| Literature DB >> 34886204 |
Jelle Keuper1,2, Ronald Batenburg1,3, Robert Verheij1,2, Lilian van Tuyl1.
Abstract
The COVID-19 pandemic has forced general practices to search for possibilities to provide healthcare remotely (e.g., e-health). In this study, the impact of the pandemic on the use of e-health in general practices in the Netherlands was investigated. In addition, the intention of practices to continue using e-health more intensively and differences in the use of e-health between practice types were investigated. For this purpose, web surveys were sent to general practices in April and July 2020. Descriptive data analysis was performed and differences in the use of e-health between practice types were tested using one-way ANOVA. Response rates were 34% (n = 1433) in April and 17% (n = 719) in July. The pandemic invoked an increased use of several (new) e-health applications. A minority of practices indicated the intention to maintain this increased use. In addition, small differences in the use of e-health between the different practice types were found. This study showed that although there was an increased uptake of e-health in Dutch general practice during the COVID-19 pandemic, only a minority of practices intends to maintain this increased use in the future. This may point towards a temporary uptake of digital healthcare delivery rather than accelerated implementation of digital processes.Entities:
Keywords: COVID-19; e-health; general practice
Mesh:
Year: 2021 PMID: 34886204 PMCID: PMC8656482 DOI: 10.3390/ijerph182312479
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1First time use and intensified use of (new) e-health applications, n = 1083 (April 2020).
Figure 2Percentage of practices that used a specific e-health application, n = 732 (July 2020).
Figure 3Percentage of practices that expected continuation of intensified use of specific e-health applications after the pandemic, n = 1083 (April 2020) and n = 718 (July 2020).
Percentage of practices using e-health applications for the first time because of the COVID-19 pandemic, specified by e-health application (mean ± standard deviation), n = 1074 (April 2020).
| E-Health Application | Solo Practice | Duo Practice | Group Practice | |
|---|---|---|---|---|
| E-consultation | 15% ± 0.355 | 12% ± 0.326 | 9% ± 0.289 | 0.114 |
| Online ordering of repeat prescriptions | 2% ± 0.137 | 1% ± 0.120 | 1% ± 0.114 | 0.849 |
| Video consultation | 60% ± 0.492 | 64% ± 0.482 | 67% ± 0.470 | 0.190 |
| Teleconsultation | 12% ± 0.324 | 6% ± 0.235 | 9% ± 0.292 | 0.019 * |
| Telemonitoring | 7% ± 0.258 | 4% ± 0.185 | 5% ± 0.228 | 0.113 |
| Other | 3% ± 0.167 | 2% ± 0.143 | 4% ± 0.200 | 0.179 |
One-way ANOVA was used to test differences in the mean use of specific e-health applications between the three practice types. * Indicates a significant difference (p < 0.05) between the mean values of the three practice types.
Percentage of practices using e-health, by e-health application (mean ± standard deviation), n = 735 (July 2020).
| E-Health Application | Solo Practice | Duo Practice | Group Practice | |
|---|---|---|---|---|
| E-consultation | 83% ± 0.381 | 83% ± 0.380 | 83% ± 0.373 | 0.964 |
| Online ordering of repeat prescriptions | 81% ± 0.392 | 87% ± 0.331 | 88% ± 0.330 | 0.134 |
| Video consultation | 44% ± 0.498 | 51% ± 0.501 | 56% ± 0.498 | 0.058 |
| Teleconsultation | 51% ± 0.502 | 67% ± 0.417 | 70% ± 0.460 | 0.000 * |
| Telemonitoring | 8% ± 0.273 | 12% ± 0.324 | 13% ± 0.338 | 0.289 |
| Other | 7% ± 0.262 | 5% ± 0.217 | 10% ± 0.295 | 0.095 |
| None | 5% ± 0.212 | 1% ± 0.099 | 1% ± 0.118 | 0.019 * |
One-way ANOVA was used to test differences in the mean use of specific e-health applications between the three practice types. * Indicates a significant difference (p < 0.05) between the mean values of the three practice types.