Healthcare & clinical survey templates

Captures how much pet owners actually spend on veterinary care, medications, insurance, and routine upkeep, where the biggest cost pressures sit, and whether cost ever delays treatment — with an AI follow-up that unpacks a real recent expense decision instead of a hypothetical one.

Captures how patients experienced a recent visit — wait times, communication, staff respect, and overall likelihood to recommend — with a best-worst prioritization of improvement areas and an AI follow-up that digs into the specific moment behind their recommendation score. Built for clinics, hospitals, and practice managers tracking care quality.

Captures a patient's current health status, chronic conditions, medications, allergies, family history, and lifestyle risk factors ahead of a visit — with an AI follow-up that reconstructs the real story behind their most significant condition or symptom instead of a checkbox. Built for clinics, telehealth intake, and health research teams standardizing pre-visit history collection.

Tracks a patient's pain, functional ability, home exercise adherence, and satisfaction with their physical therapy plan of care, with an AI follow-up that digs into what's really getting in the way of progress. Built for outpatient PT clinics running periodic check-ins or discharge reviews.

Evaluates how members experience their current health insurance — cost, coverage, network access, claims handling, and customer service — for health plans, employer benefits teams, or brokers assessing plan performance. An AI follow-up interview reconstructs a real recent claim or service interaction to surface exactly where the experience broke down or exceeded expectations.

Captures how environmental conditions like air quality, extreme heat, and pollution are affecting people's health and daily choices, for public health teams and clinicians planning outreach. An AI follow-up interview digs into the respondent's most pressing environmental health concern to surface real symptoms, triggers, and what would actually help.

Understand how self-directed health consumers choose, combine, and abandon supplements and wearables — what they spend, which data or advice actually changes their behavior, and where an AI follow-up interview surfaces the real story behind their most recent stack change instead of the tidy version.

Tracks how clinicians are adjusting to shifting multi-state licensure requirements and controlled-substance prescribing rules for telehealth, including care disruptions and compliance burden. An AI follow-up interview reconstructs a specific recent case where a rule change affected a patient encounter, surfacing details a closed-ended survey would miss.

Measures whether clients want to keep doing therapy from home by video or phone, shift to a hybrid model, or return to in-person care — and why. Built for behavioral health practices and telehealth platforms deciding how to structure ongoing care; the AI follow-up interview digs into the specific trade-offs, like privacy and connection with the therapist, behind each person's stated preference.

Measures how comfortable patients are with AI tools that listen, transcribe, and summarize clinical visits, and what would make them trust those tools more. Built for health systems and clinics piloting AI documentation. An AI follow-up interview digs into the specific moment or topic that made a patient hesitant, going beyond a simple comfort score.

Measures how recent reductions in Medicare telehealth coverage are affecting beneficiaries' access to care, out-of-pocket costs, and health outcomes. Built for health systems, patient advocacy groups, and policy researchers tracking rollback effects, with an AI follow-up that reconstructs one specific care disruption in the patient's own words.

Measures student stress levels, workload, sleep habits, and use of mental health support, then identifies the biggest barriers keeping students from asking for help. Built for student affairs, wellness centers, and academic advisors; the AI follow-up reconstructs a specific recent moment a student needed support but didn't seek it, and what would have changed that.

Measures patient comfort, consent preferences, and privacy concerns when sharing health data across providers, insurers, and digital health tools. Ideal for healthcare organizations, privacy teams, and compliance officers seeking to understand patient attitudes toward data sharing.

Assesses patient experience across scheduling access, clinician communication, post-visit follow-up, and overall satisfaction to identify actionable care quality improvements.

Measures patient satisfaction across appointment scheduling, provider interaction quality, and health technology reliability using NPS and CSAT frameworks. Designed for clinics and health systems seeking actionable improvement data.

Measures patient satisfaction across scheduling, wait times, provider interaction, and telehealth quality using NPS and multi-dimensional experience scales for healthcare organizations seeking actionable improvement insights.

Measures patient experience with remote patient monitoring (RPM) devices, comfort with health data sharing across stakeholders, trust and consent preferences, and support needs for adoption.

Measures patients' experiences with insurance prior authorization, capturing process clarity, wait times, care impacts, and pain points to identify systemic improvement opportunities.

Measures clinicians' reporting behaviors, system usability, barriers to completeness, and safety culture around adverse event and near-miss reporting. Designed to surface actionable improvements for patient safety and quality leaders.

Assesses caregiver strain, care coordination challenges, and support needs among adult caregivers of children receiving medical care to inform improvements in family-centered services.

Measures patient satisfaction across appointment access, provider communication, follow-up timeliness, and digital touchpoints for healthcare organizations seeking actionable improvement insights and NPS benchmarking.

For healthcare organizations evaluating their patient portal's digital experience. Measures navigation ease, records access, secure messaging satisfaction, and Net Promoter Score to identify priority UX improvements.

Measures oncology patient perceptions of care access, appointment scheduling, provider coordination, and navigation support services. Designed for healthcare systems seeking to identify actionable gaps across the oncology care journey.

Measures dietary patterns, nutrition goals, purchasing behavior, and barriers to healthy eating. Use to segment customers, identify unmet needs, and inform food product or service development.

Assesses barriers to mental health care, provider-patient fit, telehealth preferences, wait times, and affordability. Designed for health systems, insurers, and researchers seeking to identify actionable improvements in mental health service delivery.

A recurring 2–3 minute non-diagnostic pulse measuring mood, stress drivers, coping strategies, and support preferences for e-commerce teams. Designed to inform wellbeing programs and resource planning.

A patient-facing needs assessment capturing menopause symptom burden, care access barriers, and service preferences to inform care model design and resource prioritization.

Evaluates the clarity, duplication, and effort associated with healthcare patient intake forms across digital and paper modalities. Designed for healthcare administrators seeking actionable insights to reduce patient burden and improve the check-in experience.

Measures how patients interpret, understand, and respond to lab results and reference ranges in online portals. Identifies usability barriers and preferred features to improve portal design and health literacy support.

Measures patient satisfaction across pain management, provider communication, and discharge preparedness for inpatient, outpatient, emergency, and telehealth visits.

Measures how well patients understand medical information across print, digital, and telehealth channels. Designed for healthcare communicators seeking to identify comprehension barriers and optimize plain-language materials.

Measures user onboarding experience, plan adherence behaviors and drivers, and self-reported health outcomes for digital health product teams seeking to improve retention and demonstrate impact.

Evaluates patient comprehension, usability, and decision confidence with electronic informed consent (eConsent) in clinical trials. Designed for post-consent administration to identify barriers and improve the consent experience.

A patient-reported outcome instrument tracking symptoms, treatment side effects, functional limitations, and quality of life over a 7-day recall period. Suitable for clinical research, treatment monitoring, and longitudinal patient wellbeing studies.

Measures documentation burden, system usability, and data capture pain points among clinical trial site staff. Designed for site coordinators, investigators, and research personnel to identify operational bottlenecks and prioritize workflow improvements.

Measures patient perceptions of post-visit support access, health education clarity, and care coordination quality. Designed for healthcare organizations seeking to identify gaps in patient communication and follow-up processes.

Measures patient-provider alignment across clinical, communication, and access dimensions to identify mismatch drivers and care preferences. Designed for healthcare organizations, insurers, or researchers seeking to improve provider matching and patient retention.

Evaluates laboratory information system usability, data accuracy, and workflow efficiency for biotech and healthcare lab professionals based on recent 30–90 day experience.

Evaluates patient access barriers, session comfort, perceived therapeutic outcomes, and format preferences for teletherapy. Designed for healthcare organizations and telehealth platforms seeking to improve virtual care delivery.

Evaluates patient satisfaction with healthcare appointment booking, confirmation, and reminder processes to identify friction points, optimize communication timing, and reduce no-show rates.

Assesses daily living challenges, home safety, care coordination, and support priorities among community-dwelling older adults to inform program planning and resource allocation.