| Literature DB >> 32810841 |
Ashwin Ramaswamy1, Miko Yu1, Siri Drangsholt1, Eric Ng1, Patrick J Culligan1, Peter N Schlegel1, Jim C Hu1.
Abstract
BACKGROUND: New York City was the international epicenter of the COVID-19 pandemic. Health care providers responded by rapidly transitioning from in-person to video consultations. Telemedicine (ie, video visits) is a potentially disruptive innovation; however, little is known about patient satisfaction with this emerging alternative to the traditional clinical encounter.Entities:
Keywords: COVID-19; disruptive technology; health care delivery; health care reform; health policy; health services research; medical informatics; medicine; pandemics; patient satisfaction; physicians; practice patterns; remote consultation; telemedicine
Mesh:
Year: 2020 PMID: 32810841 PMCID: PMC7511224 DOI: 10.2196/20786
Source DB: PubMed Journal: J Med Internet Res ISSN: 1438-8871 Impact factor: 5.428
Figure 1CONSORT (Consolidated Standards of Reporting Trials) diagram detailing the inclusion and exclusion criteria for our study.
Baseline characteristics of clinic visits before and after COVID-19.
| Characteristic | Pre–COVID-19 (April 1, 2019 to March 3, 2020) (n=36,273) | COVID-19 (March 4-31, 2020) (n=2336) | ||||||
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| All visits | 92.47 (11.25) | 93.43 (10.51) | <.001 | ||||
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| Telemedicine | 95.01 (8.65) | 94.87 (10.22) | .31 | ||||
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| In-person | 92.46 (11.26) | 93.02 (10.56) | .004 | ||||
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| Median (IQR) | 63 (48-72) | 62 (47-72) | —a | ||||
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| Mean (SD) | 59.85 (16.49) | 59.08 (16.15) | .03 | ||||
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| <.001 | ||||||
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| 18-25 | 853 (2.35) | 46 (1.97) |
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| 26-39 | 4827 (13.31) | 315 (13.48) |
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| 40-59 | 9526 (26.26) | 713 (30.52) |
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| 60-79 | 17,911 (49.38) | 1089 (46.62) |
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| ≥80 | 3156 (8.70) | 173 (7.41) |
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| .29 | |||||||
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| Male | 14,444 (39.82) | 904 (38.70) |
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| Female | 21,829 (60.18) | 1432 (61.30) |
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| <.001 | |||||||
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| Video | 109 (0.30) | 511 (21.88) |
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| Follow-up | 18,131 (49.98) | 852 (36.47) |
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| New patient | 7606 (20.97) | 393 (16.82) |
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| Established well visit | 3204 (8.83) | 157 (6.72) |
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| Consultation | 1224 (3.37) | 74 (3.17) |
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| New well visit | 1215 (3.35) | 77 (3.30) |
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| Follow-up (complex) | 1132 (3.12) | 55 (2.35) |
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| Physical | 772 (2.13) | 44 (1.88) |
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| Post-op | 390 (1.08) | 30 (1.28) |
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| Other | 2490 (6.86) | 143 (6.12) |
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| .15 | |||||||
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| New | 9816 (27.06) | 665 (28.47) |
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| Existing | 26,457 (72.94) | 1671 (71.53) |
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| <.001 | |||||||
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| Internal medicine | 7427 (20.47) | 626 (26.80) |
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| Obstetrics/gynecology | 3287 (9.06) | 206 (8.82) |
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| Cardiology | 3015 (8.31) | 163 (7.00) |
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| Ophthalmology | 2863 (7.89) | 144 (6.16) |
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| Otolaryngology | 2611 (7.20) | 133 (5.69) |
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| Hematology/oncology | 1934 (5.33) | 119 (5.09) |
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| Dermatology | 1646 (4.54) | 84 (3.60) |
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| Other | 13,491 (37.19) | 861 (36.86) |
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aNot applicable.
Figure 2Violin and box-and-whiskers plot depicting the unadjusted distribution of in-person vs video visits.
Multivariable linear regression for variables predicting Press Ganey scores.
| Variable | Press Ganey score | |||
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| Parameter estimate | 95% CI |
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| Telemedicine | 2.18 | 1.20 to 3.16 | <.001 | |
| Female | –0.73 | –0.96 to –0.50 | <.001 | |
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| 18-25 | –2.05 | –2.88 to –1.22 | <.001 |
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| 26-39 | –1.95 | –2.45 to –1.46 | <.001 |
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| 40-59 | –0.66 | –1.10 to –0.22 | .003 |
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| 60-79 | 0.70 | 0.29 to 1.11 | .001 |
| COVID-19 period | 0.55 | 0.04 to 1.06 | .04 | |
| New visit | –0.75 | –1.00 to –0.49 | <.001 | |