The global pandemic caused by the severe acute respiratory syndrome coronavirus 2 is creating a historic challenge for health care providers, patients, and societies throughout the world. Hospitals are drastically increasing intensive care capacities in an effort to contain the effects of the pandemic. However, staffing, technical, and infrastructural limitations are impeding progress in this regard. With an estimated intensive care unit (ICU) hospitalization rate of 5%, the pandemic quickly surpassed the global hospital care capacities [1]. In response to the crisis, new approaches are urgently needed to avoid a medical crisis.

To bring specialist care to the patients, diverse telemedical approaches have been implemented into patient care routine worldwide in both the ambulatory and hospital sectors (from the home setting to admission, treatment, and discharge), and adaptations have been developed for each use case (Figure 1).

In the area of acute care medicine, specifically intensive care medicine, telemedicine has proven to be a success story. For example, the introduction of a remote intensivist program in two US tertiary care hospitals has led to a significant reduction of mortality (9.4% vs 12.9%; relative risk 0.73; 95% CI 0.55-0.95) and has proven to be cost-effective [2].

As a result of the worldwide shortage of medical professionals, not all patients are treated under the supervision of a specialized doctor. Although, it is estimated that, if specialized ICU physician staffing was implemented in nonrural US hospitals, approximately 53,000 lives and US $5.4 billion would be saved annually; as of 2010, only 10%-15% of the US ICUs were able to provide intensivist care, clearly a resource urgently needed in response to the coronavirus disease (COVID-19) [3]. Multiple studies have shown that providing a dedicated intensivist at an ICU leads to a significant reduction in mortality and reduces the length of stay [4,5]. Worldwide, telemedical tools have been rapidly adopted to the intensive care setting, providing specialist telemedical guidance to remote hospitals.

The advantages in the reduction of distance barriers between patients and physicians are also used to improve access to high-level intensive care in otherwise medically underserved areas. In adult intensive care wards, the introduction of telemedical surveillance by a specialized intensivist reduced severity-adjusted mortality by 33% and 30%, and the incidence of ICU complications by 44% and 50% in two intervention periods in an observational time series cohort study [6]. A recently published large retrospective study in the United States showed similar results as well for adult step-down or progressive care units, where patients in the telemedical intervention group had a survival benefit of 20% and had a significantly lower length of stay [7]. Consequently, telemedical solutions are also used for “in-house screening” of patients with COVID-19 (eg, by distributing tablet computers in emergency departments), minimizing the time of direct patient contact and, thus, cutting down the infection risk [8,9]. These findings were supported by a systematic review and meta-analysis of 13 studies involving 35 ICUs using a pre-post-design. The authors concluded that there was a reduction in ICU mortality (pooled odds ratio 0.80, 95% CI 0.66-0.97; P=.02) and a reduction in length of stay but stated that in-hospital mortality was not proven to be significantly reduced (pooled odds ratio 0.82, 95% CI 0.65-1.03; P=.08) [10].

Numerous worldwide experiences have shown that the formation of “telemedical excellence centers” is an efficient and fast way to provide telemedical specialist care to large populations. This is especially true for the reaction to global crises such as the coronavirus pandemic, as these telemedical centers can be created rapidly, concentrate specialist care locally, and deliver the highest quality care within large regions without travel restrictions or risk of infection for medical staff [11]. For example, in reaction to the pandemic and under support of the federal government of North-Rhine Westphalia in Germany, the University Hospitals of Aachen and Münster have built up a “virtual hospital” structure within weeks that provides a day-and-night availability of specialist intensivist and infectologist care for over 200 regional hospitals [12-14]. In China, the National Telemedicine Center of China in Zhengzhou has established a telemedicine-enabled outbreak alert and response network, connecting over 120 smaller hospitals [15]. In rapid response to the COVID-19 pandemic, a telemedical network was created in the Sichuan Province in Western China [11]. The first results of the retrospective success analysis showed telemedicine to be a “feasible, acceptable, and effective” way to provide health care and “allowed for significant improvements in health care outcomes.” Furthermore, entirely new, data-driven disease containment strategies using contact tracing–based mobile sensors were rapidly developed and established to track and impede chains of infection [16].

In addition, within the ambulatory sector (eg, in home care and outpatient clinics), telemedical solutions are on the rise worldwide in response to the coronavirus crisis [17]. Over 50 US hospitals established or reinforced their telemedical health systems to allow clinicians to see patients who are at home without the risk of infection for medical professionals [8]. This might also be true for non–infection-related consultations (eg, in orthopedics [18] or chronic conditions [19]), reducing the need for repeated physical patient-physician contact and, consequently, the risk of cross-infections within a practice visit. A tool for the initial medical assessment of COVID-19 has been made available to German citizens by the German Central Institute for Statutory Health Insurance Physicians. The “COVID-Guide” is intended to enable patients to make an initial assessment of their own health situation in the event of possible complaints and uncertainties in connection with the coronavirus, which serves to accompany patients at home with telemedical means and, thus, recognize the occurrence of specific alarm symptoms at an early stage [20]. In contrast to other countries (eg, the Netherlands, the United Kingdom), German patients have generally free access to all medical specialties. A referral is not mandatory from the patient’s point of view. A patient can consult a specialist immediately and does not have to take a detour via a general practitioner. In the case of so-called family doctor–centered care, members of the statutory health insurance are bound to contract doctors of the health insurance companies when choosing a (telemedical) doctor. Telemedical consultations are mostly performed through direct patient-doctor contact.

To establish telemedicine in routine care, user acceptance by medical professionals is of the utmost importance to make effective use of telemedical resources. Furthermore, infrastructural problems (eg, broadband internet connectivity, organizational structures) are still thought to be a relevant factor hindering effective implementation of telemedical care [21]. To our knowledge, no structured, large-scale assessment of the perception of telemedical services within the crisis has been carried out accounting for differences between levels of care and medical professional groups. In this study, we examine the current status quo of the availability and routine use of telemedical solutions, the user acceptance, and the subjectively perceived burdens on telemedical approaches. Telemedical providers often serve as an additional source for medical knowledge. This is particularly important in crises, where the distribution of reliable information is key. Consequently, we assess the perception of the quality of public information among professional groups and their preferred information channels to evaluate efficient communication with the aforementioned providers.

Survey data collection took place on all days of the evaluated time frame between March 27, 2020, and April 11, 2020. Participants were acquired via numerous communication channels, taking into account the heterogeneous access and technical skills of different medical professional groups. Access (weblink) to the survey system was distributed through official communication channels and mailing lists of numerous medical societies and social media groups. Furthermore, several large- and medium-sized hospitals shared the weblink to the survey within their internal communication systems (eg, intranet platforms). The telemedical survey was part of a larger survey on coronavirus conducted within the time frame.

Data acquisition took place via a publicly accessible, web-based survey system (LimeSurvey, version 3.22.10; LimeSurvey GmbH) based on the programming language Hypertext Preprocessor (version 7.1.33, The PHP Group) and JavaScript (version 262, June 2017, ECMA International). The survey was accessible through all common web browsers as well as mobile phones.

All computational infrastructure was hosted on an Apache server (The Apache Software Foundation), while the system was physically hosted in Nuremberg, Germany to comply with all European data protection laws. No technical failure or server downtime was observed during the acquisition period. Data was stored using a My Structured Query Language (MySQL) database (Oracle Corporation).

All statistical preprocessing and analysis was carried out using the R statistical programming language [22] (Version 3.6.3, R Foundation for Statistical Computing) and the statistical software Jamovi (Version 1.2.16.0, The Jamovi Project) [23].

Appropriate sample size was calculated as described in Multimedia Appendix 1. A confidence level of 99% and an acceptable error margin of 3% were assumed [24].

The descriptive statistical data is laid out in total numbers as well as in relative percentages.

Assumption of normal distribution was tested using the Shapiro-Wilk test.

We used a nonparametic one-way analysis of variance to address potential differences between the professional groups. Post-hoc analysis was performed using Dwass-Steel-Chritchlow-Figner pairwise comparisons, when appropriate. Correlation analysis for ordinal variables was carried out using Spearman rho.

A total of 2927 participants took part in the survey within the observed time frame between March 27, 2020, and April 11, 2020. We calculated the ideal sample size for the survey to reach significance as described in the methods section. We assumed there were a total of 5.6 million medical professionals employed within the German health care domain, as reported by the German Federal Office of Statistics [25]. On a confidence level of 99% and within an acceptable error margin of 3%, the required sample rate was determined to be 1849 participants.

The median observed age was 43.0 (SD 11.8) years. Of the 2827 participants, 51.1% (n=1446) of participants identified as females, 47.6% (n=1345) identified as males, and 0.3% (n=69) chose not to disclose gender. The majority of the survey participants worked within a university hospital setting (n=1238, 43.8%), while 26.9% (n=749) worked within smaller regional hospitals. The ambulatory sector was represented by 21.6% (n=611) participants within private practices, 2.1% (n=60) within private clinics, and 1.6% (n=45) in a rehabilitation clinic setting. A total of 111 (3.9%) participants disclosed their work environment as “other” (eg, ambulatory nursing services). When asked about their profession, 65.6% (n=1855) identified as doctors, 29.5% (n=833) as nursing staff, and 4.9% (n=139) as other medical professionals such as therapeutic staff; Table 1).

Visualization of the gender distribution already showed indications of a non-Gaussian distribution. We further assessed the pattern by performing a Shapiro-Wilk test, resulting in a statistic value of 0.98 (P<.001), thus confirming the hypothesis of a nonnormal distribution (Figure 2).

Figure 2

Age distribution split by gender within the study participants.

Participants were asked to estimate the significance of telemedicine during the coronavirus crisis (“How high do you estimate the significance of telemedicine and teleconsultations in the current crisis?”). Of the 2730 participants that responded to this question, the importance of telemedicine and teleconsultation was rated as high (n=1065, 39%) to neutral (n=720, 26.4%). The majority of the doctors (1036/1806, 57.4%), nurses (508/797, 63.8%), and other medical professionals (90/127, 70.9%) estimated the significance of telemedicine and teleconsultation within the COVID-19 crisis as either high (4) or very high (5).

A subcohort analysis of the different groups, however, showed significant (χ²₅=15.8; P<.001) differences in the perception of telemedicine. In a subcohort analysis, differences between doctors and nurses (W=4.05, P=.01) as well as between doctors and others (W=4.36, P<.001) were shown to be significant, while differences between nurses and others did not reach statistical significance (W=2.62, P=.15).

Closer analysis of the perception of telemedicine between health care professionals (Figure 3a) working in a diverse work environment (Figure 3b) revealed different response patterns within the observed groups. One difference was the significantly higher perception of telemedicine amongst health care workers within the stationary and hospital sector (χ²₅=190; P<.001) compared to the ambulatory and practice sector, and a significantly higher estimation in university hospital workers (W=–18.39, P<.001) and regional hospital workers (W=–9.99, P<.001) compared to private practices (Table 2).

Further, correlation analysis revealed a significant negative correlation of the participant’s age with the perception of telemedicine’s significance (p=–0.23; P<.001).

We further assessed the current availability of telemedical services during the pandemic. Despite being acknowledged as a significant tool during the COVID-19 crisis by the majority of participants, telemedicine was not yet part of the daily routine in most of the work environments. In only 20.2% (240/1189) of the university hospitals, 20.3% (12/59) of the private clinics, and 5.6% (41/726) of the regional hospitals telemedical consulting was in routine use. In contrast, 36% (214/595) of the participants working in a private practice setting already used telemedical tools routinely. Further analysis revealed a large proportion of hospitals that did not have access to telemedicine at all (405/1189, 34.1% for university hospitals and 393/726, 54.1% for regional hospitals; Table 3).

Furthermore, significance analysis and post hoc analysis revealed significant differences (χ²₄=295, P<.001) between university hospitals and regional hospitals (W=–15.26, P<.001), between private practices and private clinics (W=–5.04, P=.01), and between private clinics and rehabilitation clinics (W=–5.88, P<.001).

To further investigate the reasons for the low use of telemedical tools, we addressed potential regulatory or technical obstacles within the participants’ work environment. Although participants working in private practices (239/594, 40.2%) or private clinics (23/59, 39.0%) experienced no regulatory or technical obstacles, most of the medical professionals working in university hospitals (586/1190, 49.2%) experienced at least partial obstacles. In total, only 22.7% (616/2711) answered the question “Do you experience regulatory or technical obstacles for telemedicine within you work environment?” with “yes” (Table 4).

We assessed the perception of information quality and quantity within the different professional groups and the preferred communication channels to identify the most appropriate information strategy in a pandemic situation. Information was rated on a 5-point Likert scale, ranging from very poor (1) to very good (5). A majority of the participants rated the information quality either neutral (606/2827, 21.4%) or good (n=1341, 47.4%). Information quantity of public information concerning the coronavirus crisis was rated similar with neutral (981/2827, 34.7%) or good (n=1101, 38.9%). The detailed subgroup analysis, however, revealed that, although the majority of doctors rated the information quality as good (942/1855, 50.8%) or very good (n=213, 11.5%), a majority of the participating nurses rated the quality of public information lower on a Likert scale with 3 (neutral; 233/833, 28.0%) or 4 (good; n=330, 39.6%). When addressing the satisfaction on information quantity, the differences were smaller; 42.0% (779/1855) of the doctors and 33.4% (278/833) of nursing staff rated the information quantity with a 4 (“good”; Tables 5 and 6).

We performed a subcohort analysis to address the significance of differences between the professional groups. Differences between groups were significant for both quality (χ²₂=69.3; P<.001) and quantity (χ²₂=47.9; P<.001). Post hoc analysis with Dwass-Steel-Chritchlow-Figner pairwise comparisons showed significant differences in perception of information quality between doctors and nursing staff (P<.001), and nursing staff and other groups (P<.001), while differences between nurses and others were not shown to be significant. Addressing the information quantity, significant differences between doctors and nursing staff (P<.001), and doctors and others (P=.003) was shown, while the differences between nursing staff and other medical professionals were not significant (P=.96; Table 7).

We further assessed the main information sources for information within the COVID-19 pandemic. Out of the 2733 participants that responded to this question, a total of 83.6% (n=2284) of medical professionals used websites, 61.1% (n=1671) used television, and 30.7% (n=840) used newspapers within their top 3 sources of information on the COVID-19 pandemic. Social media was relatively low in use (n=388, 14.2%), and 34.6% (n=945) informed themselves through colleagues (Table 8).