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 objective of this study is to determine whether key hospital-level financial and market characteristics are associated with whether rural hospitals merge. Hospital merger status was derived from proprietary Irving Levin Associates data for 2005 through 2016 and hospital-level characteristics from HCRIS, CMS Impact File Hospital Inpatient Prospective Payment System, Hospital MSA file, AHRF, and U.S. Census data for 2004 through 2016. A discrete-time hazard analysis using generalized estimating equations was used to determine whether factors were associated with merging between 2005 and 2016. Factors included measures of profitability, operational efficiency, capital structure, utilization, and market competitiveness. Between 2005 and 2016, 11% (n = 326) of rural hospitals were involved in at least one merger. Rural hospital mergers have increased in recent years, with more than two-thirds (n = 261) occurring after 2011. The types of rural hospitals that merged during the sample period differed from nonmerged rural hospitals. Rural hospitals with higher odds of merging were less profitable, for-profit, larger, and were less likely to be able to cover current debt. Additional factors associated with higher odds of merging were reporting older plant age, not providing obstetrics, being closer to the nearest large hospital, and not being in the West region. By quantifying the hazard of characteristics associated with whether rural hospitals merged between 2005 and 2016, these findings suggest it is possible to determine leading indicators of rural mergers. This work may serve as a foundation for future research to determine the impact of mergers on rural hospitals.

Purpose Amidst the COVID‐19 outbreak, the use of intensive care unit telemedicine (tele‐ICUs) may be one mechanism to provide patient care, particularly in rural parts of the United States. The purpose of this research was to inform hospital decision makers considering tele‐ICUs, policy makers weighing immediate and longer‐term funding and reimbursement decisions relative to tele‐ICU care, and researchers conducting future work evaluating tele‐ICUs. Methods We compared hospitals that reported providing teleintensive care to hospitals that reported not providing teleintensive care in the 2018 American Hospital Association Annual Survey (AHAAS). Differences between groups were tested using Pearson's chi‐square (categorical variables) and t ‐tests (continuous variables) using 0.05 as the probability of Type 1 error. The study sample included all US short‐term, acute care hospitals that responded to the AHAAS in 2018. Our key variable of interest was whether a hospital reported having any tele‐ICU capabilities in the 2018 AHAAS. Other factors evaluated were ownership, region, beds, ICU beds, outpatient visits, emergency department visits, full‐time employees, and whether a hospital was rural, a critical access hospital, a major teaching hospital, or part of a health system. Findings Larger, not‐for‐profit, nonrural, noncritical access, teaching hospitals that were part of a health system, particularly in the Midwest, were more likely to have tele‐ICUs. Over one‐third of hospital referral regions (HRRs) had zero hospitals with tele‐ICUs, 4 had all hospitals with tele‐ICU, and the median percent of hospitals with tele‐ICU by HRR, weighted by outpatient visits, was 11.3%. Conclusions and Implications We found wide variation in the prevalence of tele‐ICUs across HRRs and states. Future work should continue the evaluation of tele‐ICU effectiveness and, if favorable, explore the variation we identified for improved access to teleintensive care.

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