Background: As the novel coronavirus disease (COVID-19) is widely spreading across the United States, there is a concern about the overloading of the nation’s health care capacity. The expansion of telehealth services is expected to deliver timely care for the initial screening of symptomatic patients while minimizing exposure in health care facilities, to protect health care providers and other patients. However, it is currently unknown whether US hospitals have the telehealth capacity to meet the increasing demand and needs of patients during this pandemic.Objective: We investigated the population-level internet search volume for telehealth (as a proxy of population interest and demand) with the number of new COVID-19 cases and the proportion of hospitals that adopted a telehealth system in all US states.Methods: We used internet search volume data from Google Trends to measure population-level interest in telehealth and telemedicine between January 21, 2020 (when the first COVID-19 case was reported), and March 18, 2020. Data on COVID-19 cases in the United States were obtained from the Johns Hopkins Coronavirus Resources Center. We also used data from the 2018 American Hospital Association Annual Survey to estimate the proportion of hospitals that adopted telehealth (including telemedicine and electronic visits) and those with the capability of telemedicine intensive care unit (tele-ICU). Pearson correlation was used to examine the relations of population search volume for telehealth and telemedicine (composite score) with the cumulative numbers of COVID-19 cases in the United States during the study period and the proportion of hospitals with telehealth and tele-ICU capabilities.Results: We found that US population–level interest in telehealth increased as the number of COVID-19 cases increased, with a strong correlation (r=0.948, P<.001). We observed a higher population-level interest in telehealth in the Northeast and West census region, whereas the proportion of hospitals that adopted telehealth was higher in the Midwest region. There was no significant association between population interest and the proportion of hospitals that adopted telehealth (r=0.055, P=.70) nor hospitals having tele-ICU capability (r=–0.073, P=.61).Conclusions: As the number of COVID-19 cases increases, so does the US population’s interest in telehealth. However, the level of population interest did not correlate with the proportion of hospitals providing telehealth services in the United States, suggesting that increased population demand may not be met with the current telehealth capacity. Telecommunication infrastructures in US hospitals may lack the capability to address the ongoing health care needs of patients with other health conditions. More practical investment is needed to deploy the telehealth system rapidly against the impending patient surge.

The number of social media users has increased substantially in the past decade, creating an opportunity for health-care professionals and patients to leverage social media for health communication. This study examines the recent use and predictors of social media for health communication in a nationally representative sample of US adults over time. We used 2013, 2014, and 2017 National Cancer Institute’s Health Information National Trends Survey to identify respondents’ use of social media for sharing health information or exchanging medical information with a health-care professional. We conducted bivariate analysis using the Pearson χ² test to assess the association of respondents’ basic demographic characteristics as well as health status and the use of social media for health communication. We performed multivariable logistic regression models to examine factors associated with the use of social media for health communication. We identified 4242 respondents (weighted sample size: 343 465 241 [2-year pooled sample]) who used social media for sharing health information and 4834 respondents (weighted sample size: 354 419 489 [2-year pooled sample]) who used social media for exchanging medical information. Multivariable analyses indicated the proportion of respondents who used social media for sharing health information has decreased (odds ratio [OR], 0.65; 95% confidence interval [CI], 0.49-0.85, P = .002), while the use of social media for exchanging medical information with a health-care professional has increased (OR, 1.88; 95% CI, 1.09-3.26, P = .025). The younger population had significantly higher odds of using social media for health communication. The study found no racial/ethnic disparities in the use of social media for health communication. Use of social media for sharing health information has declined, while exchanging medical information with health-care professionals has increased. Future research is needed to determine how to engage the population in social media–based health interventions, particularly for older adults.

Background: Dipeptidyl peptidase 4 (DPP4) is a cell surface protein that can act as a tumor suppressor or activator, depending upon the level of expression and interaction with the microenvironment and chemokines. DPP4 inhibitors are used to treat diabetes.Methods: We conducted this Surveillance Epidemiology and Endpoint Research‐Medicare database study to evaluate the role of DPP4 inhibitors on the overall survival (OS) of diabetic patients diagnosed with colorectal (CRC) and lung cancers.Results: Diabetic patients with CRC or lung cancer who were treated with DPP4 inhibitors exhibited a statistically significant survival advantage (hazard ratio [HR] of 0.89; CI: 0.82‐0.97, P = 0.007) that remained significant after controlling for all other confounders. When DPP4 inhibitors were used in combination of metformin which is known to suppress cancer, the survival advantage was even more pronounced (HR of 0.83; CI: 0.77‐0.90, P < 0.0001). Data were then analyzed separately for two cancer types. In the CRC‐only cohort, the use of DPP4 inhibitors alone had a positive trend but did not meet statistically significant threshold (HR of 0.87; CI: 0.75‐1.00, P = 0.055), while the combined use of DPP4 inhibitors and metformin was associated with statistically significant survival advantage (HR of 0.77; CI: 0.67‐0.89, P = 0.003). Similarly, for the lung cancer cohort, use of DPP4 alone was not found to be statistically significant (HR of 0.93; CI: 0.83‐1.03, P = 0.153), whereas lung cancer patients treated with the combination of DPP4 inhibitors and metformin showed statistically significant survival advantage (HR of 0.88; CI: 0.80‐0.97, P = 0.010).Conclusions: DPP4 inhibition in CRC and lung cancer is associated with improved OS, which possibly may be due to the effect of DPP4 inhibition on immunoregulation of cancer.

Background: Past studies examining barriers to patient portal adoption have been conducted with a small number of patients and health care settings, limiting generalizability. Objective: This study had the following two objectives: (1) to assess the prevalence of barriers to patient portal adoption among nonadopters and (2) to examine the association between nonadopter characteristics and reported barriers in a nationally representative sample. Methods: Data from this study were obtained from the 2019 Health Information National Trends Survey. We calculated descriptive statistics to determine the most prevalent barriers and conducted multiple variable logistic regression analysis to examine which characteristics were associated with the reported barriers. Results: The sample included 4815 individuals. Among these, 2828 individuals (58.73%) had not adopted a patient portal. Among the nonadopters (n=2828), the most prevalent barriers were patient preference for in-person communication (1810/2828, 64.00%), no perceived need for the patient portal (1385/2828, 48.97%), and lack of comfort and experience with computers (735/2828, 25.99%). Less commonly, individuals reported having no patient portal (650/2828, 22.98%), no internet access (650/2828, 22.98%), privacy concerns (594/2828, 21.00%), difficulty logging on (537/2828, 18.99%), and multiple patient portals (255/2828, 9.02%) as barriers. Men had significantly lower odds of indicating a preference for speaking directly to a provider compared with women (odds ratio [OR] 0.75, 95% CI 0.60-0.94; P=.01). Older age (OR 1.01, 95% CI 1.00-1.02; P<.001), having a chronic condition (OR 1.83, 95% CI 1.44-2.33; P<.001), and having an income lower than US $20,000 (OR 1.61, 95% CI 1.11-2.34; P=.01) were positively associated with indicating a preference for speaking directly to a provider. Hispanic individuals had significantly higher odds of indicating that they had no need for a patient portal (OR 1.59, 95% CI 1.24-2.05; P<.001) compared with non-Hispanic individuals. Older individuals (OR 1.05, 95% CI 1.04-1.06; P<.001), individuals with less than a high school diploma (OR 3.15, 95% CI 1.79-5.53; P<.001), and individuals with a household income of less than US $20,000 (OR 2.78, 95% CI 1.88-4.11; P<.001) had significantly higher odds of indicating that they were uncomfortable with a computer. Conclusions: The most common barriers to patient portal adoption are preference for in-person communication, not having a need for the patient portal, and feeling uncomfortable with computers, which are barriers that are modifiable and can be intervened upon. Patient characteristics can help predict which patients are most likely to experience certain barriers to patient portal adoption. Further research is needed to tailor implementation approaches based on patients’ needs and preferences.

Objective: Patient portal functionalities, such as patient–physician e-communication, can benefit patients by improving clinical outcomes. Utilization has historically been low but may have increased in recent years due to the implementation of Stage 2 Meaningful Use for electronic health records. This study has 2 objectives: 1) to compare patient portal utilization rates before Stage 2 (2011–2013) and after Stage 2 (2014–2017), and 2) to examine whether disparities in patient portal utilization attenuate after Stage 2. Materials and Methods: We conducted an observational study using a pooled cross-sectional analysis of 2011–2017 National Health Interview Survey data (n = 254 183). Results: The mean percent use of patient portals significantly increased from the pre-Stage 2 to the post-Stage 2 period (6.9%, 95% CI, 6.2–7.5; P < .001). Non-Hispanic Black individuals (OR 0.81, 95% CI, 0.76–0.86; P < .0001) and Hispanic individuals (OR 0.79, 95% CI, 0.74–0.84; P < .0001) have lower odds of using patient portals compared to non-Hispanic White individuals. Although we found independent effects of race/ethnicity, we did not find a statistically significant interaction between race/ethnicity and time. We found a similar level of increase in patient portal utilization from the pre- to postperiod across racial and ethnic groups. Discussion: Health care policies such as Stage 2 Meaningful Use are likely contributing to increased patient portal utilization across all patients and helping to attenuate disparities in utilization between subgroups of patients. Conclusion: Further research is needed to explore which patient portal functionalities are perceived as most beneficial to patients and whether patients have access to those functionalities.