Telemedicine and e-Health

The use of virtual care (VC) among individuals with chronic disease is well-documented, yet evidence on quality of care outcomes, such as frequency of subsequent hospitalizations, emergency department (ED) visits, and mortality, is fragmented. This systematic review aimed to synthesize evidence of quality of care outcomes, namely subsequent outpatient encounters, hospital admissions, ED visits, and mortality, associated with VC among outpatients with chronic diseases.

: A search strategy was developed and applied to six electronic databases (Embase, MEDLINE, the Cochrane Library, PsycINFO, Web of Science, and CINAHL) for articles published between January 1, 2013 and July 6, 2024. Eligible studies included synchronous VC (e.g., live, video, or audio based) between a patient and health care provider. A narrative synthesis compared VC with in-person care, considering types of outpatient care, specialty, VC components, follow-up duration, and outcomes.

: After reviewing 5,679 abstracts, 24 articles were included. Studies were predominantly from the United States (n = 11), followed by Australia (n = 3) and Canada (n = 2). The follow-up durations ranged from 2 weeks to 2 years, with 14 studies having follow-up durations of 6 months or less. Studies predominantly reported no difference or lower rates of hospital admissions (n = 18/20), ED visits (n = 11/12), and mortality (n = 12/14) among outpatients who used VC compared with those who had in-person visits. Half of the studies (n = 3/6) reported more subsequent outpatient encounters for patients using VC for the initial outpatient encounter compared with those who had in-person visits.

: The review indicated that outpatient VC is associated with fewer or no different volume of hospital admissions or ED visits among people with chronic conditions but may be associated with an increased number of outpatient follow-up visits. Robust research at scale that considers the volume of VC consumed and associations with outcomes over longer follow-up periods is required.

Depression represents a major public health burden, especially in low- and middle-income countries (LMICs). Telepsychiatry provides a promising solution by offering remote mental health services, overcoming barriers such as limited resources, isolation, and cost. This study aimed to evaluate the comparative efficacy of different telepsychiatry interventions in LMICs by network meta-analysis of randomized controlled trials (RCTs).

: We searched PubMed, EMBASE, CENTRAL, CINAHL, PsycINFO, and ProQuest Dissertations & Theses from inception to May 2024 to identify all relevant studies. Telepsychiatry interventions were categorized as: (1) CBTAppGuided, a cognitive behavioral therapy (CBT) app with professional guidance; (2) CBTChatBot, a CBT app that uses a chatbot for guidance; (3) CBTApp, a CBT app without professional guidance; (4) Reminder; and (5) Consultation. Study quality was assessed according to the Effective Practice and Organization of Care guideline. Depression severity was calculated using summary standardized mean differences with 95% confidence intervals (CIs).

: Seven RCTs were included with a total of 1,469 adults (mean age range: 16.0–35.64 years). Compared with face-to-face usual care, the most effective telepsychiatry intervention was CBTAppGuided [−23.04, 95% CI: −26.12 to −19.96], followed by CBTChatBot [−5.27, 95% CI: −6.25 to −4.29]. Other interventions, including CBTApp [−0.83, 95% CI: −1.32 to −0.34], Reminder [−0.44, 95% CI: −0.72 to −0.16], and Consultation [−0.27, 95% CI: −0.78 to 0.26], demonstrated smaller effects. CBTAppGuided, CBTChatBot, CBTApp, and Reminder achieved statistically significant improvement, whereas Consultation did not show statistically significant improvement and was not different from face-to-face treatment.

: Telepsychiatry interventions, particularly CBTAppGuided, show potential for reducing depression severity in LMICs, with promising outcomes for both guided and unguided app-based formats. Further research is needed to confirm their effectiveness in resource-limited settings.

Telehealth has long offered promise for improving health care access, but due to restrictive regulations and technology limitations, historic use has been low. Despite telehealth’s unprecedented expansion during the COVID-19 pandemic, economic questions remain, raising uncertainty about telehealth’s future.

We used an economics lens to conduct a narrative review of the vast medical literature and nascent economic literature on telehealth. We reviewed evidence on demand-side and supply-side forces influencing telehealth adoption and evidence on telehealth’s impact on health care use, costs, effectiveness, and equity.

Current evidence is sparsely distributed across care types, telehealth modalities (e.g., phone, video, secure messaging), models of telehealth delivery, and pre- and post-pandemic periods. While the literature provides some signals that patients and clinicians are responsive to monetary costs of telehealth, more robust studies are needed, including studies on patient and provider time costs. Telehealth adoption appears to modestly increase outpatient care use, but evidence of its impact on costlier emergency or inpatient care use is needed. There is a lack of studies on monetary costs of telehealth, particularly the impact of telehealth on production costs. Importantly, there is a lack of high-quality studies on the comparative effectiveness of modalities. While there is a growing literature on disparities, studies that address confounders are needed to assess if telehealth can deliver on its promise to improve access for underserved populations.

: Our review paves the way for a stronger economics literature on telehealth, highlighting areas of future research.

State professional licensure has been cited as a significant barrier to widespread telehealth adoption, and states have developed strategies to reduce such licensure burdens through policy changes. We aimed to measure the association between state-level medical licensure policies and outpatient telehealth utilization between 2018 and 2022 among Medicare beneficiaries.

We conducted a quasi-experimental study of a 5% sample of age-qualifying Medicare fee-for-service beneficiaries between January 2018 and December 2022. We assessed state-level medical licensure policy for telehealth visits, captured as participation in Interstate Medical Licensure Compact (IMLC) before the COVID-19 public health emergency (PHE) and/or policy relaxation during the COVID-19 PHE. Outcomes included out-of-state telehealth (OOS-TH) and in-state telehealth (IS-TH). We evaluated the association between state-level policies and outcomes through logistic regression, adjusting for patient-level characteristics and month/year of the encounter.

We analyzed 141,199,029 outpatient encounters for 1,682,501 Medicare beneficiaries. In the pre-COVID-19 era, IMLC participation was associated with higher OOS-TH (adjusted odds ratio [aOR]: 2.24; 95% confidence interval [CI]: 2.09–2.40) but not IS-TH (aOR: 0.98; 95% CI: 0.96–1.01). In the COVID-19 era, we observed higher IS-TH in IMLC-only states (aOR: 1.09; 95% CI: 1.08–1.10) and states with COVID-19 policy relaxations (aOR: 1.11; 95% CI: 1.10–1.12). We observed lower OOS-TH utilization by IMLC participation (aOR: 0.74; 95% CI: 0.72–0.75) and COVID-19 policy relaxations (aOR: 0.83; 95% CI: 0.81–0.85).

Permissive licensure policies were higher telehealth utilization, though we observed mixed effects in telehealth type (IS-TH vs. OOS-TH) and by time (pre-COVID-19 vs. COVID-19). Variability in IS-TH and OOS-TH utilization may indicate that while local policies can improve telehealth access, interstate barriers still exist.

Analyze the impact of COVID-19 on outpatient mental health (OP-MH) utilization patterns, particularly telehealth, across eight different MH conditions with a 2-year follow-up.

This population-based cohort study uses a 5% random sample of Medicare beneficiaries aged ≥18 and newly diagnosed with one of the eight MH disorders: psychotic, depressive, bipolar, anxiety, trauma-related, substance-use, other MH disorders, and two or more MH disorders. Monthly OP-MH utilization patterns were compared among patients in 2020–2021 newly diagnosed in 2019 to comparable prepandemic cohorts newly diagnosed in 2017. Multiple logistic regression models were conducted to examine differences in telehealth utilization across MH conditions.

Across groups, patients were mostly aged 65–84 (n = 39,749 [72.4%] in 2017 and n = 40,513 [75.5%] in 2019), female (n = 33,387 [60.8%] in 2017 and n = 32,193 [60.0%] in 2019), and White (n = 48,314 [88.0%] in 2017 and n = 47,282 [88.1%] in 2019). Total OP-MH utilization dropped (a 27.5% decrease at its lowest) for all MH conditions at the pandemic’s onset compared with the nonexposure group. Although utilization increased postpandemic, slight disruptions remained until the end of 2021. Telehealth visits rose from 0.5% in January 2020 to 55% in April 2020, decreasing to 18% by December 2021. Regression analysis showed that patients with psychotic, bipolar, or trauma-related, and two or more MH disorders had higher odds of telehealth usage compared with those with anxiety, while patients with substance-use disorders had lower odds. Rural residents, older adults (65+), and men had lower odds of using telehealth, with residents of the Northeast and West regions showing higher odds compared with the South. Telehealth disparity profiles were uniquely associated with different MH conditions.

Findings highlight the need for tailored telehealth strategies among Medicare beneficiaries to address specific demographic and geographical disparities across MH conditions.

e-Health programs to empower patients with advanced cancer and their family caregivers can improve their quality of life. Successful engagement with e-Health programs requires digital competence. People with lower digital competence might be less likely to participate and complete e-Health trials, affecting trial validity. The objective of this work was to explore how digital competences differ between individuals according to sociodemographic characteristics and how it influences participation and retention in a trial with an e-Health component.

We analyzed data collected as part of the Dyadic Psychoeducational Interventions for patients with advanced cancer and their Informal Caregivers DIAdIC (DIAdIC) trial, in which a psychoeducational web and face-to-face program for patients with advanced cancer and their family caregivers were developed and tested. Recruitment log files were quantitatively assessed for nonparticipation reasons. Descriptive statistics outlined sociodemographic factors and digital competence. Multivariable linear regressions assessed digital competence. We reported unstandardized coefficients, 95% confidence intervals, and p-values. Logistic regressions examined retention rates. We reported odds ratios and 95% confidence intervals.

Among those refusing participation in the trial (N = 1752), 2.1% (n = 37) cited information and communication technology (ICT)-related factors. Enrolled patients reported lower digital competence than family caregivers (mean 3.07, SD 0.94 vs. 3.17, SD 0.090; p = 0.046). While digital competence varied by sociodemographic characteristics of patients and their family caregivers, digital competence did not significantly predict dropout.

ICT-related factors were rarely mentioned as a reason for nonparticipation. Digital competence is associated with sex, age, trial location, educational attainment, and perception of income. e-Health-related factors or digital competence are no reasons for nonparticipation in studies with an e-Health component.

Online self-triage/symptom checkers are a relatively new e-Health modality. We aimed to evaluate the degree to which patient’s chosen symptom during the use of an online self-triage tool was congruent with that chosen by a nurse performing phone triage.

Patient encounters from September 1, 2022, to September 30, 2023, were reviewed for patients who completed both online self-triage and a subsequent nursing phone triage within 24 hours. The symptoms chosen by the patient for their self-triage encounter and the symptoms chosen by the nurse during the subsequent nurse triage were reviewed. The symptoms chosen in these two triage encounters were then compared for congruency. A subset of our database was evaluated for congruency between the self-triage and the nurse phone triage endpoint recommendations.

There were 5,443 encounters meeting inclusion criteria to study for congruency between self-triage and nurse triage symptom choice. The range of time between self-triage and nurse triage ranged from 0 min to 1,439 min (23.9 hours) with a median of 23 minutes between self and nurse triage encounters. Symptom congruency between the two methods found 74.2% (4,038) to be completely congruent while 989 (18.2%) were somewhat congruent. Only 7.6% (416) had no apparent congruency. Out of 1,705 self and nurse triage dyads eligible for study for agreement between endpoint recommendations, 244 (14.3%) were under-triaged, 1,110 (65.1%) were triaged to the same level of care and 351 (20.6%) were over-triaged.

Congruency between symptoms chosen by the patient for triage and nurse triage were highly congruent with only 7.6% of the sample showing no apparent congruency between the self-triage symptom and the nurse triage symptom. When compared to nurse triage, most self-triage endpoint recommendations were either triaged to the same level of care or were over-triaged to a higher level of care.

The rapid expansion of telehealth-delivered medication for opioid use disorder (MOUD) during the COVID-19 pandemic highlighted critical digital divide issues in communities. How community context influences the digital divide remains unclear, creating uncertainty about ameliorating the gaps in access to tele-MOUD.

We qualitatively examined the perspectives of 315 opioid community coalition members who were part of the HEALing Communities Study (HCS) to understand how the digital divide created access barriers in urban and rural communities. Primary coding for all interviews used a deductive approach with codes derived from the Reach, Effectiveness, Adoption, Implementation, Maintenance/Practical Robust Implementation and Sustainability Model overarching HCS framework. Secondary coding used the nine determinants of Lythreatis’s 2022 digital divide framework, and inductive thematic analysis was used to identify themes with each of the nine determinants.

Shared issues across communities related to the digital divide, including trust, social support, technological infrastructure, digital literacy, policy changes, and pandemic-related disruptions, critically influenced telehealth expansion and effectiveness. Rural communities reported specific barriers around infrastructure and socioeconomics, whereas urban communities reported specific barriers around sociodemographic factors.

To address these digital divide issues, policymakers should continue to invest in rural infrastructure and improve internet access for underserved populations. Clear guidelines are also needed for when tele-MOUD is appropriate versus in-person visits and when urine drug screening is necessary. Additionally, emphasizing patient choice and maintaining in-person care is important to support equitable access to these services.

Telemedicine has seen rapid growth, especially following the COVID-19 pandemic, providing diverse options for patient care. This study, grounded in the Technology Acceptance Model, examines and compares factors influencing women’s usage intentions of telemedicine, considering their roles as both direct patients in gynecology and indirect patients in pediatrics.

The study conducted a survey to collect data from women who have used telemedicine services (N = 758). Structural equation modeling was employed to assess the relationships between variables, including previous satisfaction, social media health content consumption, perceived ease of use (PEOU), perceived usefulness (PU), trust, and future usage intention.

The results demonstrate that social media health content consumption, PEOU, PU, and trust in telemedicine have significant direct effects on future usage intention. PEOU and trust mediate the relationships between social media consumption, previous satisfaction, and future usage intention. Notably, the study reveals differences in the factors influencing telemedicine usage between pediatrics and obstetrics/gynecology. Social media health content consumption positively affects usage intention for gynecological but not for pediatric. Trust in telemedicine significantly enhances usage intentions for gynecology but not for pediatrics.

The findings reveal disparities in telemedicine usage patterns between obstetrics/gynecology and pediatrics. Practical implications suggest that telemedicine platforms should leverage social media to enhance health education and provide clear guidance, particularly for gynecological services. In addition, strengthening patient privacy protections is essential to build trust and promote telemedicine adoption.

To establish partnerships with county public health departments to expand telehealth access for referrals to Georgia Memory Net (GMN), a state-funded program focused on improving the early and accurate diagnosis of Alzheimer’s disease and other dementias.

Funding from the Coronavirus Aid, Relief, and Economic Security Act, and the Building Our Largest Dementia (BOLD) Infrastructure for Alzheimer’s Act supported GMN partnership development with Georgia Department of Public Health county health departments.

Telehealth infrastructure, including remote video neurological assessments and neuropsychological testing, is now available in 10 Georgia county health departments. Expansion efforts are in progress to bring telehealth services to additional counties, broadening GMN reach.

Telehealth evaluations delivered through county health departments provide an effective platform for expanding access to specialized dementia diagnosis and treatment, particularly in rural and underserved areas, enhancing early detection and care for patients throughout the state.

Disparities in dermatologic care access exist across sociodemographic factors, with racial minorities and uninsured individuals less likely to receive care. Teledermatology expanded during COVID-19, yet national disparities remain understudied.

: We conducted a repeated cross-sectional analysis of the 2020–2022 Medical Expenditure Panel Survey, including individuals with at least one dermatology visit. Multivariate logistic regression assessed associations between sociodemographic factors and teledermatology use, with two-part models examining spending.

Among 5,280 respondents (representing 68,315,000 patients), visits in 2021 (adjusted odds ratio [aOR] = 2.725, p = 0.003) had higher odds of teledermatology use, as did Black (aOR = 6.467, p < 0.001), Hispanic (aOR = 5.520, p = 0.012), and non-Black, non-White, non-Hispanic race patients (aOR = 3.416, p = 0.002). Patients with a bachelor’s degree (aOR = 5.470, p = 0.019) also had increased odds. Medicaid was associated with lower out-of-pocket costs.

Teledermatology use grew, benefiting racial minorities, but educational barriers persist. Targeted interventions are needed to enhance access.