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Questioning the Yelp Effect: Mixed Methods Analysis of Web-Based Reviews of Urgent Cares
BACKGROUND: Providers of on-demand care, such as those in urgent care centers, may prescribe antibiotics unnecessarily because they fear receiving negative reviews on web-based platforms from unsatisfied patients—the so-called Yelp effect. This effect is hypothesized to be a significant driver of in...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8538031/ https://www.ncbi.nlm.nih.gov/pubmed/34623316 http://dx.doi.org/10.2196/29406 |
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author | Hu, Dian Liu, Cindy Meng-Hsin Hamdy, Rana Cziner, Michael Fung, Melody Dobbs, Samuel Rogers, Laura Turner, Monique Mitchell Broniatowski, David André |
author_facet | Hu, Dian Liu, Cindy Meng-Hsin Hamdy, Rana Cziner, Michael Fung, Melody Dobbs, Samuel Rogers, Laura Turner, Monique Mitchell Broniatowski, David André |
author_sort | Hu, Dian |
collection | PubMed |
description | BACKGROUND: Providers of on-demand care, such as those in urgent care centers, may prescribe antibiotics unnecessarily because they fear receiving negative reviews on web-based platforms from unsatisfied patients—the so-called Yelp effect. This effect is hypothesized to be a significant driver of inappropriate antibiotic prescribing, which exacerbates antibiotic resistance. OBJECTIVE: In this study, we aimed to determine the frequency with which patients left negative reviews on web-based platforms after they expected to receive antibiotics in an urgent care setting but did not. METHODS: We obtained a list of 8662 urgent care facilities from the Yelp application programming interface. By using this list, we automatically collected 481,825 web-based reviews from Google Maps between January 21 and February 10, 2019. We used machine learning algorithms to summarize the contents of these reviews. Additionally, 200 randomly sampled reviews were analyzed by 4 annotators to verify the types of messages present and whether they were consistent with the Yelp effect. RESULTS: We collected 481,825 reviews, of which 1696 (95% CI 1240-2152) exhibited the Yelp effect. Negative reviews primarily identified operations issues regarding wait times, rude staff, billing, and communication. CONCLUSIONS: Urgent care patients rarely express expectations for antibiotics in negative web-based reviews. Thus, our findings do not support an association between a lack of antibiotic prescriptions and negative web-based reviews. Rather, patients’ dissatisfaction with urgent care was most strongly linked to operations issues that were not related to the clinical management plan. |
format | Online Article Text |
id | pubmed-8538031 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-85380312021-11-09 Questioning the Yelp Effect: Mixed Methods Analysis of Web-Based Reviews of Urgent Cares Hu, Dian Liu, Cindy Meng-Hsin Hamdy, Rana Cziner, Michael Fung, Melody Dobbs, Samuel Rogers, Laura Turner, Monique Mitchell Broniatowski, David André J Med Internet Res Original Paper BACKGROUND: Providers of on-demand care, such as those in urgent care centers, may prescribe antibiotics unnecessarily because they fear receiving negative reviews on web-based platforms from unsatisfied patients—the so-called Yelp effect. This effect is hypothesized to be a significant driver of inappropriate antibiotic prescribing, which exacerbates antibiotic resistance. OBJECTIVE: In this study, we aimed to determine the frequency with which patients left negative reviews on web-based platforms after they expected to receive antibiotics in an urgent care setting but did not. METHODS: We obtained a list of 8662 urgent care facilities from the Yelp application programming interface. By using this list, we automatically collected 481,825 web-based reviews from Google Maps between January 21 and February 10, 2019. We used machine learning algorithms to summarize the contents of these reviews. Additionally, 200 randomly sampled reviews were analyzed by 4 annotators to verify the types of messages present and whether they were consistent with the Yelp effect. RESULTS: We collected 481,825 reviews, of which 1696 (95% CI 1240-2152) exhibited the Yelp effect. Negative reviews primarily identified operations issues regarding wait times, rude staff, billing, and communication. CONCLUSIONS: Urgent care patients rarely express expectations for antibiotics in negative web-based reviews. Thus, our findings do not support an association between a lack of antibiotic prescriptions and negative web-based reviews. Rather, patients’ dissatisfaction with urgent care was most strongly linked to operations issues that were not related to the clinical management plan. JMIR Publications 2021-10-08 /pmc/articles/PMC8538031/ /pubmed/34623316 http://dx.doi.org/10.2196/29406 Text en ©Dian Hu, Cindy Meng-Hsin Liu, Rana Hamdy, Michael Cziner, Melody Fung, Samuel Dobbs, Laura Rogers, Monique Mitchell Turner, David André Broniatowski. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 08.10.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Hu, Dian Liu, Cindy Meng-Hsin Hamdy, Rana Cziner, Michael Fung, Melody Dobbs, Samuel Rogers, Laura Turner, Monique Mitchell Broniatowski, David André Questioning the Yelp Effect: Mixed Methods Analysis of Web-Based Reviews of Urgent Cares |
title | Questioning the Yelp Effect: Mixed Methods Analysis of Web-Based Reviews of Urgent Cares |
title_full | Questioning the Yelp Effect: Mixed Methods Analysis of Web-Based Reviews of Urgent Cares |
title_fullStr | Questioning the Yelp Effect: Mixed Methods Analysis of Web-Based Reviews of Urgent Cares |
title_full_unstemmed | Questioning the Yelp Effect: Mixed Methods Analysis of Web-Based Reviews of Urgent Cares |
title_short | Questioning the Yelp Effect: Mixed Methods Analysis of Web-Based Reviews of Urgent Cares |
title_sort | questioning the yelp effect: mixed methods analysis of web-based reviews of urgent cares |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8538031/ https://www.ncbi.nlm.nih.gov/pubmed/34623316 http://dx.doi.org/10.2196/29406 |
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