ABSTRACT
Introduction
The COVID-19 pandemic spurred telehealth use in US oncological care but there remains limited data on the onco-primary cancer survivorship population. We investigated patterns of telehealth use during the pandemic and factors driving utilization.
Methods and Materials
Retrospective study of patients aged 21 years and older diagnosed with breast, colorectal, prostate or non-small lung cancer (stages 1–4). The study period evaluated was defined as during COVID-19: March 1, 2020–April 30, 2021. Patient cohorts were defined as “ever telehealth users” and “never telehealth users”. We tested between-cohort differences in baseline characteristics using Pearson's chi-square tests.
Results
We identified 4931 onco-primary patients. Of these patients 36.7% (n= 1812) were “ever cancer telehealth users” and 63.3% (n = 3119) patients were “never cancer telehealth users.” Among telehealth users, 44.6% were 65 years or older at cancer diagnosis, 24% were Black, 24.1% lived in rural settings and the most common cancer types were breast (40.4%) followed by prostate (30.4%). “Never telehealth user” had similar demographics. Increased telehealth use was seen in those patients with a higher baseline comorbidity burden (RR 1.14; 95% CI 1.06–1.23), prostate cancer (Prostate RR 1.33; 95% CI 1.16–1.54) and advanced stage cancer (RR 1.20; 95% CI 1.08–1.34).
Conclusion
Telehealth, while not as heavily utilized, remains an important care tool in marginalized rural and Black onco-primary care patients.
Implications for Practice
This paper highlights baseline use rates of telehealth in the onco-primary patients including more health disparate populations and helps guides future healthcare system investments in this technology.
Background
Implementation of telehealth has been a global health priority since 2005; however, the adoption of telehealth in US oncological care has historically been low, slow, and not widespread. In the US, the use of telehealth was stymied by a lack of sufficient reimbursement by insurance plans, strict regulatory restrictions on where and how telehealth could be delivered and privacy regulations that required significant technological investment to meet compliance standards. However, in 2020 the COVID-19 pandemic spurred the rapid expansion of the teleoncology landscape by easing regulatory hurdles including allowing for telehealth to be delivered through different modalities (i.e. phone and video visits) while also establishing reimbursement parity for telehealth care delivery [Citation1–3]. In some instances, the proportion of telehealth visits, for example at a large US academic cancer center, was as low as 7% pre-COVID and post-COVID rose to as high as 72% [Citation4]. The importance of minimizing in-person contact and following nationally mandated stay-at-home orders was particularly paramount in immunocompromised individuals and resulted in a rapid rise in remote care delivered to cancer survivors (defined here as any person from the time of cancer diagnosis through the balance of one’s life) [Citation5].
It is estimated that as of 2019 there are approximately 17 million cancer survivors in the US with the number expected to rise to 22 million by 2030 [Citation6]. In addition to those currently receiving treatment, this includes patients who are post treatment and whose predominant care needs are now long-term follow-up care and general medical and preventive care. As a result, coordination and communication between primary care providers (PCP) and cancer specialists are critical. Onco-primary care patients are part of an innovative care model where patients who have been diagnosed with cancer are also supported by their primary care providers in a team-based approach of managing their care by considering a comprehensive, whole person care approach to the care they receive [Citation7]. Given the fragmentation in care between oncology and primary care, telehealth can be utilized to facilitate care coordination to better manage oncologic surveillance, incorporate preventative care and healthy lifestyle initiatives and address comorbidities. Telehealth also allows for increased access to care for those patients living in rural environments with long travel distances or poor caregiver support to facilitate in-person visits with multiple physicians [Citation8]. Patient-facing telehealth can provide a potentially crucial role in facilitating co-management between oncologists and PCPs while also serving to increase access to care in some marginalized populations of cancer survivors. However, there remains limited data on the efficacy and trends of telehealth use in the survivorship population [Citation9].
In this study, we sought to better understand the Duke University Health System (DUHS) telehealth patterns of cancer survivors using both primary care and oncology services, particularly during the COVID-19 pandemic.
Materials and methods
Population setting
We performed a retrospective cohort study of living adult DUHS patients aged 21 years and older who were diagnosed with breast, colorectal, prostate, or non-small cell lung cancer (stages 1-4) between January 2019 and April 2021. We excluded patients with unknown age or stage information or those diagnosed with stage 0 cancer. To further identify the onco-primary population we identified each patient that had a DUHS PCP assigned as indicated by the electronic health record (EHR; Epic). The study periods evaluated were defined as during COVID-19: March 1, 2020–April 30, 2021. We chose these time periods as they were consistent with Medicare reimbursement rules around telehealth due to the pandemic. As insurance companies were not reimbursing for most telehealth visits prior to COVID-19 and as a result for this study all the telehealth encounter data came from the period “during COVID-19”.
Data source
Data on visits were extracted from the Duke EHR and patient demographics were extracted from the Duke Cancer Institute’s (DCI) cancer registry. This study was deemed exempt by the Duke Institutional Review Board.
Study measures
From the DCI cancer registry and Duke EHR, we extracted information on patient age at the time of cancer diagnosis, biological sex, race/ethnicity (non-Hispanic Black, Hispanic, other/unknown, non-Hispanic white), cancer type, cancer stage, marital status, rurality, primary/secondary payor (commercial insurance, public insurance, self-pay, other and missing), PCP specialty (family medicine, internal medicine, other), enrollment in MyChart and preferred language. MyChart is the online portal that patients use to view EHR medical records and message their respective providers. Rurality was defined by applying the Rural-Urban Commuting Area Codes (RUCA) classification B to the patient’s ZIP code [Citation10]. We used the Klabunde modification of the Charlson comorbidity index (CCI) to assess the comorbidity index [Citation11].
Outcomes
Telehealth visits were defined as encounter types coded for telemedicine, telemedicine-phone or e-visit with an appointment status code for completed, arrived, or present. Of note, data for telehealth visits were analyzed by combining the different telehealth modalities under the umbrella of “telehealth visits” more broadly. We defined one cohort of patients as the “ever telehealth user” cohort (i.e. at least one telehealth encounter between March 2020 and April 2021). We defined a second cohort of patients as the “never telehealth user” cohort (i.e. no telehealth encounters between March 2020 and April 2021). Cancer-related telehealth visits were defined as a subset of telehealth visits where the encounter record showed a diagnosis of breast, colorectal, non-small cell lung or prostate cancer (Supplementary Table 1).
Statistical analysis
Baseline patient characteristics were described overall and by cohort (ever vs. never telehealth). We tested between-cohort differences in baseline characteristics using Pearson’s chi-square tests. The proportion of cancer and non-cancer telehealth encounters was also compared across cohorts. To assess the association between baseline characteristics and telehealth use, we conducted univariable and multivariable-adjusted log-binomial regression to estimate relative risks. Variable collinearity was assessed using the variance inflation factor method [Citation12]. We analyzed data using SAS version 9.4 software (SAS Institute, Cary, NC) and produced figures in Microsoft Excel (2016).
Results
Patient characteristics
We identified 4931 onco-primary care patients (). Of these patients, 36.7% (n = 1812) were “ever cancer telehealth users” and 63.3% (n = 3119) patients were identified as “never cancer telehealth users.” Among telehealth users, 44.6% were aged 65 years or older at cancer diagnosis and 57.4% were women. Most patients were married (64.1%), non-Hispanic white (68.8%) and lived in urban settings (77.6%). The most common cancer type among telehealth users was breast (40.4%) followed by prostate (30.4%). Finally, most patients had public insurance (54%) and spoke English (98.5%).
Table 1. Baseline demographic characteristics overall and by ever vs. never telehealth users and ever vs. never cancer telehealth users.
“Never telehealth users” had similar demographics with 49.3% aged >65 years, 53.9% were women, 67.9% were non-Hispanic white, and 75.9% living in urban settings. The most common cancer types were also breast (36.2%) followed by prostate (28.7%). Similarly, most patients also had public insurance (58.1%) and were predominantly English speakers (97.6%).
Telehealth encounter and trends
We considered the proportion of total encounters that were telehealth encounters delivered per month from March 2020 through April 2021 (). Throughout all months, traditional, in-person visits remained the predominant type of visit (range: 86.2%–94.9%). Telehealth encounters gradually increased over time, peaking in April 2020, and there was some sustained telehealth use throughout the study period.
Figure 1. Proportion of cancer and non-cancer related telemedicine encounters by month.
Among telehealth encounters, we also considered the proportion of encounters per month that were attributed to non-cancer related primary care visits vs. cancer-related visits (). Cancer-related telehealth visits represented the minority of telehealth visits. There was a surge in cancer-related telehealth visits early in the pandemic period (e.g. April and May 2020). While some limited telehealth activity was sustained throughout the study period, cancer-related telehealth leveled-off at approximately 1.7% of visits. Non-cancer-related telehealth visits followed a similar pattern but did so at a higher percentage of overall visits. Non-cancer-related telehealth visits also peaked early in the pandemic period (e.g. April and May 2020) and leveled-off over time, at approximately 3.4% of telehealth visits.
In the multivariable-adjusted log-binomial regression analyses, higher baseline comorbidity burden was associated with increased telehealth visits (; NCI Comorbidity index 2 + versus 0: RR 1.14; 95% CI 1.06–1.23) and with cancer-related telehealth visits (RR 1.57 95% CI 1.30–1.91). Breast cancer and prostate cancer patients also had higher rates of cancer-related telehealth visits compared to patients with colon cancer (Breast RR 1.19; 95% CI 1.03–1.37; Prostate RR 1.33; 95% CI 1.16–1.54). Diagnosis with advanced stage cancer compared to early-stage cancer was also associated with a higher likelihood of cancer-related telehealth visits (Stage IV vs Stage I RR 1.20; 95% CI 1.08–1.34). Patients without activated MyChart accounts were less likely to use any telehealth (RR 0.90; 95% CI 0.87–0.93) or cancer-related telehealth (RR 0.71; 95% CI 0.63–0.80) compared to patients with activated MyChart accounts.
Table 2. Multivariable regression for patient characteristics and cancer-related telehealth use.
Discussion
The rapid adoption of telehealth into oncological care delivery propelled by the pandemic has presented an additional avenue to improve accessibility and care coordination for high complexity patients. Available data suggests that telehealth will persist and grow after the pandemic ends with projections that telehealth could virtualize care for 20% of all Medicare, Medicaid, commercial outpatient, office, and home health spend. Estimates have shown that $250 billion of healthcare spending in the US could be shifted to virtual care [Citation13]. Cancer survivors could particularly benefit from telehealth given their need for both oncologic and primary care services. In our study, we leveraged institutional data to identify trends in telehealth use in the cancer population to better inform utilization patterns. We found that telehealth while its use increased in the very early days of the pandemic, it then tapered off back to the baseline, but overall use was low at <6% of encounters.
Our study has several important findings. First, cancer telehealth continued to be utilized at 1.5–2% of total encounters (ranging from ∼150 to 200 teleoncology encounters per month) at the tail end of the pandemic. While prior work has emphasized outcomes and accessibility for teleoncology care, we focused on utilization trends in the cancer survivor population [Citation14]. Importantly, the continued use of telehealth among cancer survivorship patients quantified by number of encounters gives health systems a baseline to estimate investment in infrastructure for telehealth going forward. With some estimates, showing that population needs will outstrip the current pace of telehealth infrastructure, the evaluation of telehealth preparedness and continued investment in this technology by health systems should remain an important priority going forward [Citation15]. This may be particularly important for certain patients living in rural settings with limited access to subspeciality care. Furthermore, the evidence supports a continued policy and legislative efforts to strengthen telehealth use. While the public health emergency resulted in loosening restrictions on telehealth care delivery some of these legislative restrictions have been reinstated limiting providers ability to provide telehealth care. Provisions that were waved during the pandemic including the ability to provide reimbursable telehealth care to patients outside of rural areas and from home rather than a provider’s office have an uncertain future. However, the utilization rates of telehealth as shown in this study could signal to policymakers the importance of supporting legislature that encourages telehealth use.
It is worth noting that comparative studies evaluating telehealth cancer found higher utilization rates of ∼15–20% [Citation16, Citation17]. These differences may in part be due to limited studies looking at utilization rates at the more recent time frame investigated in this study which evaluated use in April and May 2021. Furthermore, our study only included patients who also had an established PCP which could have further narrowed the population of interest. From a clinical standpoint, low uptake might also just signal that telehealth is not a great modality for some of the services that cancer survivors needs, especially those on active treatment who were included in this analysis. If patients are coming to the hospital for treatment then combining that with an in-person visit would be logistically easier and contribute to lower telehealth utilization rates. As telehealth utilization in oncology care remains relatively nascent in the US, patient preferences on when to use telehealth and on preferred care delivery platforms must be better elicited. Despite certain advantages to telehealth, the question remains about the most appropriate oncologic patient and clinical scenario when telehealth would be best deployed. For example, colorectal cancer patients in our study utilized telehealth less. These patients, especially those with rectal cancer, have a bowel diversion requiring a permanent colostomy which patients may feel is better managed and cared for in an in-person visit instead. Additionally, while our study showed some association between increased comorbidities and increased telehealth utilization these patients likely have an increased number of appointments in general and so additional research is needed to further delineate the patient that would benefit the most from this modality. Research including qualitative work evaluating telehealth preferences in this population will be important to delivering high-quality teleoncology care.
Second, although most telehealth non-users were 65 years and older a large fraction (45%) of telehealth users also fell in this age range. Prior studies have shown that older patients’ resistance to engaging in telehealth could center on an inability to perform a physical examination, general concerns with the quality of telehealth care delivered and preferences for certain telehealth modalities like audio visits [Citation18]. However, while age-related inequities in telehealth use are frequently cited in the literature as a limitation for this care delivery, this study shows a relatively robust use of telehealth in older onco-primary patients [Citation19]. This reinforces the importance of not making assumptions based on a patient’s characteristics, but instead of soliciting patient preferences for telehealth use. This study finding provides important insight into mitigating the effects of ageism, defined as a negative attitude toward older adults, which has been pervasive in our healthcare system [Citation20, Citation21]. Ageism places the older adult population at risk for exclusion from telehealth despite a willingness to engage with telehealth [Citation22]. Importantly, the high percentage of older cancer survivors utilizing telehealth may support future efforts to scale telehealth support even among the aging population. This is also important data for providers engaging in shared decision making “post pandemic” to consider offering telehealth when issues of accessibility such as travel distance, physical disability, nursing home use might limit an older patient’s ability to participate in an in-person visit. Again, the use of telehealth is of particular importance in this population of onco-primary patients where coordination of care between both primary care physicians and oncologists can be impacted by these barriers. In the US, as the COVID-19 pandemic public health emergency mandates are expiring, telehealth reimbursement and reversion to older regulations may severely inhibit the use of telehealth for patients which could be particularly detrimental for older patients for the reasons listed above. Therefore, our research showing the continued higher utilization of telehealth in this older population of onco-primary care has important implications to better inform future policy decisions.
Finally, telehealth is used by a lower but significant fraction of Black (24%) and rural (22.2%) onco-primary patients compared to those non-telehealth cancer survivors who are Black (24.4%) and rural (23.4%). Several studies have investigated the potential disparities existing in telehealth access especially among racial/ethnic minorities and rural populations [Citation19, Citation23, Citation24]. Our study confirms the finding of decreased telehealth utilization in Black and rural populations, highlighting opportunities for further research investigating the reasons for decreased accessibility and use in these populations. Given that MyChart activation in our multivariate analysis was associated with telehealth use, this might be a simple screening tool to identify patients who are more likely to engage with the telehealth modality. A patient who has activated MyChart is more likely to be digitally literate, have access to the technology required (e.g. smart phone, adequate internet, etc.) and based on this enhanced digital literacy are more likely to use telehealth. Additionally, we should consider if there are differential preferences in how Black and rural patients would want to engage with their providers. Understanding patient and clinician preferences and satisfaction with telehealth use plays an important role in driving telehealth utilizations. The literature has shown that in general, patients have been satisfied with telehealth care while demographics differences including race, gender and disability status may impact this satisfaction however there remains inconsistencies on what differences impacted utilization. Other studies have demonstrated that most clinicians remain satisfied with telehealth as it allows for work from home and decreased transportation and found it to be effective in the use of cancer survivorship which is relevant to our onco-primary population. However, there remained some concerns that telehealth was still inferior to in person encounters for the patient physician relationship [Citation25–27]. Other potential targets to improve utilization include assessing technology proficiency, broadband internet capabilities at home as well as provider engagement in offering telehealth for Black and rural patients. Importantly, while issues regarding access and utilization are being addressed it is critical that health systems continue to invest resources for telehealth as both rural and Black patients are particularly vulnerable to disparities driven by social determinants of health. Focusing the intensity of resources on this subset of onco-primary patients will play an important role in mitigating the digital divide that might be present or perpetuated. As noted in other studies, the incorporation of the end user including both patient and clinician engagement in the co-design of solutions will be critical for the success of developing these telehealth programs [Citation24]. Future research will center on patient satisfaction with telehealth use in this population to better inform providers and health systems looking to actively invest support in telehealth use in the aging population [Citation28].
Limitations
The study findings must be considered within the context of our study design. First, this is a single institution study that limits the generalizability of the results nationwide. Second, the retrospective nature of the study did not permit incorporation of patient level factors, so the reasons patients were unable to utilize telehealth are not captured. This includes lack of internet services, unfamiliarity with technology or poor access to computers or smart phones. Importantly, we do not have an effective way to assess patient preferences for telehealth. This includes healthcare provider preference which is currently not included as a driver of telehealth utilization. As a result, this impacts our ability to unequivocally say that the patterns observed in this paper are the only primary drivers of telehealth usage as confounders do exist. Given the constraints of our research data there are also limitations in establishing causation definitively in all instances. Research especially in the onco-primary population on telehealth preferences will be important going forward. Second, despite the broad geographic footprint of our institution there was a lack of racial and ethnic diversity in our population. Third, the lack of comprehensive claims data can limit our ability to capture patients who obtained telehealth care at other institutions. Fourth, we did not include outcomes data including follow up adherence, cancer recurrence, readmissions, or patient satisfaction as we felt that this was not in the scope of this study. Fifth, we did not have any methods for accounting for COVID-19 waves or surges. Sixth, we were not able to identify the specific clinical conditions or patient population that would most benefit from telehealth use. Seventh, the policy commentary is endemic to an American lens which given the unique reimbursement and healthcare policy landscape in the US may not be as broadly applicable to other countries. Finally, for our study, the decision to offer telehealth was determined by individual clinics and those decisions and the reasons for inclusion and exclusion were not available for review from our data. Despite these limitations, our research can help inform future work to help guide legislative decisions by delineating how changes in telehealth utilization may differentially be impacted by pandemic, patient preferences or payer reimbursement policies.
Conclusion
Teleoncology is an important care delivery tool especially in the aging population of onco-primary care patients who require continued care coordination and easier accessibility to care. While the COVID-19 pandemic ushered in the rapid infusion of teleoncology care, the legislative, policy and health systems investment in its future remains unclear. Our study findings including continued baseline utilization of teleoncology particularly among older adults provides continued evidence to support the infrastructure of telehealth care in this population. Additionally, telehealth, while not as heavily utilized, remains an important care tool in marginalized rural and Black onco-primary care patients.
Disclaimers
This study has not been presented in part at a major research meeting prior to submission for publication. The findings and conclusions in this document are those of the author(s) who are responsible for its contents and do not represent the views of the Department of Veterans Affairs, the US Government, or Duke University. Therefore, no statement in this article should be construed as an official position of the Department of Veterans Affairs or Duke University.
Conflicts of Interest
Dr. Zullig reports consulting with Novartis and Eisai.
Supplemental Material
Download MS Word (179.7 KB)Acknowledgements
Vishnukamal Golla: Conception/Design, collection of data, data analysis and interpretation, manuscript writing and final approval of manuscript. Nicole Frascino: Collection of data, data analysis and interpretation, manuscript writing and final approval of manuscript. Lauren E. Wilson: Collection of data, data analysis and interpretation, manuscript writing and final approval of manuscript. Megan Oakes: Collection of data, manuscript writing and final approval of manuscript. Kevin C. Oeffinger: Data analysis and interpretation, manuscript writing and final approval of manuscript. Devon K. Check: Data analysis and interpretation, manuscript writing and final approval of manuscript. Leah L. Zullig: Conception/Design, collection of data, data analysis and interpretation, manuscript writing, final approval of manuscript and financial support.
Disclosure statement
No potential conflict of interest was reported by the authors.
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