Clinician Telemedicine Perceptions During the COVID-19 Pandemic
Introduction
Telemedicine is medical care provided remotely using technology. There is a growing interest in telemedicine because of its convenience, accessibility, and lower costs. Cost analyses suggest that virtual visits can cost less than in-person encounters. Two studies estimated a very low threshold (80–151 patients a year1,2) to reach a point where telemedicine was more cost-effective than in-person visits in specialty orthopedic care with 45% less cost per patient.3 Telemedicine is associated with satisfactory ratings by patients and clinicians4–8 and patient–physician communication is comparable with in-person visits.9 Clinician concerns about technical hurdles (training and implementation), legal and ethical rules such as lack of interstate licensure reciprocity, concerns about maintaining patient confidentiality, concerns about limited precedent regarding liability issues, lack of widespread reimbursement, and lack of universal accessibility have limited adoption of telemedicine to date. Yet the potential benefits of telemedicine include improved access, more equitable care, and lower costs.10–15 Additionally, advances in technology and access to smart phones and internet access have made telemedicine more accessible.
The coronavirus disease 2019 (COVID-19) pandemic led to a rapid expansion in telehealth worldwide. As a result, the majority of clinicians have had experienced using telemedicine on a variety of platforms. This experience may have changed their views of telemedicine, and it may become more utilized even after the pandemic is over.
The primary purpose of this study was to determine if there are any factors independently associated with a clinician desiring to continue telemedicine services after the COVID-19 pandemic. Secondarily, we sought factors independently associated with clinician satisfaction with the quality of care provided through telemedicine. The third goal was to determine if there were any factors independently associated with telemedicine platform preference by clinicians.
Materials and Methods
Institutional review board approval (2018-07-0137) was given and qualitative interviews were conducted in May 2020 with seven clinicians from a multispecialty group known for their enthusiasm for telemedicine and early adoption in their practices, either before or after COVID-19-related changes. These qualitative interviews were analyzed using thematic content analysis and a survey was constructed to further elucidate these themes. Members of the physician group were invited to complete the survey through e-mail and were provided with a description of the study and after which, completion of the questionnaire implied informed consent. Questionnaires were completed online using Qualtrix (Provo, Utah), a secure web-based survey application.
Participants completed a survey about demographics, telemedicine experience, satisfaction with various elements of telemedicine encounters, desired features in a telemedicine platform, personality elements, and preferences. Demographic questions included years in practice, specialty, patient population, practice location, and practice context. Practice locations were approximated by county and counties were later stratified by population density, with the most urban counties ranked higher than more rural counties.
For questions pertaining to satisfaction with telemedicine care, clinicians were asked to rate their agreement with the statements from totally disagree (−5) to totally agree (+5). Personality elements and preference-based questions were arranged on a sliding scale, with one element of comparison listed on the far left (−5), the other on the far right (+5), and a neutral response in the middle (0). Participants were asked to state where on the continuum they identified themselves. For the question pertaining to desired telemedicine platform features, eight features noted from the qualitative interviews were listed as well as an option for “other.” Participants were asked to rank these features from most important to least important (1–9).
A total of 241 participants responded. Twenty-one (8.7%) were excluded from analysis as they completed <50% of the survey. The final analysis included 220 subjects, with an average of 13 years of experience and 25% indicating a surgical specialty (Table 1).
n = 220 | |
---|---|
Years in practice, mean (SD) | 13 (9.4) |
Population density, mean county ranka (SD) | 3.3 (1.6) |
Patient population, n (%) | |
Pediatric | 55 (25) |
Adult | 125 (57) |
Both | 40 (18) |
Practice context, n (%) | |
Outpatient | 131 (60) |
Inpatient or both | 89 (40) |
Specialty, n (%) | |
Nonsurgical | 166 (75) |
Surgical | 54 (25) |
Prior telemedicine experience, n (%) | |
No | 193 (88) |
Yes | 27 (12) |
Duration of telemedicine visits, minutes (SD) | |
New patients | 27 (13) |
Follow-up | 18 (9.3) |
Platform features, mean rank (SD) | |
Ease of use (patients) | 1.3 (0.73) |
Ease of use (clinician) | 2.2 (1.0) |
Ability to have multiple people on the same call | 4.3 (1.6) |
Ability to screen share | 5.2 (1.6) |
Good customer service | 5.1 (1.6) |
Ability to message patient | 6.7 (1.3) |
Integration with calendar | 6.3 (1.7) |
Integration with EMR | 5.3 (2.1) |
Other | 8.6 (1.4) |
Platform experience, n (%) | |
Google hangouts | 195 (89) |
Zoom | 62 (28) |
Web-based platform | 56 (25) |
Other | 68 (31) |
Platform preference, n (%) | |
Google hangouts | 107 (49) |
Zoom | 31 (14) |
Web-based platform | 31 (14) |
Other | 51 (23) |
Statistical Analysis
Practice location information that was incomplete was treated as missing data. These missing values were replaced with the average of the other population density rank (mean imputation). Histograms and Shapiro–Wilk tests of normality showed non-normal distributions of the age, experience, preference, and satisfaction measures. Categorical variables are presented as frequencies with percentages, and all continuous variables were represented as means with standard deviations due to adequate sample size.
In bivariate analysis, we compared differences among clinicians who desire to continue using telemedicine after COVID-19 and those who did not, using Pearson’s chi-squared and Mann–Whitney tests. We also compared factors associated with satisfaction with the quality of telemedicine care using Mann–Whitney tests, Kruskal–Wallis tests, and Spearman’s rank correlation coefficient. Finally, we compared the characteristics of those with a preference for specific telemedicine platforms using Pearson’s chi-squared and Kruskal–Wallis tests.
Variables with a p-value of <0.01 on bivariate analysis were entered into multivariable logistic and linear regression models to assess the independent association of these explanatory variables with the desire to continue telemedicine after COVID-19, satisfaction with the quality of telemedicine care, and the preferred telemedicine platform (Tables 2–3). Results of the logistic regression are reported as odds ratios with standard error, 95% confidence interval (CI), and p-value. Results of the linear regression are reported as coefficients, 95% CI, standard error, p-value, semipartial R2, and R-squared values. Two-sided p-values <0.05 were considered significant.
ODDS RATIO | 95% CI | p | ||
---|---|---|---|---|
Telemedicine perceptionsa | ||||
Quality of care | 2.7 | 1.5 | 5.2 | 0.002 |
Quality of relationships | 0.74 | 0.47 | 1.2 | 0.19 |
Diagnosis from history | 0.84 | 0.52 | 1.3 | 0.46 |
Ease of physical examination | 2.1 | 1.0 | 4.5 | 0.045 |
Patient comfort | 0.90 | 0.56 | 1.5 | 0.68 |
Clinician preferencesb | ||||
Phone/video vs. in-person meeting | 0.56 | 0.34 | 0.93 | 0.024 |
Clinician beliefsa | ||||
Adaptability is important | 2.0 | 1.0 | 3.8 | 0.044 |
Physical touch is important | 0.56 | 0.28 | 1.1 | 0.10 |
COEFFICIENT | 95% CI | STANDARD ERROR | p | SEMIPARITAL R2 | ADJUSTED R2 | ||
---|---|---|---|---|---|---|---|
Population density, county ranka | −0.26 | −0.43 | −0.090 | 0.086 | 0.003 | 0.023 | 0.49 |
Duration of new patient visits, minutes | 0.021 | 0.000 | 0.042 | 0.011 | 0.05 | 0.010 | |
Preference for platform features, mean rankb | |||||||
Ease of patient use | −0.69 | −1.03 | −0.35 | 0.17 | <0.001 | 0.041 | |
Clinician preferencesc | |||||||
Phone/video vs. in-person meeting | −0.19 | −0.30 | −0.066 | 0.060 | 0.002 | 0.024 | |
Working at the office vs. home | 0.037 | −0.063 | 0.14 | 0.051 | 0.47 | 0.0013 | |
Clinician beliefsd | |||||||
Adaptability is important | 0.67 | 0.48 | 0.87 | 0.098 | <0.001 | 0.118 | |
Physical touch is important | −0.15 | −0.28 | −0.021 | 0.066 | 0.023 | 0.013 | |
Clinician personalityc | |||||||
Judging vs. perceiving | 0.13 | 0.022 | 0.23 | 0.053 | 0.017 | 0.015 |
Results
Only 12% of the physicians had previously used telemedicine in their practice; during COVID-19, 96% are using video visits to provide medical care. Among physicians now using telemedicine, 91% plan to continue to offer telemedicine services after the resolution of physical distancing and other adjustments to the pandemic.
Most clinicians ranked patient ease of use as the most important feature a platform can offer (mean rank 1.3 ± 0.73) and clinician ease of use followed closely behind (mean rank 2.2 ± 1.0) (Table 1).
Accounting for potential confounding using multivariable analysis, desire to continue offering telemedicine visits after the COVID-19 pandemic was associated with a higher satisfaction with the quality of telemedicine care, endorsement of the ease of performing a physical examination with telemedicine, belief that adaptability is an important element of being a clinician, and less preference for in-person work meetings over virtual meetings (Table 2).
Accounting for potential confounding using multivariable analysis, higher satisfaction with the quality of telemedicine care was associated with belief that adaptability is an important element of being a clinician, clinicians who identify as being more perceiving (value flexibility) than judging (value organization), providers from more urban counties, those who rank patient ease of use as a more important element of a telemedicine platform, and those with less preference for in-person work meetings over virtual meetings (Table 3).
Discussion
The early experience with telemedicine was promising,1–5,16 but uptake was slow until the COVID-19 pandemic. We studied factors associated with clinician desire to continue telemedicine services after the COVID-19 pandemic and factors associated with clinician satisfaction with the quality of care provided through telemedicine.
The findings of this study can be interpreted in light of some limitations. There are about 1,500 physicians in the multispecialty group, and some people started but did not complete the survey. We anticipated a low response rate as it is typical for survey studies. Although the group that responded may or may not be representative of the larger group or the average physician, we think the statistical associations with other factors and answers to other questions are likely reproducible in other settings and populations. The survey was administered within <2 months of drastic changes in medical practice due to the pandemic and opinions and preferences may continue to evolve.
Consistent with prior studies, the key factor desired in a platform was patient ease of use. Studies of hospital physicians in South Korea, India, Hong Kong, United States, and Spain found that overall satisfaction17 and perceived ease of use18–21 directly impacts both the perceived usefulness and the intention to use telemedicine.
The observation that desire to continue offering telemedicine visits after the COVID-19 pandemic correlates not only with confidence with the examination and satisfaction with the modality,22 but also with personal factors such as belief that adaptability is an important element of being a clinician, clinicians who identify as being more perceiving (value flexibility) than judging (value organization), and less preference for in-person work meetings over virtual meetings suggests that clinicians who are going to have less preference for telemedicine going forward can be identified by other traits and preferences. In the qualitative interviews along with our personal observations and interactions, including prior investigations,23,24 we found that both clinicians and patient concerns about telemedicine are things that lessen after a good telemedicine experience. The pandemic has provided many more clinicians and patients with good telemedicine experiences and the likelihood of continued use is high. Telemedicine will likely be a key part of the practice of clinicians who like to evolve and adapt and already value the conveniences that technology provides. However, there may be other personality factors and preferences associated with more enthusiastic adoption of telemedicine that we did not think to test.
The findings that higher satisfaction with the quality of telemedicine care was also associated with personal factors such as the belief that adaptability is an important element of being a clinician and clinicians who identify as being more perceiving (value flexibility) than judging (value organization) suggests that clinicians’ personality and beliefs can affect telemedicine utilization. The observation that higher satisfaction with the quality of telemedicine care was associated with urban location is compatible with a study in Norway that showed small hospitals are less likely to use telemedicine because it decreases the need for physical presence of clinicians, and might lead to difficulties with recruitment and retention of clinicians to rural sites.25 The American Medical Association Physician Benchmark Survey found that the financial burden of implementing telemedicine may be a barrier for small practices.26
Conclusions
Based on the results of this survey study and consistent with personal observations in our daily work, telemedicine is going to be advanced first by physicians who tend to be flexible, value technology-based practices, and who view adaptability as an important element of being a clinician. Additionally, we observed that clinicians who feel they can readily adapt the physical examination to video, and those that believe they can accomplish the goals of a meeting without being in the same room are more likely to be telemedicine proponents. People in your organization with these beliefs can more readily help bring telemedicine forward and help create institutional change. Future studies can develop the noted association of clinician personality aspects and their preferences and satisfaction with telemedicine utilization.
Disclosure Statement
None of the authors have any financial and personal relationships with other people or organizations that could inappropriately influence (bias) this study.
Funding Information
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
References
- 1. Cost-effectiveness of telemedicine in remote orthopedic consultations: Randomized controlled trial. J Med Internet Res 2019;21:e11330. Crossref, Medline, Google Scholar .
- 2. A cost-minimization analysis of orthopaedic consultations using videoconferencing in comparison with conventional consulting. J Telemed Telecare 2002;8:283–289. Crossref, Medline, Google Scholar .
- 3. Clinical effectiveness and cost analysis of patient referral by videoconferencing in orthopaedics. J Telemed Telecare 2001;7:219–225. Crossref, Medline, Google Scholar .
- 4. Quality of care for remote orthopaedic consultations using telemedicine: A randomised controlled trial. BMC Health Serv Res 2016;16:483. Crossref, Medline, Google Scholar .
- 5. Patient reported outcomes with remote orthopaedic consultations by telemedicine: A randomised controlled trial. J Telemed Telecare 2019;25:451–459. Crossref, Medline, Google Scholar .
- 6. Participant satisfaction and comfort with multidisciplinary pediatric telemedicine consultations. J Pediatr Surg 1999;34:137–142. Crossref, Medline, Google Scholar .
- 7. Comparison of parent satisfaction with care for childhood obesity delivered face-to-face and by telemedicine. Telemed J E Health 2011;17:383–387. Link, Google Scholar .
- 8. User satisfaction with asynchronous telemedicine: A study of users of Santa Catarina’s system of telemedicine and telehealth. Telemed J E Health 2012;18:339–346. Link, Google Scholar .
- 9. Patient satisfaction with physician–patient communication during telemedicine. Telemed J E Health 2009;15:830–839. Link, Google Scholar .
- 10. Application of the concerns-based adoption model to the installation of telemedicine in a rural Missouri nursing home. J Nurses Prof Dev 2004;20:42–49. Crossref, Medline, Google Scholar .
- 11. Legal and ethical issues in telemedicine and robotics. Int J Gynecol Obstet 2006;94:73–78. Crossref, Medline, Google Scholar .
- 12. Psychosocial factors are associated with electronic portal registration. Clin Orthop Relat Res 2020: [Epub ahead of print]; DOI: 10.1097/CORR.0000000000001278. Crossref, Medline, Google Scholar
- 13. Neurosurgery and telemedicine in the United States: Assessment of the risks and opportunities. World Neurosurg 2016;89:133–138. Crossref, Medline, Google Scholar .
- 14. Consent and privacy in telemedicine. Hawaii Med J 1993;52:340–341. Medline, Google Scholar .
- 15. Current legal and ethical concerns in telemedicine and e-medicine. J Telemed Telecare 2003;9(1_suppl):67–69. Crossref, Google Scholar
- 16. Patient perceptions and current trends in internet use by orthopedic outpatients. HSS J 2017;13:271–275. Crossref, Medline, Google Scholar
- 17. Acceptance of telemedicine among healthcare professionals. Arch Bronconeumol Engl Ed 2015;51:611–612. Crossref, Medline, Google Scholar .
- 18. Physician’s attitude towards acceptance of telemedicine technology for delivering health care services. Int J Mech Eng Technol 2018;09:715–722. Google Scholar
- 19. Examining the technology acceptance model using physician acceptance of telemedicine technology. J Manag Inf Syst 1999;16:91–112. Crossref, Google Scholar .
- 20. Determinants of intensive care unit telemedicine effectiveness. An ethnographic study. Am J Respir Crit Care Med 2019;199:970–979. Crossref, Medline, Google Scholar
- 21. Predictive factors of telemedicine service acceptance and behavioral intention of physicians. Int J Med Inf 2014;83:559–571. Crossref, Medline, Google Scholar .
- 22. Predictive factors of physicians’ satisfaction with telemedicine services acceptance. Health Informatics J 2020;26:1866–1880. Crossref, Medline, Google Scholar .
- 23. Clinicians’ perspectives of a novel home-based multidisciplinary telehealth service for patients with chronic spinal pain. Int J Telerehabilitation 2018;10:81–88. Crossref, Medline, Google Scholar .
- 24. Patient perceptions of telehealth primary care video visits. Ann Fam Med 2017;15:225–229. Crossref, Medline, Google Scholar .
- 25. Exploring factors associated with the uneven utilization of telemedicine in Norway: A mixed methods study. BMC Med Inform Decis Mak 2017;17:180. Crossref, Medline, Google Scholar .
- 26. The use of telemedicine by physicians: Still the exception rather than the rule. Health Aff (Millwood) 2018;37:1923–1930. Crossref, Medline, Google Scholar .