The coronavirus 2019 pandemic (COVID-19) has resulted in major changes in lifestyle practices and healthcare delivery. The goal of this study was to examine changes in practice and service outcomes in a telehealth program before and after the federal and private telehealth policy expansion during the COVID-19 pandemic. These findings are particularly useful to understand what may be needed to overcome telehealth challenges in future disasters.
We conducted a cross-sectional analysis of virtual visits through a statewide telehealth center embedded in a large academic healthcare system. Primary outcomes of this study were changes in telehealth visits pre- and post-policy expansions among at-risk populations.
A total of 2,132 telehealth visits were conducted: 1,530 (71.8 percent) patients were female, 1,561 (73.2 percent) were between the ages 18-50, 1,576 (74 percent) were uninsured, and 1,225 (57.5 percent) were from rural regions. The average number of telehealth visits per day increased from 14 to 33 visits post-expansion. A significant change in patient characteristics was found among senior, uninsured, and rural patients after the telehealth expansion.
There was an 11 percent decrease in telehealth visits from very high vulnerability regions post-expansion compared to pre-expansion. There was a 15 percent decrease in visits resulting in prescription post-expansion (p-value<0.01).
COVID-19 policy expansions expanded telehealth utilization among at-risk populations such as senior, uninsured, and rural patients while decompressing hospitals and emergency rooms and maintaining positive patient experiences. Further regulations are needed around virtual visits unintended consequences, software certification, and guidelines for workforce training.
Keywords: Telehealth, Population, Changes, Outcomes, COVID-19
The coronavirus 2019 pandemic (COVID-19) introduced major changes in lifestyle practices, and healthcare delivery aimed to minimize the movement and interaction of individuals.1,2 To “flatten the curve” of COVID-19 cases during the initial phases of the pandemic, the Centers for Disease Control and Prevention (CDC) promoted social distancing through community-based interventions such as working remotely, school dismissals, and the cancellation of large-gatherings.3 As a result, in March 2020, major North Carolina healthcare systems reduced operations at outpatient clinics by cancelling non-emergent surgical procedures.4 These changes disrupted the usual ways in which patients seek care.
Studies reported a substantial increase in new telehealth programs post-pandemic.5-9 Our early COVID-19 investigation showed that confirmed COVID-19 case counts were significantly higher in areas with high population density and areas with a major airport.10 Additionally, patients’ gender and geographic location are strong predictors to the choice of telehealth communication medium.11,12 However, there is lack of knowledge regarding existing telehealth programs and the changes introduced to existing telehealth programs in North Carolina because of the telehealth waivers and the shutdown of healthcare systems.
On March 6, 2020, the US government announced two important regulatory changes related to telehealth to combat COVID-19.13 First, the Department of Health and Human Services (HHS) and the Centers for Medicare & Medicaid Services (CMS) waived telehealth reimbursement restrictions and privacy protections, allowing coverage for telephone and video encounters on consumer platforms.14 Second, licensed providers are now permitted to prescribe controlled substances to patients they have not met before, an option that limited the spread of telehealth in the past. Private payers have also waived telehealth restrictions to further encourage individuals to use telehealth.15
Telehealth and the digital divide led major concerns on widening the health disparity gap.16,17 The coverage of audio-only telephone visits by CMS and private insurers18,19 is particularly important to vulnerable populations such as seniors and rural patients who may not have internet accessibility and can only rely on their phone to seek care. Historically, studies have reported that telemedicine visits yield higher fill rates of prescription when compared to in-person visits.20,21 It is unclear if there were changes in telehealth use and prescription rates post-CMS telehealth expansion compared to pre-expansion.
The Centers for Disease Control and Prevention (CDC) established a Social Vulnerability Index (SVI) to measure the vulnerability of communities across the US.22 Therefore, comparing the changes observed in telehealth use post-CMS policy expansions to baseline (i.e., pre-telehealth expansions) can provide new insights to policymakers that can help bridge current health disparities.
Emerging viewpoint articles have provided preliminary insights on the importance of telehealth as a new healthcare modality.23-25 However, to our knowledge, no studies have evaluated the impact of these telehealth policy changes on an existing virtual care practice in North Carolina. In this study, we characterized telehealth practice change in one large healthcare system before and after the CMS telehealth expansion, which was instated on March 6, 2020.
The goal of this study was to examine practice changes measured as utilization, patient characteristics, and service outcomes in a telehealth practice before and after the federal and private telehealth policy expansion on March 6, 2020, during the COVID-19 pandemic. These findings are particularly useful to policymakers and organizations to understand what may be needed to overcome telehealth challenges in future disasters.
Materials and Methods
We conducted a cross-sectional analysis of telehealth visits at a major telehealth center embedded in a large academic healthcare system that comprises 11 hospitals and 350 outpatient clinics in the Southeast. During the initial phase of COVID-19 (March through April 2020), in-person visits at the medical center were canceled except for emergency conditions.26 Consequently, patients with existing in-person visit appointments during March through April were asked to choose between an alternative telehealth visit or to wait for an in-person visit later. Starting the end of April, the healthcare system gradually resumed in-person visits. The study period in which we collected telehealth data was between January 21 and April 19, 2020. We concluded the study in April, which is before the resumption of in-person visits, to reduce the effect of confounding factors when healthcare systems reopened and some telehealth policies began to change. In this study, we defined at risk populations as patients who are over 65 years, uninsured, or living in a rural region.
The telehealth center was launched in 2018 as a virtual urgent care center offering 24/7 on-demand access to physicians via video or telephone, thereby providing expanded access to rural and underserved populations as we reported previously.27 All providers at the center were externally contracted board-certified physicians, not internally employed by the health system and generally not the patient’s primary care physician. Virtual care providers were licensed to treat or consult on a wide range of medical conditions including fevers, respiratory infections, and rashes. Encounters for behavioral health conditions were not eligible for virtual visits.
Providers were able to send a prescription to the patient’s pharmacy of choice, if clinically indicated, but no laboratory or imaging tests can be ordered. Virtual providers could provide a copy of the encounter documentation and visit notes to the institution’s electronic health record, which were visible to the patient and the primary care physician. Patients were charged a fixed fee of $49 USD for the virtual encounter and have the option to submit this charge to their insurance company for reimbursement.
We collected de-identified patient- and visit-level data for all telehealth visits at the virtual care center from January 21, 2020, the date of the first COVID-19 case in the US, through April 19, 2020. All data were extracted electronically from the telehealth system. We compared visit trends before and after the federal telehealth expansion on March 6, 2020. Several major private insurers waived telehealth restrictions on the same day or closely after the federal expansions.28,29 In this study, we defined pre-telehealth expansion to be between January 21 and March 5, 2020; and post-telehealth to be between March 6 and April 19, 2020.
Patient-level data were self-reported and included demographics, insurance status, and chief complaint. We categorized patients’ location as rural or urban using the US Census population estimates of rural classification (less than 50,000 people) and urban classification (more than 50,000 people).30
Visit-level data included total time, wait time, visit duration, visit diagnosis, visit modality (telephone vs. video), and whether the visit resulted in a prescription medication sent to a pharmacy (yes/no). Total time was measured as the combination of patient wait time and visit duration. Wait time was defined as the timespan from when a telehealth visit is requested by the patient until the start time of the visit. The visit duration was defined as the time from start to end of the visit.
Primary outcomes of this study were patient characteristics (measured by subgroup analysis of sex, age, insurance coverage, and location) and practice change (measured by the volume of visits, wait times, visit duration, communication medium, and prescription rates).
We performed descriptive analysis including subgroup analysis for all telehealth visits during the study period as well as pre/post analysis to evaluate visit trends before and after the federal telehealth expansion (pre-expansion cohort: 44 days, January 21 through March 5; post-expansion cohort: 44 days, March 6 through April 19). We calculated relative changes for the pre/post analysis and performed chi-square testing for statistical significance where appropriate. All data were extracted and analyzed in Microsoft Excel and R statistical programming software.
To understand the telehealth use of patients based on their location, we used ArcGIS® to map ZIP code-level populations as reported in the 2010 US Census Bureau data with telehealth visits by ZIP Code Tabulation Areas (ZCTA). We used the 2018 CDC SVI to assess the patient’s neighborhood vulnerability by ZCTA. The CDC SVI score ranges from 0 (lowest vulnerability) to 1 (highest vulnerability). We then mapped the CDC SVI data and visit counts from the telehealth program on the North Carolina map to better understand the change in patients’ neighborhood vulnerability pre- and post-expansions. We excluded 58 pre-expansion visits and 51 post-expansion visits from our geospatial analysis because these visits were from out of state addresses.
A total of 2,132 patients visited the telehealth center during the study period, with an average of 21 visits per day. Among all visits, 1,530 (71.8 percent) patients were female, 1,561 (73.2 percent) were between the ages 18-50, 1,576 (74 percent) were uninsured, and 1,225 (57.5 percent) were from rural regions (Table 1). A total of 1,453 (68 percent) visits occurred in the 44 days following the federal telehealth expansion.
Pre-expansion, the average number of telehealth encounters was 14.4 visits per day; after expansion, the number increased to 33 visits per day, a 229 percent increase (Table 1). The change in demand, as measured by proportion of virtual visits, represented heterogeneity across different subpopulations: demand significantly increased 5.6 percent among males (p-value=0.002) and 6.2 percent among young adults (age 18-34) (p-value<0.001) but significantly decreased by 4.9 percent among females and 5.8 percent among pediatric patients (age < 17).
Uninsured patients accounted for a greater proportion of virtual visits after the federal telehealth expansion (1163/1453; 80 percent) as compared to before (414/679; 61 percent), a statistically significant increase (p < 0.001).
Patients living in rural areas accounted for the larger proportion of virtual patients before (415/679; 61.1 percent) and after (810/1453; 55.8 percent) the telehealth expansion. Nevertheless, the portion of patients residing in urban areas increased following the telehealth expansion (643/1453; 44.3 percent) as compared to before (264/679; 38.9 percent), a statistically significant increase (p=0.001).
Telehealth utilization increased substantially post-telehealth expansion, as expected. Pre-telehealth expansion, patients represented 190 (17 percent) unique ZIP codes compared to 265 (24 percent) unique ZIP codes. Figure 1A shows the difference in telehealth visits pre and post telehealth policy expansions. The increase in telehealth visits post-expansion occurred in major North Carolina cities such as Raleigh-Durham, Charlotte, Asheville, and Wilmington (shown in red and orange). While a decrease in telehealth visits post-expansion occurred in scattered rural North Carolina regions (shown in blue and green). Figure 1B mapped the CDC SVI score to the North Carolina map such that the different shades of red indicated North Carolina areas of high vulnerability, and yellow and orange colors represented low vulnerability regions.
Post-telehealth expansion, the volume of telehealth visits originating from regions with very high vulnerability decreased 11 percent (29 percent to 17 percent) to pre-telehealth expansion (Table 2). In North Carolina, 247 (31 percent) ZIP codes are categorized as high vulnerability followed by 234 (29 percent) categorized as very high vulnerability. Pre-expansion, 236 (38 percent) telehealth visits originated from low vulnerability areas compared to 633 (45 percent) after the expansion.
The average total time (SD) (including wait time and visit duration) for a virtual visit increased from 21.7 (16.8) pre-expansion to 75.5 (129.8) minutes post-expansion. In response, we increased the number of providers from 14 pre-expansion to 32 post-expansion. The number of providers and the average virtual visit total time peaked following the telehealth policy expansion, but total time subsequently decreased to 13 minutes, while the number of providers leveled off around 32 providers per day (Figure 2).
Pre-telehealth expansion, the average wait time (SD) was 15.4 (6.9) minutes and the average visit duration was 6.3 (0.9) minutes. Post-telehealth expansion, the average (SD) wait time was 67.2 (128.7) minutes and the average visit duration was 7.6 (5) minutes (Figure 3). Peak wait times following the telehealth expansion reached 349 minutes.
Post-telehealth expansion, the proportion of patients choosing a telephone visit decreased (581/679, 85.6 percent vs. 1,148/1,453, 79 percent) while the proportion of patients requesting video visits increased (98/679, 14.4 percent vs. 305/1453, 21 percent) following the federal telehealth expansion, a statistically significant change (p<0.01) (Table 1).
Following the policy change, a smaller proportion of virtual visits resulted in a prescription medication (962/1,453, 66.2 percent) as compared to before the telehealth expansion (531/679, 82 percent) (Table 1). This difference reached statistical significance (p<0.01).
The distribution of visit diagnoses was similar for virtual visits occurring before and after the federal telehealth expansion. In both cases, the most common diagnoses included: flu, sinusitis, bronchitis, and urinary tract infection. Pre-expansion, three of the top diagnosis (flu, bronchitis, cough) can be labeled as possible COVID-19 cases that may require testing, while post-expansion, there were four of the top five diagnosis (flu, upper respiratory infection, bronchitis, cough) with possible COVID-19 cases.
In this cross-sectional study, we evaluated telehealth visits at a major virtual care center during the COVID-19 crisis and observed a significant 225 percent increase in the demand for virtual visits such that the daily volume of virtual visits spiked by 157 percent on March 9, 2020, only three days after the policy expansion bill was passed, as would be expected. This was associated with an increase in wait times of two or more hours from a baseline of ~15 minutes, although visit duration remained essentially the same. The increase in demand and wait times suggest the need for rapid increase in human capacity to deliver telehealth during the initial response to a disaster, which the policy for expanding telehealth coverage could support over time.
We found significant rise in uninsured patients after the policy expansions, which was unexpected. Although we do not have a definitive explanation for this phenomenon, a possible explanation may be that uninsured patients resided in regions with limited access to healthcare and the availability of telehealth during the pandemic allowed them to proactively seek care. Another possibility is that some of the patients in the uninsured category were previous telehealth users who lost their jobs due to economic conditions resulting from the pandemic and lost insurance coverage as a result.31 Similarly, the decrease in telehealth visits from patients living in highly vulnerable regions is unknown. A possible explanation could be that patients in those highly vulnerable populations chose to use a different telehealth program given the availability of new programs during that time period.
The number of virtual visits with patients over 65 years of age tripled post the policy expansions. Similarly, more males and young adults steered toward virtual care for their health needs. This increase in usage from patients over 65 years was expected given heightened concerns about risk of worse outcomes from COVID-19. Regarding young adults, it is possible that comfort with technology was a driver of increased virtual visits. However, it is not immediately clear why the proportion of male patients increased given that female patients have been reportedly the dominant users of telehealth.32
This study shows that despite the surge in virtual visits at our center following the federal telehealth expansion, a substantial smaller proportion of virtual visits resulted in a medication being prescribed. This is encouraging because it suggests that reassurance can be an important component of care delivered virtually and that telemedicine does not necessarily lead to “overmedication” as compared to traditional in-person care. However, not receiving medication as expected by the patient was a reason provided by some patients for their negative ratings of virtual care visits, indicating there may be some patients who need additional reassurance.
As the number of virtual visits increased by 229 percent and wait times reaching 350 minutes, we had to substantially double the number of tele-doctors by a factor of two to meet the increasing demand from patients. This expansion in workforce showed effectiveness when the wait times reduced to average levels pre-telehealth expansion and patient rating improved. The nature of on-demand telehealth services creates a challenge to determine the suitable staffing to meet patient needs. Particularly, the widespread of COVID-19 coupled with the telehealth policy expansion introduced an unprecedented upsurge in patient demand for telehealth. The ability to predict staffing needs is valuable; however, our experience with substantial fluctuation in staffing presents a new telehealth challenge to match between staffing capacity and patient needs.
Training advanced practice providers (APP) and physician assistants (PA) as potential telehealth workforce is one strategy to meet the growing demand.33 Another suggestion is to train current medical and nursing students to serve as scribes during the telehealth visit to assist with documentation and/or triage. The use of medical scribes can cut physician EHR time and boost productivity and satisfaction; therefore, expanding the use of medical scribes to telehealth use possibly will have similar effect.34
Following the federal telehealth expansion on March 6, our data demonstrated a substantial increase in the uptake of virtual care visits among urban patients and among the number of virtual visits occurring by video. We found that telehealth visits from more vulnerable regions substantially decreased post the expansion. A possible explanation for the significant increase in patients from urban areas, who may have easier access to in-person care facilities, could be shelter-in-place orders, increased public awareness regarding group gatherings, and greater concerns about COVID-19 risk among those living in areas with higher population density. The increase in urban patients also may be linked to availability of broadband internet speed to support video calls. These findings suggest that telehealth policy expansions may worsen health disparities and further widen the digital divide within our communities.
This study had several limitations. This study was conducted at a single, online telehealth center at a large academic health system. It is important to recognize that the increase in virtual care visit volume may not be fully attributable to the policy changes, as more patients might have opted for virtual visits regardless of the policy change due to the shutdown of in-person visits. However, the timing of the policy change and the immediate increased demand clearly coincide, and the expanded coverage is promising for handling the capacity demands required with the increased demand. One confounding factor to the study design is the cancellation of in-person visits, which limited our ability to compare virtual vs. in-person visits. A confounding factor to our findings may be the digital bias of telehealth patients, which may not be generalizable to individuals with limited digital knowledge or equipment. Although we used the COVID-19 symptoms defined by WHO in our predictive model, those symptoms are non-specific and overlap with those of flu; therefore, the model may identify some cases as COVID-19 that instead should be classified as a different illness. Also, due to lack of data, the non-linear behavior of number of COVID-19 infections over time was not taken into account in our predictive model, which may simplify the problem.
Building virtual care capacity remains a work in progress in order to bridge patient expectations with virtual care capabilities.6 More efforts are needed to adapt and implement virtual care best-practices.35 The success of virtual care heavily relies on well-trained workforce, ergonomically designed physical space, reliable IT infrastructure, and high-speed internet. Lessons learned from the electronic health records adoption era may be valuable to inform virtual care best practices and policymaking.
The policy expansion presented an opportunity for provide care to a broader audience, especially among at-risk populations. We envision that the widespread adoption of telehealth will require additional regulatory measures additional to the established licensure, credentialing, and data privacy and security policies. Currently, there are no health IT certifications for telehealth platforms unlike electronic health record systems that undergo rigorous certification process through the Office of the National Coordinator.36 Additionally, due to the sudden shift to telehealth, there is a lack in education and training on telehealth best practices, a key element to high-quality care. Some providers are self-learning how to care for patients in a virtual space; however, we believe that formal specialty-based telehealth training guidelines are essential for providers with no or limited telehealth experience. Finally, we envision that policymakers will need to further regulate unintended consequences of virtual visits.
All authors confirm the content of this manuscript and have all contributed to the work presented in this manuscript.
Conflict of Interest: The authors declare no conflicts of interest.
Funding sources: None.
1. WHO. WHO Director-General’s opening remarks at the media briefing on COVID-19 - 11 March 2020. Accessed March 12, 2020, https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020
2. Grennan D. What Is a Pandemic? JAMA. 2019;321(9):910-910. doi:10.1001/jama.2019.0700
3. CDC. Preventing COVID-19 Spread in Communities. Accessed March 12, 2020, https://www.cdc.gov/coronavirus/2019-ncov/community/index.html
4. Kelly A. “UNC Hospitals develops COVID-19 testing kits, responds to pandemic.” The Daily Tar Heel; 2020. 3/19/2020. Accessed 9/22/2020. https://www.dailytarheel.com/article/2020/03/covid-testing-0320
5. Hamad J, Fox A, Kammire MS, Hollis AN, Khairat S. “Evaluating the Experiences of New and Existing Teledermatology Patients During the COVID-19 Pandemic: Cross-sectional Survey Study.” JMIR Dermatol. Jan-Jun 2021;4(1):e25999. doi:10.2196/25999
6. Khairat S, Pillai M, Edson B, Gianforcaro R. “Evaluating the Telehealth Experience of Patients With COVID-19 Symptoms: Recommendations on Best Practices” Journal of Patient Experience. 2020:2374373520952975. doi:10.1177/2374373520952975
7. Schifeling CH, Shanbhag P, Johnson A, et al. “Disparities in Video and Telephone Visits Among Older Adults During the COVID-19 Pandemic: Cross-Sectional Analysis.” JMIR Aging. Nov 10 2020;3(2):e23176. doi:10.2196/23176
8. Smith WR, Atala AJ, Terlecki RP, Kelly EE, Matthews CA. “Implementation Guide for Rapid Integration of an Outpatient Telemedicine Program During the COVID-19 Pandemic.” Journal of the American College of Surgeons. 2020/04/30/ 2020;doi:https://doi.org/10.1016/j.jamcollsurg.2020.04.030
9. Griggs GK. “Innovations in Virtual Care During the Pandemic: Implications for the Future.” North Carolina Medical Journal. 2021;82(4):252. doi:10.18043/ncm.82.4.252
10. Khairat S, Meng C, Xu Y, Edson B, Gianforcaro R. “Interpreting COVID-19 and Virtual Care Trends: Cohort Study.” Original Paper. JMIR Public Health Surveill. 2020;6(2):e18811. doi:10.2196/18811
11. Schifeling CH, et al., 2020.
12. Khairat S, Liu S, Zaman T, Edson B, Gianforcaro R. “Factors Determining Patients’ Choice Between Mobile Health and Telemedicine: Predictive Analytics Assessment.” Original Paper. JMIR Mhealth Uhealth. 2019;7(6):e13772. doi:10.2196/13772
13. CMS. Additional Background: Sweeping Regulatory Changes to Help U.S. Healthcare System Address COVID-19 Patient Surge. Accessed April 20, 2020, https://www.cms.gov/newsroom/fact-sheets/additional-backgroundsweeping-regulatory-changes-help-us-healthcare-system-address-covid-19-patient
14. Representatives Ho. Making emergency supplemental appropriations for the fiscal year ending September 30, 2020, and for other purposes. Accessed March 12, 2020, https://docs.house.gov/billsthisweek/20200302/BILLS-116hr6074-SUS.pdf
15. BCBS. COVID-19 Resources for our Members. Accessed April 6, 2020, https://blog.bcbsnc.com/2020/02/what-you-need-to-know-about-coronavirus/
16. Schifeling CH, et al., 2020.
17. Khairat S, Haithcoat T, Liu S, et al. “Advancing health equity and access using telemedicine: a geospatial assessment.” J Am Med Inform Assoc. Jul 24 2019;doi:10.1093/jamia/ocz108
18. CMS. Additional Background: Sweeping Regulatory Changes to Help U.S. Healthcare System Address COVID-19 Patient Surge. Accessed April 20, 2020, https://www.cms.gov/newsroom/fact-sheets/additional-backgroundsweeping-regulatory-changes-help-us-healthcare-system-address-covid-19-patient
19. AHIP. Health Insurance Providers Respond to Coronavirus (COVID-19). Accessed April 20, 2020, https://www.ahip.org/health-insurance-providers-respond-to-coronavirus-covid-19/
20. Ray KN, Shi Z, Gidengil CA, Poon SJ, Uscher-Pines L, Mehrotra A. “Antibiotic Prescribing During Pediatric Direct-to-Consumer Telemedicine Visits.” Pediatrics. 2019;143(5):e20182491. doi:10.1542/peds.2018-2491
21. Foster CB, Martinez KA, Sabella C, Weaver GP, Rothberg MB. “Patient Satisfaction and Antibiotic Prescribing for Respiratory Infections by Telemedicine.” Pediatrics. 2019;144(3):e20190844. doi:10.1542/peds.2019-0844
22. Control CfD, Prevention. CDC SVI Documentation 2018. Accessed June 2, 2021, https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI_documentation_2018.html
23. Mehrotra A, Ray K, Brockmeyer DM, Barnett ML, Bender JA. “Rapidly Converting to ‘Virtual Practices’: Outpatient Care in the Era of Covid-19.” Catalyst non-issue content. 2020;1(2)doi:doi:10.1056/CAT.20.0091
24. Reeves JJ, Hollandsworth HM, Torriani FJ, et al. “Rapid Response to COVID-19: Health Informatics Support for Outbreak Management in an Academic Health System.” Journal of the American Medical Informatics Association. 2020;doi:10.1093/jamia/ocaa037
25. Hollander JE, Carr BG. “Virtually Perfect? Telemedicine for Covid-19.” New England Journal of Medicine. 2020;doi:10.1056/NEJMp2003539
26. Kelly A, 2020.
27. Khairat S, Haithcoat T, Liu S, et al., 2019.
28. BCBS. Blue Cross and Blue Shield Companies Announce Coverage of Coronavirus
Testing for Members and Other Steps to Expand Access to Coronavirus Care. Accessed April 21, 2020, https://www.bcbs.com/press-releases/blue-cross-and-blue-shield-companies-announce-coverage-of-coronavirus-testing
29. NTPRC. Telehealth coverage policies in the time of covid-19 to date. Accessed April 21, 2020, https://www.cchpca.org/sites/default/files/2020-03/CORONAVIRUS%20TELEHEALTH%20POLICY%20FACT%20SHEET%20MAR%2017%202020%203%20PM.pdf
30. Ratcliffe M, Burd C, Holder K, Fields A. Defining Rural at the U.S. Census Bureau. 2016.
31. Holmes M. “Running the Numbers: Estimated Changes in Health Insurance Coverage of North Carolinians in the First Six Months of the COVID-19 Pandemic.” North Carolina Medical Journal. 2020;81(6):400. doi:10.18043/ncm.81.6.400
32. Khairat S, Liu S, Zaman T, Edson B, Gianforcaro R, 2019.
33. Balestra M. “Telehealth and Legal Implications for Nurse Practitioners.” The Journal for Nurse Practitioners. 2018;14(1):33-39. doi:10.1016/j.nurpra.2017.10.003
34. Bates DW, Landman AB. “Use of medical scribes to reduce documentation burden: Are they where we need to go with clinical documentation?” JAMA Internal Medicine. 2018;178(11):1472-1473. doi:10.1001/jamainternmed.2018.3945
35. Krupinski EA, Bernard J. “Standards and Guidelines in Telemedicine and Telehealth.” Healthcare (Basel, Switzerland). 2014;2(1):74-93. doi:10.3390/healthcare2010074
36. ONC. About The ONC Health IT Certification Program. Accessed April 21, 2020, https://www.healthit.gov/topic/certification-ehrs/about-onc-health-it-certification-program
Saif Khairat (firstname.lastname@example.org) is an associate professor for the Carolina Health Informatics Program in the Cecil G. Sheps Center for Health Services Research at the University of North Carolina at Chapel Hill.
Yuxiao Yao (email@example.com) is affiliated with the Graduate of School of Information and Library Science ath the University of North Carolina at Chapel Hill.
Cameron Coleman (firstname.lastname@example.org) is affiliated with the University of Michigan.
Philip McDaniel (email@example.com) is a GIS librarian at the Health Services Library at the University of North Carolina at Chapel Hill.
Barbara Edson (firstname.lastname@example.org) is the executive director of the Virtual Care Center at UNC Health.
Christopher M. Shea (email@example.com) is an associate professor in the Gilling’s School of Public Health at the University of North Carolina at Chapel Hill.