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Utilization of telemedicine in cancer patients, an analysis of the National Health Interview Survey data in the COVID-19 era
Khalid Alkhatib, M.D., Jason Qian, M.D., Catherine Gu, M.D., Mara Koelker, M.D., Muhieddine Labban, M.D., Nicola Frego, M.D., Alexander P. Cole, M.D., Quoc-Dien Trinh, M.D..
Brigham and Women's Hospital, Boston, MA, USA.

Introduction: With recent advances in digital communications technology and the backlog of cancer care resulting from the COVID-19 pandemic, the demand for telemedicine has skyrocketed. The latest evidence suggests that high-quality oncological care can be delivered by means of telemedicine, with some caveats. Against this backdrop, we sought to analyze the use of telemedicine among cancer survivors, hypothesizing that its use may be higher for certain oncological conditions relative to others.Materials & Methods: We conducted a cross-sectional study on cancer patients using data between July and December 2020 in the National Health Interview Survey (NHIS). We utilized an affirmative answer to “Have you EVER been told by a doctor or other health professional that you had Cancer or a malignancy of any kind?” to identify patients with cancer history. We used the question “In the past 12 months, have you had an appointment with a doctor, nurse, or other health professional by video or by phone?” to identify telemedicine recipients. Survey-weighted multivariable Poisson regression analysis adjusted for potential confounders was conducted to estimate risk ratios (RR) for receipt of telemedicine, and a two-way interaction between currently receiving treatment and cancer type was assessed for any effect modification. Results: We Identified 2,389 individuals with a cancer history, representing a weighted population of 12.312 million. The prevalence of telemedicine utilization was 44% (see Table1). Relative to breast cancer survivors, we found that PCa was a significant predictor of receipt of telemedicine (RR: 1.39, 95% CI: [1.06-1.81], P= 0.02), (see Table2). A significant interaction was found between those currently receiving treatment for cancer and cancer type P_int<0.01; marginal probability analysis showed that patients currently receiving PCa treatment were more likely to receive telemedicine in comparison to those not on treatment, with an adjusted risk difference of 0.18, (95% CI[0.01-0.35], P=0.04) (see Table3). Conclusions: Our study suggests that telemedicine appointments were widely used among cancer survivors in 2020, with PCa survivors more likely to use telemedicine compared to other malignancies. Such findings may point to wider adoption of telemedicine among urologists, as suggested by other studies, or that PCa care lends itself better to telemedicine, compared to other malignancies. Future studies should focus on understanding the dynamics of such patient- and provider-level factors.

Table 1: Respondent with a history of cancer demographics and characteristics factored by receipt of virtual care using the National Health Interview Survey between July and December 2020
Variables	Total		Receipt of Virtual Care
	Weighted Mean (Std. dev.)	[95% CI]	Weighted Mean (Std. dev.)	[95% CI]	Weighted Prevalence[95% CI]
Age (continuous)
	65.55 (13.77)	[64.96,66.13]	65.89 (13.77)	[64.73,67.05]	0.44[0.42,0.47]
	N (Weighted%)	Population weighted estimation in million	N (Weighted%)	Population weighted estimation in million	Weighted Prevalence[95% CI]
Currently receiving treatment for cancer
No	2101(88)	10.815	934(83)	4.558	0.42[0.39,0.45]
Yes	288(12)	1.497	181(17)	0.907	0.61[0.53,0.68]
Total	2389(100)	12.312	1115(100)	5.465	0.44[0.42,0.47]
Cancer Type
Breast cancer	340(14)	1.667	143(12)	0.647	0.39[0.32,0.46]
Colorectal cancer	74(4)	0.478	32(4)	0.2	0.42[0.26,0.59]
Cervical/ovarian/uterine cancer	163(8)	0.979	75(8)	0.447	0.46[0.37,0.55]
Lung cancer	44(2)	0.238	23(2)	0.117	0.49[0.31,0.67]
Lymphoma cancer	54(2)	0.304	29(3)	0.161	0.53[0.37,0.68]
Thyroid cancer	54(3)	0.351	35(4)	0.235	0.67[0.47,0.82]
Skin cancer (including melanoma)	811(32)	3.997	346(28)	1.52	0.38[0.34,0.42]
Prostate cancer	211(9)	1.074	101(10)	0.543	0.51[0.42,0.59]
Other or multiple Cancers	638(26)	3.224	331(29)	1.597	0.50[0.45,0.54]
Total	2389(100)	12.312	1115(100)	5.465	0.44[0.42,0.47]
Gender
Female	1403(57)	6.978	673(57)	3.138	0.45[0.42,0.48]
Male	986(43)	5.334	442(43)	2.327	0.44[0.40,0.48]
Total	2389(100)	12.312	1115(100)	5.465	0.44[0.42,0.47]
Educational Attainment
Incomplete school or Highschool degree	716(40)	4.9	275(35)	1.888	0.39[0.34,0.43]
Associate or Bachelor''s degree	1211(45)	5.522	601(48)	2.619	0.47[0.44,0.51]
Master's degree	350(12)	1.44	179(13)	0.731	0.51[0.44,0.57]
Professional and Doctoral degree	106(3)	0.399	58(4)	0.21	0.53[0.41,0.64]
Total	2383(100)	12.261	1113(100)	5.448	0.44[0.42,0.47]
Race/Ethnicity
Non-Hispanic White	2083(83)	10.175	959(81)	4.408	0.43[0.41,0.46]
Non-Hispanic Black	134(7)	0.853	74(9)	0.465	0.55[0.44,0.65]
Hispanics	102(7)	0.818	50(7)	0.379	0.46[0.34,0.60]
Non-Hispanic Asians	27(2)	0.233	15(2)	0.133	0.57[0.35,0.77]
Others	43(2)	0.233	17(1)	0.08	0.34[0.20,0.52]
Total	2389(100)	12.312	1115(100)	5.465	0.44[0.42,0.47]
Receipt of treatment that weakens the immune system
No	2161(92)	11.179	959(87)	4.716	0.42[0.39,0.45]
Yes	207(8)	1.03	141(13)	0.676	0.66[0.57,0.73]
Total	2368(100)	12.209	1100(100)	5.392	0.44[0.42,0.47]
General Health Status
Poor	152(7)	0.832	93(9)	0.484	0.58[0.49,0.67]
Fair	376(18)	2.161	228(23)	1.273	0.59[0.52,0.65]
Good	795(34)	4.176	386(34)	1.882	0.45[0.40,0.50]
Very Good	756(30)	3.745	309(26)	1.425	0.38[0.34,0.42]
Excellent	309(11)	1.394	98(7)	0.397	0.28[0.22,0.35]
Total	2388(100)	12.308	1114(100)	5.461	0.44[0.42,0.47]
Family Income
$0 to $34,999	691(27)	3.283	334(27)	1.476	0.45[0.40,0.50]
$35,000 to $49,999	321(13)	1.632	145(14)	0.756	0.46[0.39,0.54]
$50,000 to $74,999	429(17)	2.086	194(17)	0.917	0.44[0.38,0.50]
$75,000 to $99,999	302(13)	1.591	140(12)	0.658	0.41[0.35,0.49]
$100,000 or greater	646(30)	3.72	302(30)	1.658	0.45[0.40,0.50]
Total	2389(100)	12.312	1115(100)	5.465	0.44[0.42,0.47]
Health Coverage
No	52(4)	0.505	10(1)	0.062	0.12[0.06,0.24]
Yes	2336(96)	11.801	1105(99)	5.403	0.46[0.43,0.48]
Total	2388(100)	12.306	1115(100)	5.465	0.44[0.42,0.47]
Urbanization level of residence
Non-metropolitan	430(18)	2.169	165(15)	0.844	0.39[0.33,0.45]
Medium and small metropolitan	825(32)	4.001	352(29)	1.558	0.39[0.35,0.44]
Large fringe metropolitan	566(25)	3.096	282(25)	1.371	0.44[0.39,0.50]
Large central metropolitan	568(25)	3.046	316(31)	1.692	0.56[0.50,0.61]
Total	2389(100)	12.312	1115(100)	5.465	0.44[0.42,0.47]
CI; confidence interval. The survey's response rate was 48.9%. Respondents who reported ever being diagnosed with cancer were included in the analysis, respondents who answered no, refused to answer, were not certain, or did not know were excluded from the analysis. Respondents who reported multiple cancers were grouped with other cancers, and all other cancer types were from participants reporting one cancer

Table 2: Survey Complex Weighted Poisson regression for the outcome of receiving virtual visits in patients with cancer history in the National Health Interview Survey between July and December 2020
	Risk Ratio	[95% CI]	P>t
Currently receiving treatment for cancer
No	Ref	-	-
Yes	1.26	[1.1-1.44]	<0.01
Cancer Type
Breast cancer	Ref	-	-
Colorectal cancer	1.28	[0.86-1.91]	0.23
Cervical/ovarian/uterine cancer	1.36	[1.06-1.73]	0.01
Lung cancer	1.23	[0.84-1.80]	0.28
Lymphoma cancer	1.51	[1.05-2.18]	0.03
Thyroid cancer	1.94	[1.46-2.59]	<0.01
Skin cancer (including melanoma)	1.16	[0.94-1.42]	0.16
Prostate cancer	1.39	[1.06-1.81]	0.02
Other or multiple Cancers	1.35	[1.11-1.65]	<0.01
Age (continuous)
	1.00	[1.00-1.01]	0.97
Gender
Female	Ref	-	-
Male	0.88	[0.78-1.01]	0.07
Educational Attainment
Incomplete school or Highschool degree	Ref	-	-
Associate or Bachelor''s degree	1.30	[1.15-1.48]	<0.01
Master's degree	1.45	[1.20-1.74]	<0.01
Professional and Doctoral degree	1.60	[1.27-2.03]	<0.01
Race/Ethnicity
Non-Hispanic White	Ref	-	-
Non-Hispanic Black	1.03	[0.85-1.24]	0.75
Hispanics	0.96	[0.75-1.23]	0.76
Non-Hispanic Asians	1.03	[0.67-1.60]	0.88
Others	0.86	[0.56-1.32]	0.48
Receipt of treatment that weakens the immune system
No	Ref	-	-
Yes	1.20	[1.03-1.4]	0.02
General Health Status
Poor	Ref	-	-
Fair	1.12	[0.92-1.37]	0.27
Good	0.87	[0.71-1.06]	0.16
Very Good	0.72	[0.58-0.89]	<0.01
Excellent	0.54	[0.40-0.72]	<0.01
Family Income
$0 to $34,999	Ref	-	-
$35,000 to $49,999	1.03	[0.86-1.25]	0.73
$50,000 to $74,999	1.00	[0.85-1.19]	0.97
$75,000 to $99,999	0.93	[0.76-1.13]	0.45
$100,000 or greater	0.99	[0.83-1.16]	0.86
Health Coverage
No	Ref	-	-
Yes	3.75	[1.63-8.6]	<0.01
Urbanization level of residence
Non-metropolitan	Ref	-	-
Medium and small metropolitan	1.01	[0.84-1.21]	0.92
Large fringe metropolitan	1.19	[0.99-1.44]	0.06
Large central metropolitan	1.39	[1.16-1.67]	<0.01
Two-Way interaction between Currently receiving treatment for cancer and Cancer type was statistically significant (Pint= <0.01)

Table3 Marginal mean predicted probability of receiving virtual visits with the adjusted risk difference between those Not currently receiving treatment for cancer and for those currently receiving treatment for cancer for each cancer Type
	Currently receiving treatment for cancer
	No	Yes
	MPPa [95% CI]	MPPa [95% CI]	ARDb [95% CI]	P>t
Cancer Type
Breast cancer	0.35[0.29-0.42]	0.34[0.17-0.50]	-0.02[-0.21-0.17]	0.85
Colorectal cancer	0.43[0.26-0.59]	0.68[0.36-0.99]	0.24[-0.10-0.59]	0.17
Cervical/Ovarian/Uterine cancer	0.45[0.37-0.54]	0.60[0.33-0.87]	0.14[-0.14-0.42]	0.33
Lung cancer	0.36[0.19-0.52]	0.67[0.40-0.94]	0.35[0.002-0.70]	0.05
Lymphoma cancer	0.48[0.29-0.67]	0.80[0.53-1.07]	0.32[0.001-0.64]	0.05
Thyroid cancer	0.66[0.50-0.81]	0.48[0.27-0.70]	-0.18[-0.41-0.06]	0.14
Skin cancer (including Melanoma)	0.38[0.34-0.43]	0.59[0.45-0.73]	0.20[0.07-0.33]	<0.01
Prostate cancer	0.46[0.36-0.56]	0.64[0.49-0.80]	0.18[0.01-0.35]	0.04
Other or multiple cancers	0.47[0.42-0.53]	0.51[0.42-0.60]	0.04[-0.07-0.14]	0.50
a Mean Predicted Probability b Adjusted Risk difference

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