A patient education intervention improved rates of successful video visits during rapid implementation of telehealth

Abstract

Introduction

The need to rapidly implement telehealth at large scale during the COVID-19 pandemic led to many patients using telehealth for the first time. We assessed the effect of structured pre-visit preparatory telephone calls on success of telehealth visits and examined risk factors for unsuccessful visits.

Methods

A retrospective cohort study was carried out of 45,803 adult patients scheduled for a total of 64,447 telehealth appointments between March and July 2020 at an academic medical center. A subset of patients received a structured pre-visit phone call. Demographic factors and inclusion of a pre-visit call were analysed by logistic regression. Primary outcomes were non-completion of any visit and completion of phone-only versus audio-visual telehealth visits.

Results

A pre-visit telephone call to a subset of patients significantly increased the likelihood of a successful telehealth visit (OR 0.54; 95% CI: 0.48–0.60). Patients aged 18–30 years, those with non-commercial insurance or those of Black race were more likely to have incomplete visits. Compared to age 18–30, increasing age increased likelihood of a failed video visit: 31–50 years (OR 1.31; 95% CI: 1.13–1.51), 51–70 years (OR 2.98; 2.60–3.42) and >70 years (OR 4.16; 3.58–4.82). Those with non-commercial insurance and those of Black race (OR 1.8; 95% CI 1.67–1.92) were more likely to have a failed video visit.

Discussion

A structured pre-call to patients improved the likelihood of a successful video visit during widespread adoption of telehealth. Structured pre-calls to patients may be an important tool to help reduce gaps in utilization among groups.

Keywords

Telehealth implementation telemedicine patient education

Introduction

The COVID-19 pandemic spurred a rapid shift from traditional in-person outpatient visits to telehealth appointments to promote social distancing and reduce exposure to vulnerable patients.^1,2 In this analysis, ‘telehealth’ refers to synchronous audio-visual visits.

Benefits of telehealth have long been recognized, including the ability to overcome barriers to care including lack of transportation and financial constraints, general cost-savings, improved health outcomes, enhanced social support for patients, reduced patient travel times and wait times, and ability to provide virtual care during natural disasters and public health emergencies.^3,4 Telehealth has been effective for managing chronic diseases including chronic pulmonary diseases, diabetes, hypertension, digestive diseases, and mental health in both primary care and specialty settings.⁵

However, little is known about the effect of a system-wide shift toward telehealth. Recently, Eberly et al. found that patients with older age, Asian race and primary language other than English were less likely to complete a phone or video encounter during the pandemic. Additionally, older patients and those of Black race or Latinx ethnicity were less likely to complete a video visit. Similarly, Chunara et al. found that Black patients had 0.6 times the odds of using telehealth versus white patients during the pandemic.⁶ This raises important equity concerns, particularly among older patients, racial/ethnic minority groups and those of lower socioeconomic status.⁷

Studies have found associations of access to digital technologies and electronic medical records (EMR) with age, race, ethnicity and socioeconomic status. These associations may further apply to access to telehealth services.^8–10 Yet little is known about how to educate patients new to telehealth in order to support access. It is therefore important to understand how patients were able to successfully access care in a rapid large-scale implementation of telehealth and evaluate interventions to support patient access. In this study, we analysed all scheduled telehealth visits within internal medicine clinics (adult primary care and specialty services) at a large academic medical center to determine factors associated with successful telehealth visits. Further, we evaluated the effect of an intervention using structured pre-visit telephone calls to patients on the likelihood of telehealth visit success.

Methods

This is a single center, retrospective cohort study of Department of Medicine outpatient clinics across Vanderbilt University Medical Center. This included all adult primary care and subspecialty internal medicine clinics. At the start of the COVID-19 pandemic, from 16 March to 1 July 2020, outpatient Vanderbilt clinics transitioned to a hybrid telehealth and clinic model per state stay-at-home orders and corresponding institutional recommendations. Providers and patients were encouraged to use telehealth as much as possible for clinical encounters during this time. Per recommendations of our medical center, all telehealth visits were initially attempted via video rather than phone-only. Patient access to the telehealth visit required downloading a patient portal application and then linking to the video-conferencing application (Zoom) through the portal. Detailed instructions were given during the scheduling process, but how they were delivered varied throughout the various medical clinics. The medical center developed educational materials including a website for patients detailing how to do a telehealth video visit. Only visits with a medical provider in the Department of Medicine were included in this analysis. Visits occurring in other departments, such as surgery, paediatrics and behavioural health, and ancillary staff telehealth encounters were excluded.

A medical student initiative to support patients during the transition to telehealth was developed. Students were educated via a 1-hour peer educational programme on the details of telehealth access from the patient’s point of view. At our institution, patients use the patient portal to access the video visit on Zoom. Students developed and distributed additional materials such as troubleshooting guides. Students contacted patients who were scheduled for a telehealth visit 1–5 days prior to the visit for clinics interested in support. The goal was to call as many patients as possible; there was no specific selection of patients. The calls included a standardized script that the student went through with patients. Topics included: (1) explaining telehealth visits; (2) best practices for telehealth including gathering medications and home vital signs if possible; (3) guidance on the technical steps to complete a visit, including downloading apps for both the portal and Zoom, and how to start the visit through the portal with emphasis on common points of confusion; (4) performance of a test visit if desired; and (5) answers to any remaining patient telehealth-related questions (Figure 1 and supplemental file).

Figure 1.

Process of dedicated structured pre-calls to prepare patients for telehealth visits.

Demographic data were obtained including patient age, sex, race and insurance status at the time of visit. Billing codes were used to assess whether a telehealth visit was an attempted but failed visit (no billing code), a video-conferencing telehealth visit or audio/phone-only visit. Multivariable logistic regression models were conducted to evaluate the likelihood of a failed (not completed) visit and a planned video telehealth visit converted to a phone-only visit adjusting for patient age, sex, race and insurance status and examining interaction of sex, race and insurance status. Statistical analysis was completed using Stata version 16.1. This study was approved by the Vanderbilt University Medical Center Institutional Review Board (IRB). All authors had access to the study data and reviewed and approved the final manuscript. There was no specific funding for this work.

Results

In internal medicine clinics between March and July 2020, a total of 64,447 telehealth visits were scheduled for 45,803 unique patients (Table 1). In total, 27,684 (61%) of the patients were female. The median age was 56 (range 18 to greater than 90 years).

Table 1.

Demographic characteristics of patients with successfully completed telehealth visits (total n = 64,447 visits).

Demographics	Visits
Female, n (%)	39,365 (61)
Age, years (range)	56 (18–90+)
Insurance, n (%)
Commercial	38,429 (60)
Medicare	23,219 (35)
Medicaid	1851 (3)
Other	948 (2)
Race, n (%)
White	50,973 (79)
Black	7631 (12)
Hispanic	830 (1)
Asian	1082 (2)
Missing	3931 (6)

Of the scheduled visits, 61,725 (96%) were successfully completed via video or phone-only. All telehealth visits were initially attempted via video rather than phone-only. Of the successfully completed visits, 53,541 (86.7%) were done using synchronous audio-visual telehealth and 8184 (13.3%) were audio/phone-only visits. In total, 53,541 (86.7%) of scheduled telehealth visits were successfully done using synchronous audio-visual telehealth, while 8184 (13.3%) visits were audio/phone-only visits; 2,722 (4%) of attempted telehealth visits were not completed in any form.

Over 1 month, the student-led Vanderbilt Telehealth Volunteer Program assembled 135 medical student volunteers who collectively dedicated 1300 hours to directly assist 5182 patients preparing for telehealth. Patients who received a call from a medical student had decreased rates of failed video visits (OR 0.54; 95% CI: 0.48–0.60).

A multivariable logistic regression model was used to evaluate the likelihood of a visit being attempted but not completed, which occurred rarely at only 4% across all clinics (Table 2). The age range of 18–30 years was most likely to have an incomplete visit. Completed visits were more likely at all older age ranges. Using commercial insurance status as a reference, non-commercial insurance status increased the likelihood for an incomplete visit. Females were more likely to have an incomplete visit (OR 1.26; 95% CI: 1.16–1.36). Black race was also associated with greater likelihood of an incomplete visit (OR 1.28; 95% CI: 1.15–1.46).

Table 2.

Risk factors for an incomplete telehealth visit (neither video nor audio).

Incomplete visit (‘no-show’)	Odds ratio	95% CI	p-value
Age
18–30	ref	ref
31–50	0.79	0.68–0.91	<0.05
51–70	0.83	0.71–0.96	<0.05
>70	0.7	0.57–0.83	<0.05
Insurance status
Commercial	ref	ref
Medicare	1.13	1.02–1.26	<0.05
Medicaid	1.72	1.44–2.12	<0.05
Other	1.06	0.76–1.74	NS
Sex	1.26	1.16–1.36	NS
Race/ethnicity
White	ref	ref
Black	1.28	1.15–1.46	<0.05
Hispanic	1.33	0.98–1.48	NS
Asian	0.81	0.57–1.16	NS

A second logistic regression model was used to evaluate the likelihood of a failed video visit (converted to a phone-only visit) controlling for age, sex, race and insurance status (Table 3). Age, non-commercial health insurance and Black race were more likely to lead to a phone-only visit. Compared to patients 18–30 years of age, incrementally increasing age increased the risk of a failed video (phone-only) visit. Of note, patients in the age group >70 years were four times as likely to have a failed video visit as patients aged 18–30 years. All non-commercial insurance statuses increased the likelihood of a failed video telehealth visit. Female versus male sex was not significant for a failed video telehealth visit. Black race was associated with an increased risk of a failed video visit (OR 1.8; 95% CI: 1.67–1.92).

Table 3.

Risk factors for a failed video telehealth visit (conducted using audio-only/phone visit).

Failed video (phone-only) telehealth visit	Odds ratio	95% CI	p-value
Age
18–30	ref	ref
31–50	1.31	1.13–1.51	<0.05
51–70	2.98	2.60–3.42	<0.05
>70	4.16	3.58–4.82	<0.05
Insurance status
Commercial	ref	ref
Medicare	1.91	1.80–2.04	<0.05
Medicaid	2.14	1.83–2.50	<0.05
Other	1.83	1.50–2.22	<0.05
Sex	1.05	0.99–1.10	NS
Race/Ethnicity
White	ref	ref
Black	1.8	1.67–1.92	<0.05
Hispanic	1.24	0.98–1.57	NS
Asian	0.81	0.64–1.01	NS

Discussion

The potential advantages of telehealth have long been recognized, including savings of time and cost, ability to overcome transportation and other access barriers, and ability to deliver healthcare during large-scale emergencies. In some areas of healthcare, telehealth has been shown to have high patient satisfaction and to be just as effective as medical care delivered in-person.^11,12 Despite evidence for efficacy of telehealth, many barriers slowed its adoption including regulatory and billing challenges, provider education and willingness, concerns over privacy and security, and technology challenges.^4,13–15

With the onset of the COVID-19 pandemic in the United States, the Department of Health and Human Services declared a public health emergency and temporarily waived some restrictions on telehealth, allowing for geographic flexibility of patient location, including receiving services virtually from their home. Commercial insurers also shifted to more permissive policies. The urgent need to limit spread of COVID-19 also helped to overcome barriers such as clinician willingness and health system resistance to disruptive change.⁴ This created a unique situation that led to rapid adoption of telehealth at large scale for many healthcare providers and systems.

Data has been emerging from several institutions indicating that older patients, minority patients and those with non-commercial insurance have not successfully accessed telehealth at the same rate as other groups.^6,7,10,16 Concurring with these findings, in our study, risk factors for a failed video telehealth visit emerged including increasing age range, non-commercial health insurance and Black race. Interestingly, our study observed that while younger patients (18–30 years) were the most likely to have successful telehealth video visits, they were also more likely to completely miss telehealth appointments. Patients forgetting visits, or electing to ‘no-show’, could not be distinguished from technical causes in our data set and may have contributed to this observation. Other studies have shown the younger demographic may be more likely to miss appointments. A large Veterans Affairs study in 2016 found that younger patients were more likely to no-show their in-person appointments.¹⁷ The baseline incomplete or ‘no-show’ rate for medicine clinics in February 2020, before the first case of COVID-19 in this state, was 7.9% for patients using traditional scheduling and 5.4% in patients scheduling online (unpublished operational data). This suggests that overall rate of telehealth video no-show may not differ significantly from prior baseline. However, other factors, such as contact with patients about changing the appointment type, thus giving them an opportunity to reschedule or cancel, may have also influenced this behaviour. Strikingly, patients >70 years of age were four times as likely to have a failed video visit leading to a phone-only visit compared to patients 18–30 years of age.

Encouragingly, a dedicated patient education protocol significantly improved the likelihood of a successful video telehealth visit. Our study found that individuals who received a call from a medical student had decreased rates of failed video visits, with an odds ratio of 0.54 (95% CI: 0.48–0.60), indicating that the student intervention was effective. The significant success of the medical student initiative highlights the efficacy of reaching out to patients directly prior to a telehealth appointment. Structured pre-calls that educate patients about telehealth, promote self-efficacy, perform a test visit and address privacy concerns are an important tool to overcome potential disparities in telehealth access. While structured patient preparation requires resources, our study and other recent studies have found that those with increasing age, non-commercial health insurance and race may be populations particularly vulnerable to difficulties with telehealth. These findings can be used to apply interventions to those patients most at risk, therefore making the intervention a potentially cost-effective and valuable resource for organizations. Increasing engagement with patients and understanding their experience of telehealth will also be important to sustain telehealth as an integral part of healthcare post-pandemic.¹⁸

Limitations of the study include that the data were from a single academic center, which may be affected by region-specific biases. The analysis was based on EMR and billing data, and therefore more patient-specific disease-related information was not available. We do not have data available to analyse the cause of a failed visit (i.e. patient electing to no-show, lack of patient knowledge, lack of computer, phone or internet access, or privacy concerns). Some failed telehealth appointments may simply have been the result of the rapid transition to telehealth and failed communication streams rather than actual barriers to accessing care. While it is likely that patients who did not have the equipment to join a telehealth visit cancelled visits completely, reason for cancellation was not accessible in the EMR. Issues of access to internet services remains a fast-changing area of study which will continue evolving. We had relatively small numbers of minority patients, which will make evaluating this at a multi-center or national level an important future study. Other literature suggests continued limitations in digital technology access associated with race and socioeconomic status. Yoon et al. found that minority status and low socioeconomic status substantially reduced the odds of a patient using the internet to access health information.⁸ In another study, Black individuals, Latinx and those without an educational degree had higher odds of never logging on to their internet-based patient portal.¹⁹ Further investigation identifying specific barriers to telehealth care will be important to design solutions.

While there is little available evidence comparing effectiveness between video visits and phone visits, more data on the benefit of video visits are emerging. Prior work demonstrates that video contributes to quality and satisfaction.^20,21 In contrast, there is little available literature on effectiveness of phone-only visits as a substitute for an office visit. Video visits allow some physical exam as well as nuances of nonverbal communication, albeit less complete than an in-person visit.²¹ More study is needed before considering phone-only to be an equivalent model for care. Additionally, phone telehealth visits are reimbursed currently at much lower rates than video telehealth visits. The Centers for Medicare and Medicaid Services (CMS) has signalled that the enhanced payment for phone visits during the public health emergency will expire. The video telehealth model is likely to be the preferred model as reimbursement continues to evolve. The tradeoff is that more technical demands are placed on the patient, so understanding risk factors for telehealth inaccessibility and developing mitigating strategies will be important.

We found that a protocol designed to improve patient education directly prior to a telehealth appointment significantly increased the success rate of video telehealth visits. Patients aged 18–30 years, those with non-commercial health insurance and those of Black race were more likely to no-show their virtual appointments. Patients of increasing age, patients with non-commercial health insurance and patients of Black race had increased likelihood of a planned video telehealth visit converting to phone-only. Further exploration of demographic factors related to successful telehealth appointments is valuable for reducing healthcare disparities. Understanding further ways to enhance patient education, especially for those at risk for a failed telehealth visit, can improve access to healthcare in the digital age. In addition to addressing patient factors, policy, reimbursement, clinician and health system factors will need to be addressed to sustain telehealth as a relevant, ongoing care strategy.^4,18

Disclosures

Dr Sara Horst has been a consultant for Janssen, UCB, Boehringer Ingelheim and Gilead. Dr Dawn Beaulieu has been a consultant for Takeda, Abbvie, Pfizer and UCB. Dr David Schwartz has been a consultant for Abbvie, Genetech, Gilead, Janssen, Pfizer, Takeda and UCB.

Supplemental Material

sj-pdf-1-jtt-10.1177_1357633X211008786 - Supplemental material for A patient education intervention improved rates of successful video visits during rapid implementation of telehealth

Supplemental material, sj-pdf-1-jtt-10.1177_1357633X211008786 for A patient education intervention improved rates of successful video visits during rapid implementation of telehealth by Roman E Gusdorf, Kaustav P Shah, Austin J Triana, Allison B McCoy, Baldeep Pabla, Elizabeth Scoville, Robin Dalal, Dawn B Beaulieu, David A Schwartz, Sara N Horst and Michelle L Griffith in Journal of Telemedicine and Telecare

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship and/or publication of this article.

ORCID iD

Michelle L Griffith

Supplemental material

Supplemental material for this article is available online.

References

Wilder-Smith

Freedman

DO.

Isolation, quarantine, social distancing and community containment: pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak. J Travel Med 2020; 27: taaa020. DOI: 10.1093/jtm/taaa020.

Klein

Busis

NA.

COVID-19 is catalyzing the adoption of teleneurology. Neurology 2020; 94: 903–904. DOI: 10.1212/wnl.0000000000009494.

Hollander

Carr

BG.

Virtually perfect? Telemedicine for Covid-19. N Engl J Med 2020; 382: 1679–1681. DOI: 10.1056/NEJMp2003539.

Smith

Thomas

Snoswell

, et al. Telehealth for global emergencies: Implications for coronavirus disease 2019 (COVID-19). J Telemed Telecare 2020; 26: 309–313. DOI: 10.1177/1357633X20916567.

Centers for Disease Control and Prevention. Using Telehealth to Expand Access to Essential Health Services during the COVID-19 Pandemic, https://www.cdc.gov/coronavirus/2019-ncov/hcp/telehealth.html (accessed 19 January 2021).

Chunara

Zhao

Chen

, et al. Telemedicine and healthcare disparities: a cohort study in a large healthcare system in New York City during COVID-19. J Am Med Inform Assoc 2020; 28: 33–41. DOI: 10.1093/jamia/ocaa217.

Eberly

Kallan

Julien

, et al. Patient characteristics associated with telemedicine access for primary and specialty ambulatory care during the COVID-19 pandemic. JAMA Netw Open 2020; 3: e2031640. DOI: 10.1001/jamanetworkopen.2020.31640.

Yoon

Jang

Vaughan

, et al. Older adults' internet use for health information: digital divide by race/ethnicity and socioeconomic status. J Appl Gerontol 2020; 39: 105–110. DOI: 10.1177/0733464818770772.

Walker

Hefner

Fareed

, et al. Exploring the digital divide: age and race disparities in use of an inpatient portal. Telemed J E Health 2020; 26: 603–613. DOI: 10.1089/tmj.2019.0065.

10.

Jaffe

Lee

Huynh

, et al. Health inequalities in the use of telehealth in the United States in the lens of COVID-19. Popul Health Manag 2020; 23: 368–377. DOI: 10.1089/pop.2020.0186.

11.

Lin

Casteel

Shigekawa

, et al. Telemedicine-delivered treatment interventions for substance use disorders: A systematic review. J Subst Abuse Treat 2019; 101: 38–49. DOI: 10.1016/j.jsat.2019.03.007.

12.

Uppot

Virtual Radiology Consults Can Lead to Improved Care, Better Understandings of the Radiologist's Role, https://www.massgeneral.org/assets/MGH/pdf/imaging/radiology-rounds/radiology-rounds-nov-dec-2017.pdf (2017, accessed 19 January 2021).

13.

Tuckson

Edmunds

Hodgkins

ML.

Telehealth. N Engl J Med 2017; 377: 1585–1592. DOI: 10.1056/NEJMsr1503323.

14.

Cross

Kane

Integration of telemedicine into clinical gastroenterology and hepatology practice. Clin Gastroenterol Hepatol 2017; 15: 175–181. DOI: 10.1016/j.cgh.2016.09.011.

15.

George

Dominic

Cross

RK.

Integration of telemedicine into clinical practice for inflammatory bowel disease. Curr Opin Gastroenterol 2020; 36: 304–309. DOI: 10.1097/mog.0000000000000647.

16.

Weber

Miller

Astha

, et al. Characteristics of telehealth users in NYC for COVID-related care during the coronavirus pandemic. J Am Med Inform Assoc 2020; 27: 1949–1954. DOI: 10.1093/jamia/ocaa216.

17.

Davies

Goffman

May

, et al. Large-scale no-show patterns and distributions for clinic operational research. Healthcare (Basel) 2016; 4: 15. DOI: 10.3390/healthcare4010015.

18.

Thomas

Haydon

Mehrotra

, et al. Building on the momentum: Sustaining telehealth beyond COVID-19. J Telemed Telecare. Epub ahead of print 26 Sept 2020. 1357633X20960638. DOI: 10.1177/1357633X20960638.

19.

Sarkar

Karter

Liu

, et al. Social disparities in internet patient portal use in diabetes: Evidence that the digital divide extends beyond access. J Am Med Inform Assoc 2011; 18: 318–321. DOI: 10.1136/jamia.2010.006015.

20.

McLendon

SF.

Interactive video telehealth models to improve access to diabetes specialty care and education in the rural setting: A systematic review. Diabetes Spectr 2017; 30: 124–136. DOI: 10.2337/ds16-0004.

21.

Rodriguez

Betancourt

Sequist

, et al. Differences in the use of telephone and video telemedicine visits during the COVID-19 pandemic. Am J Manag Care 2021; 27: 21–26. DOI: 10.37765/ajmc.2021.88573.

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