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A randomized controlled trial of online symptom searching to inform patient generated differential diagnoses

Patient online health searching is now commonplace, however, the accuracy of patient generated differentials for new symptoms and potential for patient anxiety are concerns. We aimed primarily to determine the accuracy of patient generated differentials for new symptoms with and without online searc...

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Autores principales: Martin, Seth S., Quaye, Emmanuel, Schultz, Sarah, Fashanu, Oluwaseun E., Wang, Jane, Saheed, Mustapha O., Prem Ramaswami, de Freitas, Hermes, Ribeiro-Neto, Berthier, Parakh, Kapil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6848180/
https://www.ncbi.nlm.nih.gov/pubmed/31728417
http://dx.doi.org/10.1038/s41746-019-0183-0
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author Martin, Seth S.
Quaye, Emmanuel
Schultz, Sarah
Fashanu, Oluwaseun E.
Wang, Jane
Saheed, Mustapha O.
Prem Ramaswami
de Freitas, Hermes
Ribeiro-Neto, Berthier
Parakh, Kapil
author_facet Martin, Seth S.
Quaye, Emmanuel
Schultz, Sarah
Fashanu, Oluwaseun E.
Wang, Jane
Saheed, Mustapha O.
Prem Ramaswami
de Freitas, Hermes
Ribeiro-Neto, Berthier
Parakh, Kapil
author_sort Martin, Seth S.
collection PubMed
description Patient online health searching is now commonplace, however, the accuracy of patient generated differentials for new symptoms and potential for patient anxiety are concerns. We aimed primarily to determine the accuracy of patient generated differentials for new symptoms with and without online searching, and secondarily, to evaluate the impact of searching on anxiety levels. In the waiting room prior to seeing a clinician, 300 patients with new symptoms were randomly assigned 1:1:1 to Google searching with health related features including a symptom search tool vs Google searching with health related features disabled vs no searching. Participants were 18 years or older and presenting to the emergency department of an urban academic medical center with new low-acuity symptoms that were not due to exacerbation of a chronic condition. Search groups received access on a tablet/smartphone to Google searching with or without health related features. Both search groups could access any websites; health related features led the patient to common diagnoses and physician-validated information. The primary outcome was accuracy of the patient generated differential assessed by matching at least two of the top three diagnoses on the clinician’s differential. A secondary outcome was anxiety by a visual analogue scale. Patients were a median of 33.1 (IQI 26.2–45.9) years old, 60% women, 63% black, 82% had a high school education or less, and 45.7% reported having performed an online search prior to presentation. Search group patients spent a median of 3.82 (2.53–5.72) minutes searching online. Similar proportions of patients in each group matched at least two of three clinician diagnoses: 27.0% and 28.3% for Google searching with and without health related features vs 23.8% in the no search group. Patients in the search groups had a similar odds of matching ≥2/3 diagnoses as the no search group [OR (95% CI): 1.23 (0.70–2.13), p = 0.47]. Anxiety was unchanged with online searching. In conclusion, brief online searching in the waiting room did not improve accuracy of patient generated differential diagnoses for new symptoms. The absence of an increase in patient anxiety provides reassurance for subsequent work to refine and investigate online symptom search tools.
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spelling pubmed-68481802019-11-14 A randomized controlled trial of online symptom searching to inform patient generated differential diagnoses Martin, Seth S. Quaye, Emmanuel Schultz, Sarah Fashanu, Oluwaseun E. Wang, Jane Saheed, Mustapha O. Prem Ramaswami de Freitas, Hermes Ribeiro-Neto, Berthier Parakh, Kapil NPJ Digit Med Article Patient online health searching is now commonplace, however, the accuracy of patient generated differentials for new symptoms and potential for patient anxiety are concerns. We aimed primarily to determine the accuracy of patient generated differentials for new symptoms with and without online searching, and secondarily, to evaluate the impact of searching on anxiety levels. In the waiting room prior to seeing a clinician, 300 patients with new symptoms were randomly assigned 1:1:1 to Google searching with health related features including a symptom search tool vs Google searching with health related features disabled vs no searching. Participants were 18 years or older and presenting to the emergency department of an urban academic medical center with new low-acuity symptoms that were not due to exacerbation of a chronic condition. Search groups received access on a tablet/smartphone to Google searching with or without health related features. Both search groups could access any websites; health related features led the patient to common diagnoses and physician-validated information. The primary outcome was accuracy of the patient generated differential assessed by matching at least two of the top three diagnoses on the clinician’s differential. A secondary outcome was anxiety by a visual analogue scale. Patients were a median of 33.1 (IQI 26.2–45.9) years old, 60% women, 63% black, 82% had a high school education or less, and 45.7% reported having performed an online search prior to presentation. Search group patients spent a median of 3.82 (2.53–5.72) minutes searching online. Similar proportions of patients in each group matched at least two of three clinician diagnoses: 27.0% and 28.3% for Google searching with and without health related features vs 23.8% in the no search group. Patients in the search groups had a similar odds of matching ≥2/3 diagnoses as the no search group [OR (95% CI): 1.23 (0.70–2.13), p = 0.47]. Anxiety was unchanged with online searching. In conclusion, brief online searching in the waiting room did not improve accuracy of patient generated differential diagnoses for new symptoms. The absence of an increase in patient anxiety provides reassurance for subsequent work to refine and investigate online symptom search tools. Nature Publishing Group UK 2019-11-11 /pmc/articles/PMC6848180/ /pubmed/31728417 http://dx.doi.org/10.1038/s41746-019-0183-0 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Martin, Seth S.
Quaye, Emmanuel
Schultz, Sarah
Fashanu, Oluwaseun E.
Wang, Jane
Saheed, Mustapha O.
Prem Ramaswami
de Freitas, Hermes
Ribeiro-Neto, Berthier
Parakh, Kapil
A randomized controlled trial of online symptom searching to inform patient generated differential diagnoses
title A randomized controlled trial of online symptom searching to inform patient generated differential diagnoses
title_full A randomized controlled trial of online symptom searching to inform patient generated differential diagnoses
title_fullStr A randomized controlled trial of online symptom searching to inform patient generated differential diagnoses
title_full_unstemmed A randomized controlled trial of online symptom searching to inform patient generated differential diagnoses
title_short A randomized controlled trial of online symptom searching to inform patient generated differential diagnoses
title_sort randomized controlled trial of online symptom searching to inform patient generated differential diagnoses
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6848180/
https://www.ncbi.nlm.nih.gov/pubmed/31728417
http://dx.doi.org/10.1038/s41746-019-0183-0
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