Published September 16, 2025 | Version v1

Database of Negative Reviews from Patients of Medical Clinics in Russian Cities with a Population of over a Million (Based on infodoctor.ru for the Period 2012–2023)

  • 1. Lomonosov Moscow State University, Moscow, Russia

Description

This database contains 18.492 negative patient reviews (rated one star out of five, where five is the highest level of medical service quality) from the Russian medical review aggregator infodoctor.ru, collected between July 2012 and August 2023. The database is presented in .xlsx format (UTF-8 encoding). The dataset covers 16 major Russian cities, including Moscow (8.108 reviews), St. Petersburg (2.356), and 14 other cities with a population of over a million (8.028). Reflecting dissatisfaction with the quality of medical services, this dataset provides important information about the problems in the healthcare delivery across regions and socio-demographic groups. The data are presented as full-text reviews, which allows for an in-depth analysis of patient experience using text content analysis. Structured variables such as city, date, complaint type, doctor's specialty, patient's gender also allow for quantitative analysis using econometric methods. The combination of methods allows us to gain insight into patient dissatisfaction with medical services in Russian cities with a population of over a million for more than a decade.

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Additional details

Related works

Cites
Publication: 10.3390/math12040566 (DOI)
Publication: 10.18287/2223-9537-2025-15-1-55-66 (DOI)

References

  • Kalabikhina I, Moshkin V, Kolotusha A, Kashin M, Klimenko G, Kazbekova Z (2024) Advancing Semantic Classification: A Comprehensive Examination of Machine Learning Techniques in Analyzing Russian-Language Patient Reviews. Mathematics 12(4): 566. https://doi.org/10.3390/math12040566
  • Kalabikhina I, Moshkin V, Kolotusha A, Kashin M, Klimenko G, Kazbekova Z (2025) Analysis of patient reviews using machine learning and linguistic methods. Ontology of designing 15(1): 55–66. https://doi.org/10.18287/2223-9537-2025-15-1-55-66 (In Russian)
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