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. 2023 Sep 21:23:101191.
doi: 10.1016/j.artd.2023.101191. eCollection 2023 Oct.

Age, Sex, and Education Level Predict Telehealth Engagement in Total Joint Arthroplasty Patients

Michael Lotito  1 , Matthew Jamison  2 , Cole Howell  3 , Adriana Liimakka  4 , Jeffrey Lange  2 , Antonia F Chen  2
Affiliations

Age, Sex, and Education Level Predict Telehealth Engagement in Total Joint Arthroplasty Patients

Michael Lotito et al. Arthroplast Today. .

Abstract

Background: Racial and other demographic predictors of total joint arthroplasty (TJA) telehealth engagement since the onset of the COVID-19 pandemic remain unclear. The purpose of the current study was to elucidate this relationship.

Methods: A retrospective, cross-sectional study on 732 primary TJA patients was conducted within a single hospital system from March 2020-December 2021 (during the pandemic). Patients were excluded if their race or education level could not be determined. Patient demographics (age, sex, body mass index, language) and TJA information were obtained. The number of telehealth visits and telehealth engagement were assessed. Engagement (yes/no) and engagement frequency across all demographics and each measure of telehealth (telemedicine, patient-reported outcome measurements [PROMs], and electronic patient portal [EPP] messaging) were analyzed using multivariate logistic and linear regression, respectively.

Results: Our results demonstrated that non-White race was not a significant predictor of binomial engagement or engagement frequency across all telehealth measures. Older age was a negative predictor of binomial engagement and engagement frequency with telemedicine and EPPs. Male sex was shown to be a negative predictor of binomial engagement with EPPs as well as PROM engagement frequency. Educational attainment of less than a college degree was a negative predictor of binomial engagement and engagement frequency with PROMs and EPPs.

Conclusions: This study demonstrates that older age, male sex, and lower education level were negative predictors of various measures of telehealth engagement. Non-White race was not a significant predictor. This data informs providers on how to improve access to virtual orthopaedic care.

Keywords: Age; Education level; Hip arthroplasty; Knee arthroplasty; Sex; Telemedicine.

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Figures

Figure 1
Figure 1
Inclusion criteria.
See this image and copyright information in PMC

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