Disparities in Telemedicine Utilization During COVID-19 Pandemic: Analysis of Demographic Data from a Large Academic Orthopaedic Practice

Achieving Health Equity: Combatting the Disparities in American Access to Musculoskeletal Care : Disparities Exist in Every Aspect of Orthopaedic Care in the United States - Access to Outpatient Visits, Discretionary and Unplanned Surgical Care, and Postoperative Outcomes. What Can We Do?

PURPOSE OF REVIEW

Healthcare disparities influence multiple dimensions of orthopaedic care including access, burden and incidence of disease, and outcome in varying populations. These disparities impact healthcare at both the micro and macro scale of the healthcare experience from individual patient-physician relationships to reimbursement rates across the United States. This article provides a review of how healthcare disparities contribute to the landscape of orthopaedic care and specifically highlights how disparities affect outpatient visits, discretionary and unplanned surgical care, and postoperative outcomes.

RECENT FINDINGS

Current research demonstrates the widespread presence of healthcare disparities in the field of orthopaedics and gives both objective and subjective evidence confirming disparities' measurable influence. The disparities most highlighted by our review include differences in orthopaedic care based on insurance type and race. Currently disparities in orthopaedic care are deeply connected to patient insurance status and race. In the outpatient setting insurance significantly impacts access to care, travel burden, and utilization of services. The emergent setting is similarly influenced with measurable differences in lack of access to acute care, rates of inappropriate triage, and timeliness of care based on insurance status and race. Additionally, the postoperative period is not immune to disparities with likelihood of follow up, experience of catastrophic medical expenses, and postoperative outcomes also being affected. Addressing these disparities is a pressing need and may include solutions like wider expansion and acceptance of publicly funded insurance and the development of readily available and easily measurable metrics for healthcare equity and quality in vulnerable populations.

The role of increasing synchronous telehealth use during the COVID-19 pandemic on disparities in access to healthcare: A systematic review

INTRODUCTION

The COVID-19 public health emergency led to an unprecedented rapid increase in telehealth use, but the role of telehealth in reducing disparities in access to care has been questioned. The objective of this study was to conduct a systematic review to summarize the available evidence on how telehealth during the COVID-19 pandemic was associated with telehealth utilization for minority groups and its role in health disparities.

METHODS

We conducted a systematic review focused on health equity and access to care by searching for interventional and observational studies using the following four search domains: telehealth, COVID-19, health equity, and access to care. We searched PubMed, Embase, Cochrane CENTRAL, CINAHL, telehealth.hhs.gov, and the Rural Health Research Gateway, and included any study that reported quantitative results with a control group.

RESULTS

Our initial search yielded 1970 studies, and we included 48 in our final review. The most common dimensions of health equity studied were race/ethnicity, rurality, insurance status, language, and socioeconomic status, and the telehealth applications studied were diverse. Included studies had a moderate risk of bias. In aggregate, most studies reported increased telehealth use during the pandemic, with the greatest increase in non-minority populations, including White, younger, English-speaking people from urban areas.

DISCUSSION

We found that despite rapid adoption and increased telehealth use during the public health emergency, telehealth did not reduce existing disparities in access to care. We recommend that future work measuring the impact of telehealth focus on equity so that features of telehealth innovation can reduce disparities in health outcomes.

The theory behind and factors influencing the use of telemedicine during the COVID-19 pandemic: A systematic review

A paradigm change in patient health care toward telemedicine services was necessary in 2020 due to the COVID-19 pandemic, which broke out at the end of 2019. Theories used in determining the determinants of telemedicine utilization are various theories. Research conducted on the use of telemedicine still has doubts about the basic theory used in analyzing the factors that influence telemedicine, especially during the Covid-19 pandemic. The goal of this study is to outline the fundamental principles of telemedicine utilization during the Covid-19 outbreak and the variables that affect it. This Literature Review uses the scoping review method with the tool procedure, namely PRISMA. Based on the conducted literature review, there are 12 scholarly papers addressing the variables that affect the utilization of telemedicine services. During the Covid 19 epidemic, more individuals in many nations used telemedicine services. Anderson's theory of health care use and the idea of technology adoption or acceptance serve as the foundational theories for forecasting the variables that affect the use of telemedicine. The utilization of telemedicine is influenced by 29 different factors that come from different theories. The desire for health, exposure to COVID 19, co-morbidities, social media usage, avoiding contamination, time efficiency, ease of use of services, social impact, and hedonic incentive are among the factors associated to the COVID 19 pandemic.

Effects of the COVID-19 Pandemic on Humeral Shaft Fracture Management and Its Outcomes

Background and objective The coronavirus disease 2019 (COVID-19) pandemic necessitated a sudden and drastic shift in patient management throughout the healthcare system, to curb the spread of the disease and deal with resource limitations. Many surgical cases were canceled or delayed with only the most urgent and emergent cases taken up for treatment. It is unknown if and how these alterations affected patient outcomes. The purpose of this study was to compare time to fracture care and outcomes between patients treated for humeral shaft fractures prior to the COVID-19 pandemic and those treated during the pandemic. We hypothesized that the pandemic cohort would have a prolonged time to fracture care and worse outcomes than the pre-pandemic cohort. Materials and methods This was a retrospective cohort study performed within a single healthcare system. All humeral shaft fractures treated from March to June 2019 (pre-pandemic cohort) and March to June 2020 (pandemic cohort) were identified using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes and ICD-10-CM codes as well as Current Procedural Terminology (CPT) codes. Data on demographics, fracture characteristics, treatment, and outcomes were collected via chart and radiograph review. Outcomes analyzed included time to being made weight-bearing as tolerated (WBAT), radiographic union, and final follow-up; range of motion (ROM) at radiographic union and final follow-up; and rate of complications. Results The pre-pandemic cohort (n=19) was significantly younger with a mean age of 29 years than the pandemic cohort (n=17) with a mean age of 49 years (p=0.010). There were no other significant differences in demographics, fracture characteristics, or treatment type between the groups. Time to fracture care was not significantly different in the pre-pandemic cohort (five days) versus the pandemic cohort (four days). Time to being made WBAT, radiographic union, and final follow-up were not significantly different between the pre-pandemic (86, 113, and 98 days) and the pandemic cohorts (77, 106, and 89.5 days). ROM measurements in abduction at radiographic union were significantly different between the cohorts: in the pre-pandemic cohort, 100% of patients reached greater than 160 degrees; in the pandemic cohort, only 16.7% of patients reached greater than 160 degrees (p=0.048). There was a non-significant decrease in the proportion of patients who achieved the maximal category of ROM measurements in forward elevation and extension at radiographic union and abduction, forward elevation, and extension at final follow-up, as well as a non-significant increase in visual analog scale (VAS) pain scores at final follow-up between cohorts. There were no significant differences in the rate of complications. Conclusions Despite limited resources, reduced operating room availability, and increased utilization of virtual visits due to the COVID-19 pandemic, patients with humeral shaft fractures may not have faced delays in fracture care or worse outcomes compared to the pre-pandemic period. The pandemic cohort may have experienced significantly decreased ROM compared to the pre-pandemic cohort, which may reflect the decreased availability of physical therapy services and overall decreased activity levels due to the quarantine orders. However, we could not identify any other significant differences in the type of treatment, pain, complications, or time to union.

The environmental impact of surgical telemedicine: life cycle assessment of virtual vs. in-person preoperative evaluations for benign foregut disease

BACKGROUND

Health care accounts for almost 10% of the United States' greenhouse gas emissions, accounting for a loss of 470,000 disability-adjusted life years based on the health effects of climate change. Telemedicine has the potential to decrease health care's carbon footprint by reducing patient travel and clinic-related emissions. At our institution, telemedicine visits for evaluation of benign foregut disease were implemented for patient care during the COVID-19 pandemic. We aimed to estimate the environmental impact of telemedicine usage for these clinic encounters.

METHODS

We used life cycle assessment (LCA) to compare greenhouse gas (GHG) emissions for an in-person and a telemedicine visit. For in-person visits, travel distances to clinic were retrospectively assessed from 2020 visits as a representative sample, and prospective data were gathered on materials and processes related to in-person clinic visits. Prospective data on the length of telemedicine encounters were collected and environmental impact was calculated for equipment and internet usage. Upper and lower bounds scenarios for emissions were generated for each type of visit.

RESULTS

For in-person visits, 145 patient travel distances were recorded with a median [IQR] distance travel distance of 29.5 [13.7, 85.1] miles resulting in 38.22-39.61 carbon dioxide equivalents (kgCO₂-eq) emitted. For telemedicine visits, the mean (SD) visit time was 40.6 (17.1) min. Telemedicine GHG emissions ranged from 2.26 to 2.99 kgCO₂-eq depending on the device used. An in-person visit resulted in 25 times more GHG emissions compared to a telemedicine visit (p < 0.001).

CONCLUSION

Telemedicine has the potential to decrease health care's carbon footprint. Policy changes to facilitate telemedicine use are needed, as well as increased awareness of potential disparities of and barriers to telemedicine use. Moving toward telemedicine preoperative evaluations in appropriate surgical populations is a purposeful step toward actively addressing our role in health care's large carbon footprint.

The Efficacy of Telemedicine Versus In-Person Education for High-Risk Patients Undergoing Primary Total Joint Arthroplasty

BACKGROUND

While multiple studies have demonstrated the positive impact of preoperative education on total joint arthroplasty (TJA) outcomes, the traditional method of conducting in-person individualized counseling or group education may limit access to these resources for a subset of the population. This study aimed to evaluate the use of preoperative telemedicine and in-person educational programs for primary TJA patients to determine if the utilization of telemedicine is inferior to in-person education in high-risk populations.

METHODS

A retrospective chart review of all "high-risk" patients undergoing primary unilateral TKA or THA by 1 of 10 board-certified surgeons at a single institution over 1 year was performed. Patients were prospectively classified as high-risk based on race/ethnicity, comorbidities, and socioeconomic and psychosocial factors. Demographics, comorbidities, and hospital outcomes were compared between patients receiving preoperative nurse navigator education via telemedicine versus those receiving face-to-face education.

RESULTS

When comparing the interventions, telemedicine education was noninferior to face-to-face visits. No significant differences between postoperative length of stay, discharge home, 30-day emergency department return, or 30-day readmission rates were noted. Within the telemedicine group, patients who received video consultations were found to be 6 times more likely to be discharged home after surgery (odds ratio (OR): 5.95, 95% confidence interval (CI): 2.00 to 25.49; P = .004) and less likely to have a 30-day readmission than the phone consultations (OR: 0.36, 95% CI: 0.12 to 0.94: P = .050).

CONCLUSION

This study demonstrates that telemedicine is not inferior to in-person preoperative education for patients undergoing unilateral TJA, although video-based consultation may improve outcomes over phone-only education.

The Impact of the COVID-19 Pandemic on Internet Use and the Use of Digital Health Tools: Secondary Analysis of the 2020 Health Information National Trends Survey

Background

The COVID-19 pandemic increased the use of digital tools in health care (eg, patient portal, telemedicine, and web-based scheduling). Studies have shown that older individuals, racial/ethnic minority groups, or populations with lower educational attainment or income have lower rates of using digital health tools. Digitalization of health care may exacerbate already existing access barriers in these populations.

Objective

This study evaluated how use of digital tools to asynchronously communicate with clinicians, schedule appointments, and view medical records changed near the beginning of the pandemic.

Methods

Using 2020 Health Information National Trends Survey (HINTS) data, we examined internet use and 7 digital health technology use outcomes (electronic communication with a provider, electronic appointment scheduling, electronic test result viewing, patient portal access, portal use to download health records, portal use for patient-provider communication, and portal use to view test results). The HINTS surveyors designated surveys received after March 11, 2020, as postpandemic responses. Using weighted logistic regression, we investigated the impact of the pandemic after adjusting for sociodemographic traits (age, race/ethnicity, income, education, and gender), digital access (having ever used the internet and smartphone/tablet ownership), and health-related factors (insurance coverage, caregiver status, having a regular provider, and chronic diseases). To explore differences in changes in outcomes among key sociodemographic groups, we tested for significant interaction terms between the pandemic variable and race/ethnicity, age, income, and educational attainment.

Results

There were 3865 respondents (1437 prepandemic and 2428 postpandemic). Of the 8 outcomes investigated, the pandemic was only significantly associated with higher odds (adjusted odds ratio 1.99, 95% CI 1.18-3.35) of using electronic communication with a provider. There were significant interactions between the pandemic variable and 2 key sociodemographic traits. Relative to the lowest income group (<US $20,000), the highest income group (≥US $75,000) had increased growth in the odds of ever having used the internet in postpandemic responses. Compared to the most educated group (postbaccalaureates), groups with lower educational attainment (high school graduates and bachelor’s degree) had lower growth in the odds of using electronic communication with a provider in postpandemic responses. However, individuals with less than a high school degree had similar growth to the postbaccalaureate group in using electronic communication with a provider.

Conclusions

Our study did not show a widespread increase in use of digital health tools or increase in disparities in using these tools among less advantaged populations in the early months of the COVID-19 pandemic. Although some advantaged populations reported a greater increase in using the internet or electronic communication with a provider, there were signs that some less advantaged populations also adapted to an increasingly digital health care ecosystem. Future studies are needed to see if these differences remain beyond the initial months of the pandemic.