Improving telehealth accessibility assessment with a demographics-weighted two-step virtual catchment area (DW-2SVCA) method

Yunsik Kim , Youngseob Eum

Computational Urban Science ›› 2025, Vol. 5 ›› Issue (1) : 59

PDF
Computational Urban Science ›› 2025, Vol. 5 ›› Issue (1) :59 DOI: 10.1007/s43762-025-00218-5
Original Paper
research-article

Improving telehealth accessibility assessment with a demographics-weighted two-step virtual catchment area (DW-2SVCA) method

Author information +
History +
PDF

Abstract

The use of telehealth has significantly increased in recent years, providing patients with remote access to healthcare services. To measure accessibility of telehealth services, two-step virtual catchment area (2SVCA) methods have been developed as a broadband-aware extension of the traditional two-step floating catchment area (2SFCA) framework. Although telehealth utilization varies across demographic groups, existing 2SVCA approaches do not account for such variation and typically treat population demand as uniform. To address the knowledge gap, this study proposes the demographic-weighted 2SVCA (DW-2SVCA), which enhances the 2SVCA framework by adjusting telehealth demand through a weight matrix based on demographic characteristics, including age, gender, race, and ethnicity. In a case study of primary healthcare in Mecklenburg County, North Carolina, we applied the proposed method to measure telehealth accessibility and compared it with the existing 2SVCA approach. While the overall statistical and spatial patterns were similar, DW-2SVCA exhibited greater variance in accessibility values. To further evaluate whether the proposed method more effectively captures demographic variations in telehealth utilization, we classified the study area into four groups based on demographic profiles by using hierarchical clustering and conducted statistical tests. The results revealed that the DW-2SVCA method indicates more pronounced and statistically significant differences, with higher accessibility in regions characterized by white and middle-aged populations and lower accessibility in more racially/ethnically diverse areas. This study offers a more comprehensive tool for evaluating telehealth accessibility, highlighting the importance of incorporating demographic variations in telehealth utilization.

Keywords

Telehealth / Spatial accessibility / Two-step virtual catchment area / DW-2SVCA / Demographics

Cite this article

Download citation ▾
Yunsik Kim, Youngseob Eum. Improving telehealth accessibility assessment with a demographics-weighted two-step virtual catchment area (DW-2SVCA) method. Computational Urban Science, 2025, 5(1): 59 DOI:10.1007/s43762-025-00218-5

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Alford-Teaster J, Wang F, Tosteson ANA, Onega T. Incorporating broadband durability in measuring geographic access to health care in the era of telehealth: A case example of the 2-step virtual catchment area (2SVCA) method. Journal of the American Medical Informatics Association, 2021, 28(11): 2526-2530

[2]

Center for Medicare & Medicaid Services. (2024). Medicare telehealth trends report. https://data.cms.gov/sites/default/files/2024-12/f5b35fbf-002a-425d-924d-f99aa362a63f/Medicare%20Telehealth%20Trends%20Snapshot%2020241127_508.pdf

[3]

Dai D. Black residential segregation, disparities in spatial access to health care facilities, and late-stage breast cancer diagnosis in metropolitan Detroit. Health & Place, 2010, 16(5): 1038-1052

[4]

Dai D, Wang F. Geographic disparities in accessibility to food stores in southwest Mississippi. Environment and Planning b: Planning & Design, 2011, 38(4): 659-677

[5]

Delamater PL. Spatial accessibility in suboptimally configured health care systems: A modified two-step floating catchment area (M2SFCA) metric. Health & Place, 2013, 24: 30-43

[6]

Dunn OJ. Multiple comparisons using rank sums. Technometrics, 1964, 6(3): 241-252

[7]

Eberly, L. A., Kallan, M. J., Julien, H. M., Haynes, N., Khatana, S. A. M., Nathan, A. S., Snider, C., Chokshi, N. P., Eneanya, N. D., Takvorian, S. U., Anastos-Wallen, R., Chaiyachati, K., Ambrose, M., O’quinn, R., Seigerman, M., Goldberg, L. R., Leri, D., Choi, K., Gitelman, Y., & Adusumalli, S. (2020). Patient characteristics associated with telemedicine access for primary and specialty ambulatory care during the COVID-19 pandemic. JAMA Network Open,3(12), e2031640. https://doi.org/10.1001/jamanetworkopen.2020.31640

[8]

Federal Communications Commission. (2024). FCC increases broadband speed benchmark. https://www.fcc.gov/document/fcc-increases-broadband-speed-benchmark

[9]

Ko JS, El-Toukhy S, Quintero SM, Wilkerson MJ, Nápoles AM, Stewart AL, Strassle PD. Disparities in telehealth access, not willingness to use services, likely explain rural telehealth disparities. The Journal of Rural Health, 2023, 39(3): 617-624

[10]

Kruskal WH, Wallis WA. Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 1952, 47(260): 583-621

[11]

Langford M, Higgs G, Fry R. Multi-modal two-step floating catchment area analysis of primary health care accessibility. Health & Place, 2016, 38: 70-81

[12]

Lee, E. C., Grigorescu, V., Enogieru, I., Smith, S. R., Samson, L. W., Conmy, A., De Lew, N. (2023). Updated national survey trends in telehealth utilization and modality: 2021–2022 (Issue Brief No. HP-2023–09). Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services. https://aspe.hhs.gov/sites/default/files/documents/7d6b4989431f4c70144f209622975116/household-pulse-survey-telehealth-covid-ib.pdf

[13]

Lima JP, Abitante JDC, Pons NAD, Senne CM. A spatial fuzzy multicriteria analysis of accessibility: A case study in Brazil. Sustainability, 2019, 11(12): 3407

[14]

Liu, L., Alford-Teaster, J., Onega, T., & Wang, F. (2023). Refining 2SVCA method for measuring telehealth accessibility of primary care physicians in Baton Rouge, Louisiana. Cities,138, 104364. https://doi.org/10.1016/j.cities.2023.104364

[15]

Liu, L., Gao, R., & Zhang, L. (2024). An equity evaluation of healthcare accessibility across age strata using the G2SFCA method: A case study in Karamay District, China. Land, 13(8), 1259. https://doi.org/10.3390/land13081259

[16]

Lucas, J. W., Villarroel, M. A. (2022). Telemedicine use among adults: United States, 2021 (NCHS Data Brief No. 445). National Center for Health Statistics, U.S. Center for Disease Control and Prevention. https://doi.org/10.15620/cdc:121435

[17]

Luo W, Qi Y. An enhanced two-step floating catchment area (E2SFCA) method for measuring spatial accessibility to primary care physicians. Health & Place, 2009, 15(41100-1107

[18]

Luo W, Wang F. Measures of spatial accessibility to health care in a GIS environment: Synthesis and a case study in the Chicago region. Environment and Planning b: Urban Analytics and City Science, 2003, 30(6): 865-884

[19]

Lythreatis, S., Singh, S. K., & El-Kassar, A. N. (2022). The digital divide: A review and future research agenda. Technological Forecasting and Social Change,175, 121359. https://doi.org/10.1016/j.techfore.2021.121359

[20]

Marshall, J., Blavin, F., O’Brien, C., Parekh, A., & Smith, L. B. (2024). Patient characteristics associated with frequent telehealth utilization in 2022: Evaluation of a national virtual integrated medical and behavioral health practice within the United States. Preventive Medicine Reports,46, 102871. https://doi.org/10.1016/j.pmedr.2024.102871

[21]

Mehrotra A, Uscher-Pines L. Informing the debate about telemedicine reimbursement—What do we need to know?. New England Journal of Medicine, 2022, 387(20): 1821-1823

[22]

Ng BP, Park C, Silverman CL, Eckhoff DO, Guest JC, Díaz DA. Accessibility and utilisation of telehealth services among older adults during COVID-19 pandemic in the United States. Health & Social Care in the Community, 2022, 30(5): e2657-e2669

[23]

Reddy, B. P., O’Neill, S., & O’Neill, C. (2022). Explaining spatial accessibility to high-quality nursing home care in the US using machine learning. Spatial and Spatio-Temporal Epidemiology,41, 100503. https://doi.org/10.1016/j.sste.2022.100503

[24]

Rousseeuw PJ. Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 1987, 20: 53-65

[25]

Shao, Y., & Luo, W. (2022). Supply-demand adjusted two-steps floating catchment area (SDA-2SFCA) model for measuring spatial access to health care. Social Science & Medicine,296, 114727. https://doi.org/10.1016/j.socscimed.2022.114727

[26]

Shao Y, Luo W. Enhanced two-step virtual catchment area (E2SVCA) model to measure telehealth accessibility. Computational Urban Science, 2023, 3(1): 16

[27]

Soares N, Dewalle J, Marsh B. Utilizing patient geographic information system data to plan telemedicine service locations. Journal of the American Medical Informatics Association, 2017, 24(5891-896

[28]

Tao Z, Cheng Y, Liu J. Hierarchical two-step floating catchment area (2SFCA) method: Measuring the spatial accessibility to hierarchical healthcare facilities in Shenzhen, China. International Journal for Equity in Health, 2020, 19(1): 164

[29]

Tao Z, Yao Z, Kong H, Duan F, Li G. Spatial accessibility to healthcare services in Shenzhen, China: Improving the multi-modal two-step floating catchment area method by estimating travel time via online map APIs. BMC Health Services Research, 2018, 18: 345

[30]

Tilhou, A. S., Jain, A., & DeLeire, T. (2024). Telehealth expansion, internet speed, and primary care access before and during COVID-19. JAMA Network Open,7(1), e2347686. https://doi.org/10.1001/jamanetworkopen.2023.47686

[31]

Wang F. Measurement, optimization, and impact of health care accessibility: A methodological review. Annals of the Association of American Geographers, 2012, 102(51104-1112

[32]

Wang F, Xu Y. Estimating o-d travel time matrix by Google Maps API: Implementation, advantages, and implications. Annals of GIS, 2011, 17: 199-209

[33]

Wang, F., Zeng, Y., Liu, L., & Onega, T. (2023). Disparities in spatial accessibility of primary care in Louisiana: From physical to virtual accessibility. Frontiers in Public Health, 11. https://doi.org/10.3389/fpubh.2023.1154574

[34]

Ward JH. Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 1963, 58: 236-244

[35]

Wosik J, Fudim M, Cameron B, Gellad ZF, Cho A, Phinney D, Curtis S, Roman M, Poon EG, Ferranti J, Katz JN, Tcheng J. Telehealth transformation: COVID-19 and the rise of virtual care. Journal of the American Medical Informatics Association, 2020, 27(6957-962

[36]

Yang T, Luo W, Tian L, Li J. Integrating spatial and non-spatial dimensions to evaluate access to rural primary healthcare service: A case study of Songzi. China. ISPRS International Journal of Geo-Information, 2024, 13(5): 142

[37]

Zhang S, Song X, Zhou J. An equity and efficiency integrated grid-to-level 2SFCA approach: Spatial accessibility of multilevel healthcare. International Journal for Equity in Health, 2021, 20(11-14

RIGHTS & PERMISSIONS

The Author(s)

AI Summary AI Mindmap
PDF

12

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/