Telemedicine Interaction Feedback

This dataset contains detailed, structured feedback from synthetic telemedicine consultations, including ratings on satisfaction, communication, technical quality, and free-text comments. It captures patient demographics, consultation context, and device usage, making it ideal for analyzing patient experience, modeling satisfaction drivers, and optimizing telemedicine services.

  • last updated 22 Jul 2025
  • by GoMask
The brief that made it

Patient satisfaction modeling and trend analysis

Sample rows

preview · 8 of 200 rows · all 20 columns
feedback_idstringdevice_typestringwait_time_minutesintegerissue_resolvedbooleanlocation_countrystringconsultation_idstringpatient_idstringprovider_idstringconsultation_datetimedatetimefeedback_datetimedatetimeoverall_satisfactionintegerprovider_communicationintegertechnical_qualityintegerwould_recommendbooleanpatient_ageintegerpatient_genderstringconsultation_typestringlocation_citystringlocation_statestringfeedback_textstring
F0001smartphone2trueUSAC0001P0001PR00012023-10-05T14:15:00Z2023-10-05T14:40:00Z555true27femalevideoNew YorkNYExcellent service, the doctor was very attentive and helpful.
F0002laptop5trueUKC0002P0002PR00022023-10-06T09:30:00Z2023-10-06T10:05:00Z444true35malevideoLondonEnglandThe consultation was smooth and informative.
F0003tablet0trueCanadaC0003P0003PR00032023-09-15T16:45:00Z2023-09-15T17:00:00Z555true1othervideoTorontoONVery fast, great video quality, and easy to use.
F0004desktop16falseUSAC0004P0004PR00042023-10-10T12:00:00Z2023-10-10T12:25:00Z332false64femalephoneDetroitMIHad some issues with audio, but provider tried to help.
F0005tablet3trueAustraliaC0005P0005PR00052023-11-01T18:30:00Z2023-11-01T19:00:00Z444true29malevideoSydneyNSWDoctor answered all my questions and was polite.
F0006desktop38falseUKC0006P0006PR00062023-09-20T08:30:00Z2023-09-20T09:10:00Z221false72malephoneManchesterEnglandLong wait and poor connection made it hard to communicate.
F0007smartphone0trueGermanyC0007P0007PR00072023-10-22T13:15:00Z2023-10-22T13:18:00Z555true30femalevideoBerlinBerlinService was fast and the doctor was very knowledgeable.
F0008other88falseSouth AfricaC0008P0008PR00082023-09-29T15:00:00Z2023-09-29T15:55:00Z112false51femaleotherJohannesburgGautengWaited a long time and my issue was not resolved.

What the 200 rows show

from the 200-row sample

Other (device type) stands out: mean wait_time_minutes is 65.8, against 7.8 for the rest.

  • 76%issue_resolved = true
  • 2median wait_time_minutes
  • 4patient genders
  • 4consultation types
  • 53location states
  • 4median overall_satisfaction
Mean wait_time_minutes by device_type200 rows
0408023.1deskt…50 rows2.1laptop37 rows1.3tablet47 rows1.3smart…46 rows65.8other18 rows34.0phone2 rows
wait_time_minutes200 rows, in bands of 20
0851701651012562060120wait_time_minutes →

Median 2, from 0 to 120.

location_country200 rows · top 10 of 25 values
  1. USA40
  2. UK33
  3. Spain17
  4. Australia15
  5. Canada12
  6. Germany12
  7. South Africa12
  8. India9
  9. Japan6
  10. Nigeria6
20 columns by typefrom the column list below
  • string 11
  • integer 5
  • datetime 2
  • boolean 2

Columns

20 columns in four groups
blueprint · 20 columns
columntypedescriptionexample
Text 11 columns
feedback_idstringUnique identifier for each feedback recorduniqueF0001
consultation_idstringUnique identifier for the telemedicine consultation sessionC0001
patient_idstringUnique identifier for the patient providing feedbackP0001
provider_idstringUnique identifier for the healthcare provider involved in the consultationPR0001
feedback_textstringOptional free-text feedback provided by the patientoptionalExcellent service, the do…
patient_genderstringGender of the patientmale · female · other · prefer_not_to_say · optionalfemale
consultation_typestringType of telemedicine consultation (e.g., video, phone, chat)video · phone · chat · other · optionalvideo
device_typestringType of device used for the consultationdesktop · laptop · tablet · smartphone · other · optionalsmartphone
location_citystringCity where the patient was located during the consultationoptionalNew York
location_statestringState or region where the patient was located during the consultationoptionalNY
location_countrystringCountry where the patient was located during the consultationoptionalUSA
Numbers 5 columns
overall_satisfactionintegerOverall satisfaction rating provided by the patient (1-5 scale)1 to 55
provider_communicationintegerRating of provider's communication skills (1-5 scale)1 to 5 · optional5
technical_qualityintegerRating of technical quality (audio/video/connectivity) (1-5 scale)1 to 5 · optional5
wait_time_minutesintegerNumber of minutes the patient waited before the consultation started0 or more · optional2
patient_ageintegerAge of the patient at the time of consultation0 or more · optional27
Dates and times 2 columns
consultation_datetimedatetimeDate and time when the telemedicine consultation occurred2023-10-05T14:15:00Z
feedback_datetimedatetimeDate and time when the feedback was submitted2023-10-05T14:40:00Z
True or false 2 columns
issue_resolvedbooleanIndicates whether the patient's issue was resolved during the consultationoptionaltrue
would_recommendbooleanWhether the patient would recommend this telemedicine service to othersoptionaltrue

Use it for

  • issue resolved76%151 of 200 rowsmean wait time minute…23.1desk…2.1lapt…1.3tabl…1.3smar…

    A healthcare dashboard

    The issue_resolved rate, wait_time_minutes by device_type and a breakdown of location_country. Excel, Power BI or Tableau.

  • Why do the 18 other rows have a mean wait_time_minutes of 65.8?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable feedbacks with consultation_id, patient_id and provider_id to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 20 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

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This dataset200 rows20 columns
Yours1,000 rows20 columnslocation_city: UK only

blueprint · telemedicine-interaction-feedback

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 20 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Include satisfaction score and free-text comments
  • Tag for resolved/unresolved issues
  • Classify feedback topics (wait time, clarity, empathy)
  • Simulate variable demographic profiles
Rows
Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
telemedicine-interaction-feedback

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