Use of and Satisfaction with Telemedicine Services during the Pandemic: Findings from the COVID-19 Snapshot Monitoring in Germany (COSMO)
Abstract
:1. Introduction
2. Materials and Methods
2.1. Sample
2.2. Dependent Variables
2.3. Independent Variables
2.4. Statistical Analysis
3. Results
3.1. Sample Characteristics
3.2. Regression Analysis
4. Discussion
4.1. Main Findings
4.2. Previous Research and Possible Explanations
4.3. Strengths and Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Hyder, M.A.; Razzak, J. Telemedicine in the United States: An Introduction for Students and Residents. J. Med. Internet Res. 2020, 22, e20839. [Google Scholar] [CrossRef]
- Zaresani, A.; Scott, A. Does digital health technology improve physicians’ job satisfaction and work-life balance? A cross-sectional national survey and regression analysis using an instrumental variable. BMJ Open 2020, 10, e041690. [Google Scholar] [CrossRef]
- Elsner, P. Teledermatology in the times of COVID-19—a systematic review. J. Dtsch. Derm. Ges. 2020, 18, 841–845. [Google Scholar] [CrossRef]
- Kayser, M.Z.; Valtin, C.; Greer, M.; Karow, B.; Fuge, J.; Gottlieb, J. Video Consultation During the COVID-19 Pandemic: A Single Center’s Experience with Lung Transplant Recipients. Telemed. J. e-Health 2020. [Google Scholar] [CrossRef] [PubMed]
- Garfan, S.; Alamoodi, A.H.; Zaidan, B.B.; Al-Zobbi, M.; Hamid, R.A.; Alwan, J.K.; Ahmaro, I.Y.Y.; Khalid, E.T.; Jumaah, F.M.; Albahri, O.S.; et al. Telehealth utilization during the Covid-19 pandemic: A systematic review. Comput. Biol. Med. 2021, 138, 104878. [Google Scholar] [CrossRef] [PubMed]
- Bundesvereinigung, K. Immer Mehr Praxen Greifen Zur Kamera—Zahl der Videosprechstunden auf über Eine Million Gestiegen. Available online: https://www.kbv.de/html/1150_50419.php (accessed on 26 November 2021).
- Reitzle, L.; Schmidt, C.; Färber, F.; Huebl, L.; Wieler, L.H.; Ziese, T.; Heidemann, C. Perceived Access to Health Care Services and Relevance of Telemedicine during the COVID-19 Pandemic in Germany. Int. J. Environ. Res. Public Health 2021, 18, 7661. [Google Scholar] [CrossRef] [PubMed]
- Osterloh, F. Coronavirus: Krankenhäuser verschieben planbare Eingriffe. Dtsch. Arztebl. 2020, 117, A575–A577. [Google Scholar]
- Hajek, A.; De Bock, F.; Huebl, L.; Kretzler, B.; König, H.-H. Determinants of Postponed Cancer Screening During the COVID-19 Pandemic: Evidence from the Nationally Representative COVID-19 Snapshot Monitoring in Germany (COSMO). Risk Manag. Healthc. Policy 2021, 14, 3003. [Google Scholar] [CrossRef]
- Hajek, A.; De Bock, F.; Huebl, L.; Kretzler, B.; König, H.-H. Postponed Dental Visits during the COVID-19 Pandemic and their Correlates. Evidence from the Nationally Representative COVID-19 Snapshot Monitoring in Germany (COSMO). Healthcare 2021, 9, 50. [Google Scholar] [CrossRef] [PubMed]
- Hajek, A.; De Bock, F.; Kretzler, B.; König, H.H. Factors associated with postponed health checkups during the COVID-19 pandemic in Germany. Public Health 2021, 194, 36–41. [Google Scholar] [CrossRef]
- Hajek, A.; De Bock, F.; Wieler, L.H.; Sprengholz, P.; Kretzler, B.; König, H.-H. Perceptions of Health Care Use in Germany during the COVID-19 Pandemic. Int. J. Environ. Res. Public Health 2020, 17, 9351. [Google Scholar] [CrossRef]
- Betsch, C.; Wieler, L.H.; Habersaat, K. Monitoring behavioural insights related to COVID-19. Lancet 2020, 395, 1255–1256. [Google Scholar] [CrossRef]
- Münnich, R.; Gabler, S. 2012: Stichprobenoptimierung und Schätzung in Zensus 2011; Statistisches Bundesamt: Wiesbaden, Germany, 2012; Volume 21.
- Welle, K.; Täger, S.; Hackenberg, R.K.; Markowetz, A.; Schildberg, F.A.; Burger, C.; Wirtz, D.C.; Jansen, T.; Kabir, K. Examining the Hand in the Video Consultation. Z. Orthop. Unf. 2021, 159, 202–208. [Google Scholar] [CrossRef]
- Kahlert, S. Critical Factors that Impact ICT/Telemedicine Utilisation in Germany; Charles Sturt University: Bathurst, Australia, 2017. [Google Scholar]
- Ramaswamy, A.; Yu, M.; Drangsholt, S.; Ng, E.; Culligan, P.J.; Schlegel, P.N.; Hu, J.C. Patient Satisfaction With Telemedicine During the COVID-19 Pandemic: Retrospective Cohort Study. J. Med. Internet Res. 2020, 22, e20786. [Google Scholar] [CrossRef] [PubMed]
- Schaurer, I.; Weiß, B. Investigating selection bias of online surveys on coronavirus-related behavioral outcomes. Surv. Res. Methods 2020, 14, 103–108. [Google Scholar]
- Chae, Y.M.; Heon Lee, J.; Hee Ho, S.; Ja Kim, H.; Hong Jun, K.; Uk Won, J. Patient satisfaction with telemedicine in home health services for the elderly. Int. J. Med. Inform. 2001, 61, 167–173. [Google Scholar] [CrossRef]
Variables | Mean (SD)/n (%) |
---|---|
Age group | |
- 18 to 29 years | 200 (20.7%) |
- 30 to 49 years | 364 (37.6%) |
- 50 to 64 years | 251 (26.0%) |
- 65 years and over | 152 (15.7%) |
Gender | |
- Men | 476 (49.2%) |
- Women | 491 (50.8%) |
Migration background | |
- No | 811 (84.7%) |
- Yes | 146 (15.3%) |
Relationship/Marriage | |
- No | 324 (33.5%) |
- Yes | 643 (66.5%) |
Level of education | |
- up to 9 years | 104 (10.8%) |
- 10 years and more (without general qualification for university entrance) | 317 (32.8%) |
- 10 years and more (with general qualification for university entrance) | 546 (56.5%) |
Children under 18 years | |
- No | 654 (67.6%) |
- Yes | 313 (32.4%) |
Profession in health care | |
- No | 886 (91.6%) |
- Yes | 81 (8.4%) |
Community size | |
- ≤5000 inhabitants | 153 (15.8%) |
- 5001–20,000 inhabitants | 228 (23.6%) |
- 20,001–100,000 inhabitants | 248 (25.6%) |
- 100,001–500,000 inhabitants | 173 (17.9%) |
- >500,000 inhabitants | 165 (17.1%) |
Perceived severity: COVID-19 infection (from 1 to 7; higher values correspond to higher severity) | 3.9 (1.5) |
Perceived probability: COVID-19 infection (from 1 = extremely unlikely to 7 = extremely likely) | 3.2 (1.4) |
COVID-19 infection | |
- No | 911 (94.2%) |
- Yes | 56 (5.8%) |
At least one chronic condition | |
- No | 585 (61.9%) |
- Yes | 360 (38.1%) |
Replacement of any physician visits by a telemedicine service since March 2020 because of the corona situation | |
- Yes, once | 46 (4.8%) |
- Yes, several times | 62 (6.4%) |
- Yes, always | 20 (2.1%) |
- No, not replaced | 303 (31.3%) |
- No, there was no need to see a doctor | 536 (55.4%) |
Satisfaction with the corresponding telemedicine services (from 1 = very dissatisfied to 7 = very satisfied) | 4.7 (2.0) |
Independent Variables | Replacement of Physician Visits by Telemedicine Services Since March 2020 Because of the Corona Situation |
---|---|
Age group: - 30 to 49 years (Ref.: 18 to 29 years) | 0.59 |
(0.30–1.13) | |
- 50 to 64 years | 0.50 + |
(0.24–1.06) | |
- 65 years and over | 0.57 |
(0.22–1.46) | |
Gender: Women (Ref.: Men) | 0.93 |
(0.58–1.50) | |
Migration background: Yes (Ref.: No) | 0.75 |
(0.39–1.44) | |
Relationship/Marriage: Yes (Ref.: No) | 1.09 |
(0.64–1.86) | |
Level of education: - 10 years and more (without general qualification for university entrance) (Ref.: up to 9 years) | 0.37 * |
(0.15–0.92) | |
- 10 years and more (with general qualification for university entrance) | 0.85 |
(0.36–1.97) | |
Children under 18 years: Yes (Ref.: No) | 1.98 * |
(1.12–3.50) | |
Profession in health care: Yes (Ref.: No) | 1.33 |
(0.58–3.08) | |
Community size: - 5001–20,000 inhabitants (Ref.: ≤5000 inhabitants) | 1.60 |
(0.69–3.73) | |
- 20,001–100,000 inhabitants | 1.48 |
(0.63–3.44) | |
- 100,001–500,000 inhabitants | 1.95 |
(0.81–4.69) | |
- >500,000 inhabitants | 2.32 + |
(0.96–5.60) | |
Perceived severity: COVID-19 infection (from 1 to 7; higher values correspond to higher severity) | 1.23 * |
(1.03–1.48) | |
Perceived probability: COVID-19 infection (from 1 = extremely unlikely to 7 = extremely likely) | 1.21 + |
(1.00–1.47) | |
COVID-19 infection: Yes (Ref.: No) | 3.58 ** |
(1.47–8.73) | |
At least one chronic condition: Yes (Ref.: No) | 1.25 |
(0.76–2.08) | |
Constant | 0.06 *** |
(0.01–0.27) | |
Observations | 422 |
Pseudo R2 | 0.14 |
Independent Variables | Satisfaction with Telemedicine Services |
---|---|
Age group: - 30 to 49 years (Ref.: 18 to 29 years) | −0.10 |
(0.46) | |
- 50 to 64 years | 0.21 |
(0.61) | |
- 65 years and over | 0.84 |
(0.70) | |
Gender: Women (Ref.: Men) | −0.01 |
(0.41) | |
Migration background: Yes (Ref.: No) | −1.28 ** |
(0.42) | |
Relationship/Marriage: Yes (Ref.: No) | 0.80 |
(0.49) | |
Level of education: - 10 years and more (without general qualification for university entrance) (Ref.: up to 9 years) | −0.06 |
(0.78) | |
- 10 years and more (with general qualification for university entrance) | 0.33 |
(0.73) | |
Children under 18 years: Yes (Ref.: No) | −0.51 |
(0.47) | |
Profession in health care: Yes (Ref.: No) | −0.51 |
(0.52) | |
Community size: - 5001–20,000 inhabitants (Ref.: ≤5000 inhabitants) | 0.37 |
(0.62) | |
- 20,001–100,000 inhabitants | −0.22 |
(0.63) | |
- 100,001–500,000 inhabitants | −0.06 |
(0.66) | |
- >500,000 inhabitants | 0.33 |
(0.61) | |
Perceived severity: COVID-19 infection (from 1 to 7; higher values correspond to higher severity) | 0.36 * |
(0.16) | |
Perceived probability: COVID-19 infection (from 1 = extremely unlikely to 7 = extremely likely) | −0.02 |
(0.13) | |
COVID-19 infection: Yes (Ref.: No) | 0.76 |
(0.47) | |
At least one chronic condition: Yes (Ref.: No) | −0.11 |
(0.42) | |
Constant | 2.86 * |
(1.14) | |
Observations | 124 |
R2 | 0.23 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Hajek, A.; De Bock, F.; Merkel, C.; Kretzler, B.; König, H.-H. Use of and Satisfaction with Telemedicine Services during the Pandemic: Findings from the COVID-19 Snapshot Monitoring in Germany (COSMO). Healthcare 2022, 10, 92. https://doi.org/10.3390/healthcare10010092
Hajek A, De Bock F, Merkel C, Kretzler B, König H-H. Use of and Satisfaction with Telemedicine Services during the Pandemic: Findings from the COVID-19 Snapshot Monitoring in Germany (COSMO). Healthcare. 2022; 10(1):92. https://doi.org/10.3390/healthcare10010092
Chicago/Turabian StyleHajek, André, Freia De Bock, Christina Merkel, Benedikt Kretzler, and Hans-Helmut König. 2022. "Use of and Satisfaction with Telemedicine Services during the Pandemic: Findings from the COVID-19 Snapshot Monitoring in Germany (COSMO)" Healthcare 10, no. 1: 92. https://doi.org/10.3390/healthcare10010092
APA StyleHajek, A., De Bock, F., Merkel, C., Kretzler, B., & König, H. -H. (2022). Use of and Satisfaction with Telemedicine Services during the Pandemic: Findings from the COVID-19 Snapshot Monitoring in Germany (COSMO). Healthcare, 10(1), 92. https://doi.org/10.3390/healthcare10010092