need detailed feedback or want to understand patients’ motivations, concerns, or unmet needs around shared decision-making.
Can you describe a recent experience where you were involved in making a healthcare decision with your provider?
How did you feel about the amount of information you received before making a decision?
What helped you feel confident in making your healthcare decisions?
Were there any parts of the decision-making process that felt unclear or rushed?
How did your healthcare provider explain the risks and benefits of different options?
What suggestions do you have for improving how decisions are discussed with patients?
Can you share an example of when your preferences were included (or overlooked) in a medical decision?
What barriers, if any, made it difficult for you to participate in decisions about your care?
How would you like to be supported when making important health choices?
Is there anything you wish your healthcare team had done differently to involve you in the decision-making process?
This approach isn’t just about getting more words—shared decision-making has been linked to higher patient satisfaction and improved outcomes, with studies showing satisfaction rates more than double among engaged patients compared to those who weren’t fully included in the process. [1]
Best single-select multiple-choice questions for patient survey about shared decision-making
Single-select multiple-choice questions are ideal when you need structured data or want to quantify patient experiences. They’re also helpful as an easy “opening move” for deeper conversation—patients can quickly select an option, and you can follow up for more detail.
Question: How involved did you feel in the decisions about your treatment?
Very involved
Somewhat involved
Not involved
Question: Did you feel you had enough information to make an informed choice about your care?
Yes, completely
Somewhat
No, not enough
Question: What was the main factor that influenced your treatment decision?
Doctor’s recommendation
Family/friends’ input
Online research
Other
When to follow up with "why?" If a patient selects "Not involved," or "No, not enough," ask a tailored “why” question. This uncovers the reasons behind dissatisfaction or barriers. For example, “What made you feel left out of the decision process?” or “What additional information would have helped you make a decision?” These follow-ups often reveal actionable insights.
When and why to add the "Other" choice? Always consider an "Other" option when your listed choices might not cover all possibilities. Then, follow up by asking the patient to elaborate. This can surface surprising perspectives or reasons that structured options miss, unlocking unexpected opportunities for improvement.
Should you use a Net Promoter Score (NPS) question in patient SDM surveys?
NPS is a simple survey question asking patients how likely they are to recommend a healthcare provider or experience, typically on a 0–10 scale. It’s especially useful to benchmark overall patient experience and loyalty. In the context of shared decision-making, asking an NPS question about the process allows you to track how patient empowerment and involvement impacts overall satisfaction—a key metric in value-based care.
Want to try it? Use Specific’s NPS survey for patients about shared decision-making to launch a ready-to-use survey.
The power of follow-up questions
One of the biggest leaps in modern surveys is automated AI follow-up questions. Instead of a static form, Specific can ask real-time, conversational follow-ups, capturing context and clarifying ambiguous answers. For example, if a patient writes “The appointment felt rushed,” the AI might ask, “What would have made you feel less rushed?”, extracting practical feedback you can act on.
This is a big reason why the quality of insights from AI-powered feedback is much richer. For a deeper explanation, check out our automated follow-up questions guide.
Patient: "I didn’t get enough information from my doctor."
AI follow-up: "What specific information would you have liked to receive?"
Patient: "I just went along with what my family thought."
AI follow-up: "What could have helped you feel more confident making your own choice?"
How many followups to ask? In most cases, 2–3 follow-ups are enough to clarify and deepen understanding without fatiguing the patient. Specific gives you granular control over follow-up intensity, and lets you set logic to skip to the next question as soon as you gather the needed context.
This makes it a conversational survey: The real-time back-and-forth feels like a supportive chat, not a cold survey form—a completely different experience for both respondents and researchers.
AI analysis of open-ended responses: Thanks to built-in AI response analysis, you can quickly synthesize and distill complex patient feedback—not just number crunching, but summarizing major themes and verbatim quotes. See more in our article on how to analyze responses from a patient survey.
These automated, conversational follow-ups are a new frontier. Take them for a spin by making your own survey and experience the difference.
How to write ChatGPT prompts for great patient shared decision-making surveys
If you want AI to help you brainstorm survey questions, clear prompts make a huge difference. Start simple:
Suggest 10 open-ended questions for Patient survey about Shared Decision-Making.
AI performs even better when you add context. Try a prompt like:
I’m a healthcare administrator designing a patient feedback survey to improve shared decision-making in our hospital. Our patients vary in age and background. Please suggest 10 open-ended questions that are easy to understand and likely to reveal both successes and gaps in our current process.
After reviewing your AI-generated questions, organize them for clarity:
Look at the questions and categorize them. Output categories with the questions under them.
This way, you can identify categories such as “information clarity”, “provider support”, or “personal empowerment”, and dig deeper where needed. If you want to focus more tightly, prompt:
Generate 10 questions for the “provider support” and “information clarity” categories.
This iterative process, refined by your domain expertise, yields excellent patient surveys in a fraction of the time.
What is a conversational survey?
A conversational survey feels like a real discussion, with the AI adapting its questions based on patient replies—unlike traditional surveys that just plod through a static script. This innovative approach is central to Specific, and is what sets AI survey builders apart from manual methods.
Manual Survey Creation | AI Survey Generation (Conversational) |
|---|---|
Time-consuming to brainstorm/write every question by hand | AI automatically drafts smart, relevant, tailored questions |
Predictable, one-size-fits-all questionnaire | Dynamic, adapts to patient’s unique answers and context |
Difficult to generate meaningful follow-ups on the fly | Automated, expert-style probing in real time |
Results often require tedious manual coding to analyze | Responses are auto-categorized, summarized, and searchable with AI |
Why use AI for patient surveys? The biggest gain is richness of insight. Shared decision-making is multi-faceted; only a conversational survey digs below the surface in real time to get at the “why” behind patient feelings and actions. The AI survey example structure truly matters here. Not only does it boost completion rates by feeling more natural—research also shows engaged patients lead to better outcomes, higher satisfaction, and can even reduce healthcare costs. [2][3]
Specific makes it seamless to run engaging conversational surveys for patients. Check out our guide on how to create a patient survey about shared decision-making and see how easy it is to get started.
See this shared decision-making survey example now
Get actionable insights from every patient conversation—use Specific’s conversational approach for richer understanding and faster, more comprehensive analysis. See what a difference the right survey format can make in your patient engagement and outcomes.