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. 2021 Apr;36(4):1224-1231.
doi: 10.1016/j.arth.2020.10.024. Epub 2020 Oct 20.

Modern Internet Search Analytics and Total Joint Arthroplasty: What Are Patients Asking and Reading Online?

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Modern Internet Search Analytics and Total Joint Arthroplasty: What Are Patients Asking and Reading Online?

Tony S Shen et al. J Arthroplasty. 2021 Apr.

Abstract

Background: Patients considering total joint arthroplasty often search for information online regarding surgery; however, little is known about the specific topics that patients search for and the nature of the information provided. Google compiles frequently asked questions associated with a search term using machine learning and natural language processing. Links to individual websites are provided to answer each question. Analysis of this data may help improve understanding of patient concerns and inform more effective counseling.

Methods: Search terms were entered into Google for total hip and total knee arthroplasty. Frequently asked questions and associated websites were extracted to a database using customized software. Questions were categorized by topic; websites were categorized by type. JAMA Benchmark Criteria were used to assess website quality. Pearson's chi-squared and Student's t-tests were performed as appropriate.

Results: A total of 620 questions (305 total knee arthroplasties, 315 total hip arthroplasties) were extracted with 602 associated websites. The most popular question topics were Specific Activities (23.5%), Indications/Management (15.6%), and Restrictions (13.4%). Questions related to Pain were more common in the TKA group (23.0% vs 2.5%, P < .001) compared to THA. The most common website types were Academic (31.1%), Commercial (29.2%), and Social Media (17.1%). JAMA scores (0-4) were highest for Government websites (mean 3.92, P = .005).

Conclusion: The most frequently asked questions on Google related to total joint arthroplasty are related to arthritis management, rehabilitation, and ability to perform specific tasks. A sizable proportion of health information provided originate from non-academic, non-government sources (64.4%), with 17.1% from social media websites.

Keywords: machine learning; natural language processing; online health information; search analytics; total hip arthroplasty; total knee arthroplasty.

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Figures

Fig. 1
Fig. 1
Relative distribution of questions by Rothwell’s classification and by topic for THA and TKA. (A) The percentage of questions in the THA and TKA groups belonging to the Fact, Value, Policy, or Other classifications. (B) The number of questions in each topical category in the THA and TKA groups. Statistically significant differences (P < .05) in the number of questions within a topical category between the THA and TKA groups are indicated with ∗. THA, total hip arthroplasty; TKA, total knee arthroplasty.
Fig. 2
Fig. 2
Relative distribution of website sources by type of surgery and question topic. (A) The percentage of websites in the THA and TKA groups belonging to each of website sources (commercial, academic, single surgeon personal, medical practice, government, social media, and other). (B) The percentage of website belonging to each source stratified by question topic. Statistically significant (Pearson’s chi-squared test) sections for which P < .05 is designated with “∗”; P < .01 with “∗∗”; and P < .001 with “∗∗∗”

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