Association Between Telemedicine Use and Outpatient Visits Among Hypertensive Patients With Disabilities During COVID-19

Abstract

Background

The Korean government allowed for the temporary provision of non-face-to-face healthcare services (telemedicine) from 24 February 2020, due to the widespread outbreak of coronavirus disease 2019 (COVID-19). To provide further evidence to inform and support future policies on telemedicine, we compared its utilization rates for hypertension (HTN) treatments both before and during the COVID-19 pandemic.

Methods

This quasi-experimental study utilized 2019–2020 claims data from the Korean National Health Insurance Service to evaluate the numbers of outpatient visits for HTN by patients with disabilities in that period. Multivariable regression and difference-in-difference (DID) analyses were then conducted to compare the use of outpatient and telemedicine services due to HTN during the COVID-19 pandemic.

Results

Among patients with disabilities and also HTN identified in 2019, 9,254 accessed telemedicine appointments in 2020 compared to 635,959 cases in the control group. After 1:1 propensity score matching (PSM), the telemedicine and control patient groups each comprised 9,170 patients. Upon adjusting for other variables, the number of outpatient visits decreased by 0.57 cases in the telemedicine group compared to that in the control group. After 1:1 PSM, this decrease was 0.30 cases. DID analysis revealed that the number of outpatient visits in the telemedicine group had decreased by 0.9 cases compared to the control group, which was a higher decrease at 1.0 cases after PSM.

Conclusions

Telemedicine services are a viable alternative mode of healthcare delivery for patients with limited access to in-person care, particularly during epidemics and pandemics.

Keywords

non-face-to-face treatment telemedicine telehealth COVID-19 people with disabilities

1. Background

Since the legalization of telemedicine in the form of remote consultations between healthcare professionals and patients in South Korea in 2002, various discussions regarding its application have been carried out. Non-face-to-face treatments were implemented initially as a pilot scheme only for specific groups such as sailors, island residents, or prisoners, due to safety and efficacy concerns. They were not therefore available more generally and their wider clinical benefits thus remained unknown, especially within the National Health Insurance system in South Korea.¹

As in many other countries, coronavirus disease 2019 (COVID-19) began to spread in South Korea from about January 2020, and the World Health Organization declared it a pandemic in March 2020.² As the risk of COVID-19 infection in hospitals increased, the South Korean government began to allow phone-based medical appointments on a temporary basis for the entire population, including the use of remote prescriptions, from late February 2020, in accordance with Korea’s Infectious Disease Control and Prevention Act.³ As of January 2021, 35.2 million patients had received telemedicine care in South Korea. A prior analysis of the top five diseases treated remotely from February 2020 to March 2022 ranked essential (primary) hypertension (HTN) first, accounting for 19% of appointments, followed by type 2 diabetes, lipoprotein metabolism disorder, and acute bronchitis related to COVID-19.⁴ Although COVID-19 incidence has reduced since the end of the pandemic, interest in the future direction of telemedicine is increasing and various discussions are underway regarding its advantages and disadvantages.

Due to the spread of COVID-19, in-person services at welfare centers and public health centers for patients were suspended and replaced with remote appointments.^5,6 According to prior research, non-face-to-face chronic disease management programs showed statistically significant effectiveness in the management of blood pressure and sugar levels and have also led to a decrease in mild depression.⁶ Additionally, telemedicine alternatives for people with disabilities during COVID-19 have been evaluated⁵ but research on the current status of non-face-to-face medical services for patients with disabilities is lacking.

The number of patients with disabilities in South Korea has been increasing and was recorded as 2,645,000 people in 2021.⁷ Patients with disabilities are known to have a greater need for medical care and more limited access to health services than the rest of the population.^8-10 In a previous national survey from the United States, 39.8% of people with disabilities reported using telehealth services during the COVID-19 pandemic.¹¹ Considering that patients with disabilities in South Korea have low access to medical care, it has been discussed previously that telemedicine may be beneficial to this population.^8-10 However, people with disabilities also face challenges in accessing healthcare in this manner. Those with visual or hearing impairments may encounter difficulties in using technology, whereas people with cognitive impairments may require additional support to use telemedicine.¹² Hence, it is necessary to evaluate the current status of non-face-to-face treatments among people with disabilities. This quasi-experimental study observed the impacts of telemedicine care among patients with both disabilities and HTN.

2. Methods

2.1. Data Collection and Study Population

The healthcare system in South Korea covers all resident citizens through both the National Health Insurance Service ([NHIS] social insurance) and Medical Aid (public assistance). The records of all medical treatment claims are maintained by the NHIS and contain information on eligibility for health insurance (including sex, age, place of residence, insurance premium quantiles, and disability status).¹³ The NHIS also provides researchers with customized databases that are specifically designed for their fields of study, including the selection of diseases and calendar years to which patient treatment information applies.¹⁴

In this present quasi-experimental observation study, claims data from the NHIS from 2019 to 2020 were used. The study subjects were identified from a NHIS dataset that included a total of 2,711,941 individuals with disabilities. Disability was defined using a disability grade or type based on the eligibility of the claims data recorded in 2019. Among the 645,213 patients who received medical services for HTN (International Classification of Disease 10^th revision [ICD-10] codes I10–I14) as the main illness in 2019, 9,254 received telemedicine treatments for HTN in 2020. Only subjects aged ≥30 years included in this study, considering the nature of the disease. The case group included patients who used telemedicine services during the COVID-19 pandemic in 2020, whereas the control group comprised patients who used only face-to-face treatment the same period.

The codes for the telephone consultation management fee during telemedicine appointments were identified in the claims data from March to December 2020 as follows: AH114 (first medical consultation) and AH214 (return medical consultation). The number of outpatient cases prior to the pandemic was observed between March and December 2019 (10 months), and the observation period for telemedicine treatments due to COVID-19 was between March and December 2020 (10 months). The rates of outpatient service use before and during the COVID-19 pandemic were then compared. The period from January to February 2020, when the COVID-19 pandemic began, was excluded from the observation period. In the present study design also, the outpatient visit rate was defined based on the number of outpatient visits per patient during the observation period.

2.2. Statistical Analysis

Multivariable regression and difference-in-difference (DID) analysis, which included repeated measures analysis of variance, were conducted to compare the differences in the rates of outpatient service use for HTN as the main illness prior to and during the COVID-19 pandemic between the non-face-to-face treatment group and control groups. The adjustment variables included sex (male or female), age (continuous, aged 30 years or older), medical aid status (recipient or non-recipient), disability type (physical, brain lesions, sensory, intellectual/autistic, renal, or others), disability severity (mild or severe), place of residence (metropolitan area: Seoul, Gyeonggi, or a metropolitan city; non-metropolitan area: other regions), and Charlson comorbidity index (CCI) score (0, 1, 2, or ≥3 points). Additionally, we performed propensity score matching (PSM) to match the patient and control groups at a 1:1 ratio, using the same adjustment variables as the matching covariates. SAS enterprise guide tool, version 7.1, provided by the NHIS, was used for statistical analysis.

2.3. Ethical Approval

This study was approved by the Kyung Hee University Institutional Review Board (IRB no. KHSIRB-21-397 [EA]) as a review-exempt study because it followed the South Korean guidelines for de-identification of personal data.

3. Results

Patients aged ≥30 years who received medical services for HTN as the main illness in 2019 were selected and divided into a non-face-to-face treatment group (9,254 patients) and control group (face-to-face treatment) (635,959 patients) according to the use of telemedicine services in 2020 (Figure 1). Among these cases, 9,170 patients were matched 1:1 with controls using PSM, excluding patients who were not matched (Table 1). When comparing the number of outpatient visits for HTN before and during the COVID-19 pandemic, and after adjusting for other variables, being in the non-face-to-face treatment group was estimated to decreased outpatient visits by 0.57 compared to the control group. After PSM at 1:1, the estimated decrease was 0.30 outpatient visits in the non-face-to-face treatment group compared to the control group (Table 2).

Table 1.

Baseline Characteristics of the Study Subjects

	Original					Propensity score matching* (1:1)
	Case	(%)	Control	(%)	P-value	Case	(%)	Control	(%)	P-value
Total	9,254	100·0	635,959	100·0		9,170	100.0	9,170	100.0
Age group (years)					<.001					>.99
30–39	73	0.8	5,260	0.8		65	0.7	65	0.7
40–49	439	4.7	26,473	4.2		416	4.5	416	4.5
50–59	1,480	16.0	91,948	14.5		1,467	16.0	1,467	16.0
60–69	2,288	24.7	163,548	25.7		2,278	24.8	2,278	24.8
70–79	2,562	27.7	205,761	32.4		2,554	27.9	2,554	27.9
80+	2,412	26.1	142,969	22.5		2,390	26.1	2,390	26.1
Age Continuous	70.0	±12.3	69.0	±11.6	.24	70.1	±12.2	70.1	±12.2	>.99
Mean ± SD
Sex					<.001					>.99
Male	4,279	46.2	323,319	50.8		4,243	46.3	4,243	46.3
Female	4,975	53.8	312,640	49.2		4,927	53.7	4,927	53.7
Medical Aid					<.001					>.99
Recipient	1,196	12.9	86,952	13.7		1,148	12.5	1,148	12.5
Non-recipient	8,058	87.1	549,007	86.3		8,022	87.5	8,022	87.5
Disability type					<.001					>.99
Physical	5,590	60.4	367,631	57.8		5,585	60.9	5,585	60.9
Brain lesions	611	6.6	40,117	6.3		597	6.5	597	6.5
Sensory	2,669	28.8	189,289	29.8		2,640	28.8	2,640	28.8
Intellectual/Autistic	142	1.5	14,308	2.2		255	2.8	255	2.8
Renal	5	0.1	4,378	0.7		3	0.0	3	0.0
Others†	237	2.6	20,236	3.2		90	1.0	90	1.0
Disability severity
Mild	6,951	75.1	482,397	75.9		6,913	75.4	6,913	75.4
Severe	2,303	24.9	153,562	24.1		2,257	24.6	2,257	24.6
Region					<.001					>.99
Metropolitan area	6,152	66.5	373,472	58.7		6,098	66.5	6,098	66.5
Non-metropolitan area	3,102	33.5	262,487	41.3		3,072	33.5	3,072	33.5
Charlson comorbidity index (CCI) score					<.001
0	1,223	13.2	89,793	14.1		1,208	13.2	1,208	13.2
1	1,892	20.4	124,890	19.6		1,869	20.4	1,869	20.4
2	2,001	21.6	124,287	19.5		1,980	21.6	1,980	21.6
≥3	4,138	44.7	296,989	46.7		4,113	44.9	4,113	44.9
Continuous	2.63	±2.1	2.74	±2.2	<.001	2.64	±2.6	2.70	±2.6	.074
Mean ± SD

*The variables used for propensity score matching were sex (male or female), age (continuous), medical aid status (recipient or non-recipient), disability type (physical, brain lesions, sensory, intellectual/autistic, renal, or others), disability severity (mild or severe), place of residence (metropolitan area: Seoul, Gyeonggi, or a metropolitan city; non-metropolitan area: other regions), and CCI score (0, 1, 2, or ≥3 points).

†Other types included speech-language disorder, psychiatric disability, facial disorder, epilepsy, and internal organ impairments (heart, liver, respiratory, intestinal, and urinary organs).

SD, standard deviation.

Table 2.

Multiple Regression Analysis of the Difference in the Number of Outpatient Visits for Hypertension (HTN) Between the Non-face-to-face Treatment and Control Groups

Variables (Ref)	Original data			Propensity score matching* 1:1
Variables (Ref)	Coefficient	Standard error	P-value	Coefficient	Standard error	P-value
Non-face-to-face treatment group for hypertension in 2020 (Control)	0.575	0.0341	<.001	0.301	0.0472	<.001
Sex (male)	-0.081	0.0087	<.001	-0.081	0.0517	.12
Age (continuous)	-0.001	0.0004	.066	0.002	0.0022	.396
Disability type (physical)	0.018	0.0020	<.001	0.033	0.0129	.009
Metropolitan area status (metropolitan area)	-0.111	0.0084	<.001	0.067	0.0497	.176
Medical aid status (recipient)	0.150	0.0123	<.001	0.279	0.0718	<.001
Charlson comorbidity index (CCI) score (continuous)	0.168	0.0038	<.001	-0.003	0.0221	.903
Number of outpatient visits for hypertension in 2019 (prior to COVID-19) (continuous)	0.330	0.0001	<.001	0.461	0.0472	<.001

3.1. Difference-In-Difference Analysis

The results of difference-in-difference (DID) analysis indicated that, prior to PSM, the number of outpatient visits decreased more in the non-face-to-face group (DID=0.9 visits) between the periods before and during the COVID-19 pandemic. In addition, after 1:1 PSM, the number significantly decreased by 1.0 cases (P<.001). The total number of outpatient visits, including telemedicine appointments, was significantly higher in the non-face-to-face group than in the control group by 1.0 cases and by 0.9 cases after PSM (P<.001) (Table 3).

Table 3.

Difference-In-Differences (DID) Analysis Results of the Number of Outpatient Visits for Hypertension (HTN) in the Non-face-to-face Treatment and the Control Groups

	Excluding non-face-to-face treatment count								Including non-face-to-face treatment count
	Original				Propensity score matching^* 1:1				Original				Propensity score matching^* 1:1
	Before COVID-19 pandemic	During COVID-19 pandemic	Difference	P-value	Before COVID-19 pandemic	During COVID-19 pandemic	Difference	P-value	Before COVID-19 pandemic	During COVID-19 pandemic	Difference	P-value	Before COVID-19 pandemic	During COVID-19 pandemic	Difference	P-value
Non-face-to-face group	7.7	6.1	1.6		7.7	6.1	1.6		7.7	8.0	-0.3		7.7	8.0	-0.3
Control group	6.4	5.7	0.7		6.3	5.7	0.6		6.4	5.7	0.7		6.3	5.7	0.6
DID			0.9	<.001			1.0	<.001			-1.0	<.001			-0.9	<.001

4. Discussion

Telemedicine is believed to help address the inconveniences associated with face-to-face medical services. In addition, non-face-to-face medical services can benefit patients with disabilities, such as reduced transportation costs and improved access to medical experts.¹⁵ Compared with the general population, patients with disabilities are known to have difficulty accessing medical care, and this has been frequently documented in the literature.^8-10 The provision of telemedicine treatment to groups with limited access to healthcare is considered one of the viable options for addressing the difficulties in access to healthcare services but is an approach that remains controversial due to patient safety concerns. This study empirically evaluated the impact of telemedicine on medical care use among patients with disabilities via a quasi-experimental analysis that compared non-face-to-face and face-to-face treatment groups across the Korean disability population.

Our present analyses indicated that the number of outpatient visits due to HTN decreased by 0.57 cases in the non-face-to-face treatment group compared to the control group. Further to this, after PSM, the number of visits decreased by 0.3 cases, and the DID analysis results also indicated a decrease in the number of outpatient visits in the non-face-to-face treatment group (by 1.0 cases). Considering that patients with disabilities often face barriers to healthcare access, telemedicine appointments may represent a solution to limited in-person care options. Although the absolute reduction in outpatient visits per individual was modest, these changes may still be meaningful at the population level.

A previous study of the effectiveness of the temporary non-face-to-face treatment (including telephone consultation/prescription) policy implemented by the Health Insurance Review and Assessment (HIRA) service in South Korea reported that HTN ranked first among the diseases treated remotely, followed by diabetes. That report further found that the rate of outpatient visits in the group using telephone for remote prescription for HTN increased by 0.07 cases in the general population, showing statistical significance but no substantial numerical difference.¹⁶ No difference was observed in the number of outpatient visits in the >60-year age group, even in the DID analysis, because the entire population was targeted, and the impact on each age group was not sufficiently evaluated.¹⁶ Moreover, the interim results showed an increase in medical care use but it was difficult to determine whether medical needs were met or whether unnecessary use of medical care had increased.¹⁶ Meanwhile, our present study examined the total number of outpatient visits, including telemedicine consultations, received by patients with disabilities, with the rate being higher in the non-face-to-face treatment group, suggesting that a portion of the in-person visits may have been replaced by telemedicine consultations. Hence, the availability of non-face-to-face treatment was associated with lower use of in-person medical care, showing that some outpatient care may have been delivered through telemedicine services to patients with disabilities.

The main argument in favor of telemedicine in South Korea is improved medical accessibility. Countries with large territories, such as the United States, Australia, and Canada, have introduced telemedicine to improve medical accessibility in outlying and rural areas and to address the issue of medical expert shortage. In a previous study in South Korea, the effectiveness of non-face-to-face treatment was found to be limited in terms of healthcare accessibility due to differences in land area.¹⁷ However, individuals with disabilities often face other barriers to accessing healthcare, and our present findings suggest that telemedicine may be particularly relevant for this population.¹¹ Furthermore, when both telemedicine and in-person treatments were included in this study, the total number of outpatient treatments was in fact found to be higher in the non-face-to-face treatment group, suggesting that healthcare utilization may have been maintained even when access to care was limited. This finding is consistent with a previous study suggesting that telehealth improved access to care during the COVID-19 pandemic.¹⁸

Compared with face-to-face treatments, telemedicine, which includes non-face-to-face care, can also potentially reduce the use of limited medical resources by reducing the time required for both medical appointments and also the length of hospitalization and outpatient visits. However, specific safety concerns with regard to telemedicine, such as the risk of misdiagnosis or medical accidents by healthcare professionals, the reliability of information and communication technologies, and a lack of familiarity with digital technology among specific patient groups have been topics of discussion.^1,17 Previous studies have also noted that although telemedicine may improve healthcare access for people with disabilities, accessibility and communication barriers still remain among this patient group.¹⁹ Nevertheless, non-face-to-face treatments can have additional advantages in situations where the risk of infection is high, such as during the COVID-19 pandemic.¹⁷

In a previous survey of satisfaction with telemedicine among participating patients and medical staff at a general hospital in South Korea, the patients were found to have high levels of satisfaction with convenience (79.9%), mutual communication (87.1%), and reliability (87.1%) and there was a high willingness to reuse telemedicine (85.1%). However, the medical staff had low levels of satisfaction for convenience at 33% and mutual communication at 8.4%, and low willingness to reuse at 35.5%. Nonetheless, staff responses indicated that telemedicine was necessary in an emergency such as COVID-19, and listed advantages that included convenience for the patients (53%) and infection prevention (22%). In other words, patients showed high satisfaction regarding convenience and infection prevention, while concerns about safety among medical staff seemed to lead to lower satisfaction in this regard.²⁰ These results are similar to those of another satisfaction survey involving medical staff conducted by the HIRA. Telemedicine was found in that assessment to be convenient for the medical staff, but they felt uneasy due to medical safety concerns. These clinical practitioners also mentioned that patients with chronic diseases such as HTN and diabetes can be a target group for non-face-to-face treatment.²¹

The findings of this present study suggest that telemedicine may offer certain advantages for individuals with limited access to healthcare, particularly during public health emergencies such as epidemics and pandemics. The present evidence therefore further informs discussions regarding the implementation of non-face-to-face treatment approaches in South Korea. In December 2025, legislation related to telemedicine was amended in South Korea, although the details of its implementation remain under discussion. Meanwhile, according to another study, individuals with intellectual and developmental disabilities (IDD) used telemedicine 56% more often during the COVID-19 pandemic than those without IDD, with about 70% of these appointments used for behavioral health. This further highlights the potential role of telemedicine in improving mental health access for people with IDD.²²

Our current study included the entire disability population in South Korea and revealed that telemedicine use may differ by disability type. While individuals with IDD benefit from improved mental health support, those with physical disabilities may find reduced transportation barriers more significant. The study subjects were not classified by disability type however and it is possible that telemedicine use patterns may vary depending on this. It is almost certain that telemedicine services should be tailored to the specific needs of each disability group to more effectively enhance healthcare accessibility.

5. Limitations and Strength

This study had some limitations of note. The period of the data analysis was too short to identify the long-term health outcomes of non-face-to-face medical care. The findings should be interpreted therefore as sort-term outcomes. Similarly, the equivalence and quality of telemedicine and in-person treatments, including clinical outcomes such as blood pressure control, may not be guaranteed, and this aspect requires further research. Residual confounding may also have remained despite PSM, and the assumptions underlying the DID analysis should be considered when interpreting the findings. In addition, subgroup analyses according to disability type were not performed, and further studies are needed in this regard. Despite these limitations, to our knowledge, this study is the first to measure the impact of non-face-to-face treatment on outpatient care for patients with disabilities.

6. Conclusions

The institutionalization of telemedicine as a form of medical service delivery may be essential for dealing with future pandemics, considering the unmet needs of patients with limited access to medical care, such as those with disabilities. Furthermore, health inequalities within the population could be exacerbated if the needs of people with disabilities are not considered in the policymaking process. Therefore, the findings of this present study can help to inform future policy discussions on non-face-to-face treatment.

Footnotes

ORCID iDs

Rugyeom Lee

Joon Lee

Ethical Considerations

This study was approved by the Kyung Hee University Institutional Review Board (IRB no. KHSIRB-21-397 [EA]) as a review-exempt study because it follows the South Korean guidelines for de-identifying personal data.

Author Contributions

IHO conceptualized the study, developed the methodology, and supervised the research. RL curated and interpreted the data, conducted formal analysis, and was a major contributor in writing the manuscript. JL contributed to the methodology and participated in reviewing and editing the manuscript. MWJ interpreted the data, validated the research and was involved in reviewing the manuscript. All authors read and approved the final manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI21C2122).

Declaration of Conflicting Interests

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

Data Availability Statement

The data that support the findings of this study are available from the National Health Insurance Service (NHIS) of South Korea. However, the data were used after approval for the current study and are therefore not publicly available. Access to the data is no longer available to the authors because the data usage period has expired, although researchers may apply for access through the NHIS data sharing service. *

Appendix

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