| Literature DB >> 32762354 |
Joseph A Weiner1, Peter R Swiatek1, Daniel J Johnson1, Philip K Louie2, Garrett K Harada3,4, Michael H McCarthy2, Niccole Germscheid5, Jason P Y Cheung6, Marko H Neva7, Mohammad El-Sharkawi8, Marcelo Valacco9, Daniel M Sciubba10, Norman B Chutkan11, Howard S An3,4, Dino Samartzis3,4.
Abstract
STUDYEntities:
Keywords: COVID-19; coronavirus; global; impact; private practice; spine; surgeons
Year: 2020 PMID: 32762354 PMCID: PMC8902318 DOI: 10.1177/2192568220949183
Source DB: PubMed Journal: Global Spine J ISSN: 2192-5682
Figure 1.Distribution of survey responses by country. World map depicting number of survey responses received internationally. Color-filled countries indicate at least one survey was received. Green = Under 10 surveys received. Teal = 11 to 25. Red = 26 to 50. Orange = 51 to 100. Dark blue = Over 100. Light blue = No surveys received.
Respondent Demographics by Practice Setting.a
| Academic (n = 405), n (%) | Privademic (n = 204), n (%) | Private (n = 144), n (%) | Public (n = 139), n (%) |
| |
|---|---|---|---|---|---|
| Age (years) | n = 405 | n = 203 | n = 144 | n = 139 | .25 |
| 25-34 | 66 (16.3) | 27 (13.3) | 18 (12.5) | 19 (13.7) | |
| 35-44 | 133 (32.8) | 91 (44.8) | 57 (39.6) | 61 (43.9) | |
| 45-54 | 120 (29.6) | 47 (23.2) | 39 (27.1) | 37 (26.6) | |
| 55-64 | 75 (18.5) | 34 (16.7) | 23 (16) | 18 (12.9) | |
| 65+ | 11 (2.7) | 4 (2.0) | 7 (4.9) | 4 (2.9) | |
| Male sex | 372 (91.9) | 196 (96.1) | 137 (95.1) | 117 (84.2) | .0013 |
| Estimated home city population | n = 403 | n = 203 | n = 144 | n = 139 | <.0001 |
| <100 000 | 14 (3.5) | 3 (1.5) | 6 (4.2) | 22 (15.8) | |
| 100 000-500 000 | 79 (19.6) | 33 (16.3) | 30 (20.8) | 43 (30.9) | |
| 500 000-1 000 000 | 71 (17.6) | 29 (14.3) | 21 (14.6) | 15 (10.8) | |
| 1 000 000-2 000 000 | 54 (13.4) | 47 (23.2) | 23 (16) | 20 (14.4) | |
| >2 000 000 | 185 (45.9) | 91 (44.8) | 64 (44.4) | 39 (28.1) | |
| Geographic region | n = 400 | n = 198 | n = 142 | n = 137 | <.0001 |
| Africa | 20 (5.0) | 13 (6.6) | 7 (4.9) | 4 (2.9) | |
| Asia | 127 (31.8) | 29 (14.6) | 26 (18.3) | 30 (21.9) | |
| Australia | 1 (0.3) | 4 (2.0) | 1 (0.7) | 2 (1.5) | |
| Europe | 115 (28.9) | 47 (23.7) | 20 (14.1) | 59 (43.1) | |
| Middle east | 23 (5.8) | 28 (14.1) | 15 (10.6) | 11 (8.0) | |
| North America | 91 (22.8) | 23 (11.6) | 30 (21.1) | 7 (5.1) | |
| South/Latin America | 23 (5.8) | 54 (27.3) | 43 (30.3) | 24 (17.5) | |
| Specialty | n = 401 | n = 202 | n = 140 | n = 138 | .63 |
| Neurosurgery | 100 (24.9) | 55 (27.2) | 41 (29.3) | 36 (26.1) | |
| Orthopedics | 294 (73.3) | 145 (71.8) | 97 (69.3) | 99 (71.7) | |
| Pediatric surgery | 0 (0) | 1 (0.5) | 1 (0.7) | 0 (0) | |
| Trauma | 7 (1.7) | 1 (0.5) | 1 (0.7) | 3 (2.2) | |
| Fellowship trained | 282 (69.3) | 158 (77.5) | 112 (77.8) | 86 (61.9) | .0039 |
| Years since training completion | n = 279 | n = 158 | n = 109 | n = 84 | .23 |
| <5 | 64 (22.9) | 38 (24.1) | 33 (30.3) | 4 (28.6) | |
| 5-10 | 53 (19) | 41 (26) | 24 (22) | 19 (22.6) | |
| 10-15 | 53 (19) | 25 (15.8) | 13 (11.9) | 13 (15.5) | |
| 15-20 | 63 (22.6) | 19 (12) | 20 (18.4) | 15 (17.9) | |
| >20 | 46 (16.5) | 35 (22.2) | 19 (17.4) | 13 (15.5) | |
| Percent research | n = 404 | n = 204 | n = 143 | n = 138 | .0003 |
| 0%-25% | 306 (75.7) | 167 (81.9) | 129 (90.2) | 126 (91.3) | |
| 26%-50% | 78 (19.3) | 29 (14.2) | 13 (9.1) | 8 (5.8) | |
| 51%-75% | 10 (2.5) | 6 (2.9) | 1 (0.7) | 4 (2.9) | |
| 76%-100% | 10 (2.5) | 2 (1) | 0 (0) | 0 (0) | |
| Percent clinical | n = 404 | n = 204 | n = 143 | n = 139 | .011 |
| 0%-25% | 13 (3.2) | 3 (1.5) | 4 (2.8) | 2 (1.4) | |
| 26%-50% | 47 (11.6) | 19 (9.3) | 10 (7) | 10 (7.2) | |
| 51%-75% | 96 (23.8) | 53 (26) | 16 (11.2) | 29 (20.9) | |
| 76%-100% | 248 (61.4) | 129 (63.2) | 113 (79) | 98 (70.5) | |
| Percent teaching | n = 404 | n = 203 | n = 143 | n = 138 | .0009 |
| 0%-25% | 292 (72.3) | 135 (66.5) | 124 (86.7) | 114 (82.6) | |
| 26%-50% | 70 (17.2) | 49 (24.1) | 15 (10.5) | 17 (12.3) | |
| 51%-75% | 28 (6.9) | 14 (6.9) | 2 (1.4) | 6 (4.4) | |
| 76%-100% | 14 (3.5) | 5 (2.5) | 2 (1.4) | 1 (0.7) |
a Demographic data presented as number of respondents (n) and percent of total respondents for specific question (%). For privacy reasons, respondents were not required to answer all demographic questions.
COVID-19 Preparedness by Practice Setting.
| Academic, n (%) | Privademic, n (%) | Private, n (%) | Public, n (%) |
| |
|---|---|---|---|---|---|
| Access to COVID testing | 326 (85.1) | 158 (79.8) | 112 (81.8) | 101 (82.1) | .42 |
| Formal hospital guidelines | 227 (66.8) | 103 (58.9) | 60 (50.9) | 60 (53.1) | .0048 |
| Adequate PPE | 217 (57.3) | 77 (39.5) | 66 (48.5) | 51 (41.5) | .0002 |
| Forms of PPE | |||||
| N-95 mask | 226 (55.8) | 91 (44.6) | 63 (43.8) | 68 (48.9) | .018 |
| Surgical mask | 344 (84.9) | 169 (82.8) | 113 (78.5) | 108 (77.7) | .15 |
| Face shield | 223 (55.1) | 72 (35.3) | 54 (37.5) | 63 (45.3) | <.0001 |
| Gown | 249 (61.5) | 107 (52.5) | 63 (43.8) | 69 (49.6) | .001 |
| Full-face respirator | 61 (15.1) | 11 (5.4) | 12 (8.3) | 10 (7.2) | .0007 |
| Adequate ventilators | 180 (47.2) | 61 (31.3) | 53 (39.6) | 46 (37.7) | .0024 |
Abbreviation: PPE, personal protective equipment.
Figure 2.COVID-19 Preparedness by Practice Setting. (a) Bar graph comparing access to COVID-19 testing stratified by practice setting. (b) Bar graph comparing access to adequate personal protective equipment (PPE) stratified by practice setting.
Multivariate Analysis.a
| Academic vs Private (ref), OR (95% CI) [ | Academic vs Privademic (ref), OR (95% CI)
[ | Academic vs Public (ref), OR (95% CI) [ | Private vs Privademic (ref), OR (95% CI)
[ | Private vs Public (ref), OR (95% CI) [ | Privademic vs Public (ref), OR (95% CI)
[ | |
|---|---|---|---|---|---|---|
| Hospital formal guidelines | 1.56 (0.98, 2.5) [.06] | 1.11 (0.72, 1.72) [.61] | 1.54 (0.93, 2.5) [.095] | 0.71 (0.42, 1.17) [.19] | 0.97 (0.55, 1.72) [.93] | 1.37 (0.79, 2.38) [.26] |
| Adequate PPE | 1.33 (0.85, 2.08) [.21] | 1.72 (1.16, 2.56) [.0068] | 1.56 (0.97, 2.5) [.065] | 1.29 (0.81, 2.08) [.29] | 1.16 (0.68, 2.0) [.58] | 0.90 (0.54, 1.52) [.69] |
| Forms of PPE provided | ||||||
| N-95 mask | 1.94 (1.24, 3.06) [.004] | 1.43 (0.96, 2.13) [.075] | 1.2 (0.77, 1.87) [.42] | 0.74 (0.45, 1.2) [.22] | 0.62 (0.36, 1.05) [.076] | 0.84 (0.51, 1.37) [.48] |
| Surgical mask | 1.40 (0.8, 2.43) [.24] | 1.00 (0.59, 1.69) [.99] | 1.71 (0.98, 2.99) [.06] | 0.71 (0.39, 1.29) [.24] | 1.22 (0.65, 2.92) [.53] | 1.71 (0.93, 3.17) [.086] |
| Face shield | 2.05 (1.31, 3.19) [.0016] | 1.90 (1.28, 2.83) [.0016] | 1.36 (0.87, 2.12) [.18] | 0.92 (0.57, 1.52) [.77] | 0.66 (0.87, 2.12) [.18] | 0.72 (0.43, 1.18) [.19] |
| Gown | 2.33 (1.5, 3.62) [.0002] | 1.38 (0.93, 2.04) [.11] | 1.8 (1.15, 2.82) [.011] | 0.59 (0.37, 0.95) [.03] | 0.77 (0.46, 1.31) [.34] | 1.31 (0.8, 2.14) [.29] |
| Full-face respirator | 2.29 (1.11, 4.7) [.024] | 2.62 (1.28, 5.37) [.0086] | 2.14 (0.99, 4.63) [.054] | 1.14 (0.47, 2.78) [.77] | 0.93 (0.37, 2.35) [.88] | 0.82 (0.32, 2.09) [.67] |
| Adequate ventilators | 1.20 (0.76, 1.89) [.43] | 1.59 (1.04, 2.38) [.031] | 1.47 (0.9, 2.38) [.12] | 1.31 (0.79, 2.17) [.28] | 1.22 (0.69, 2.17) [.49] | 0.92 (0.54, 1.61) [.79] |
| Very worried about outbreak (score of 4 or 5) | 0.84 (0.54, 1.32) [.46] | 0.71 (0.47, 1.07) [.1] | 0.87 (0.54, 1.41) [.58] | 0.84 (0.51, 1.38) [.5] | 1.03 (0.59, 1.81) [.9] | 1.23 (0.72, 2.08) [.45] |
| Greatest stressors | ||||||
| Hospital ability to treat COVID-19 positive patients | 2.34 (1.46, 3.73) [.004] | 1.55 (1.05, 2.29) [.029] | 0.62 (0.38, 1.02) [.058] | 0.66 (0.4, 1.1) [.11] | 0.41 (0.24, 0.71) [.0014] | 0.61 (0.38, 1.02) [.058] |
| Economic issues | 0.49 (0.32, 0.75) [.0011] | 0.56 (0.29, 0.81) [.0025] | 1.22 (0.77, 1.91) [.4] | 1.13 (0.71, 1.78) [.6] | 2.47 (1.47, 4.16) [.0007] | 2.19 (1.34, 3.57) [.0018] |
| Hospital restrictions | ||||||
| Limitations on domestic travel | 3.1 (2, 4.81) [<.0001] | 1.9 (1.29, 2.8) [.0011] | 1.99 (1.28, 3.1) [.0021] | 0.61 (0.38, 0.98) [.041] | 0.64 (0.38, 1.08) [.095] | 1.05 (0.65, 1.7) [.85] |
| Cancellation of all education activities | 2.36 (1.45, 3.84) [.0005] | 1.13 (0.7, 1.82) [.62] | 2.53 (1.52, 4.24) [.0004] | 0.48 (0.28, 0.81) [.0061] | 1.07 (0.61, 1.88) [.8] | 2.25 (1.28, 3.94) [.0047] |
| Nonessential staff to work from home | 2.31 (1.47, 3.6) [.0002] | 1.08 (0.48, 1.38) [.45] | 1.88 (1.19, 2.97) [.0067] | 0.47 (0.29, 0.76) [.002] | 0.82 (0.48, 1.38) [.45] | 1.74 (1.06, 2.87) [.03] |
| Performing elective spine surgeries | 2.32 (1.17, 4.6) [.016] | 1.75 (0.99, 3.07) [.053] | 1.12 (0.59, 2.14) [.73] | 0.75 (0.22, 0.86) [.47] | 0.48 (0.21, 1.11) [.087] | 0.64 (0.31, 1.35) [.24] |
| Performing essential/emergent spine cases | 3.06 (1.58, 5.94) [.0009] | 1.72 (0.9, 3.28) [.1] | 3.19 (1.6, 6.36) [.001] | 0.56 (.29, 1.09) [.087] | 1.04 (0.51, 2.12) [.91] | 1.85 (0.92, 3.73) [.085] |
| Impact on patient care in 1 year | ||||||
| No change | 1.22 (0.67, 2.24) [.52] | 1.41 (0.8, 2.49) [.24] | 0.68 (0.39, 1.18) [.17] | 1.15 (0.58, 2.31) [.69] | 0.56 (0.28, 1.1) [.092] | 0.48 (0.25, 0.93) [.031] |
| Heightened awareness of hygiene | 1.09 (0.71, 1.67) [.68] | 0.67 (0.46, 0.99) [.042] | 1.46 (0.94, 2.28) [.094] | 0.62 (0.39, 0.98) [.04] | 1.34 (0.79, 2.25) [.79] | 2.17 (1.33, 2.54) [.0019] |
| Will increase use of PPE | 1.27 (0.81, 1.98) [.3] | 0.69 (0.47, 1) [.055] | 1.11 (0.71, 1.74) [.64] | 0.54 (0.34, 0.87) [.012] | 0.88 (0.51, 1.5) [.63] | 1.61 (0.99, 2.62) [.054] |
Abbreviation: PPE, personal protective equipment.
a Nominal multivariate logistic regression controlling for gender (P = .0013), home city population (P < .0001), region (P < .0001), fellowship training (P = .0039), and practice breakdown (ie, research, clinical, and teaching) (P = .0003, P = .011, and P = .0009, respectively). Odds ratios (ORs) presented as first group in reference to second group (ie, academic surgeons had 1.56 times likelihood of reporting formal hospital guidelines compared with private surgeons).
COVID-19 Impact and Response by Practice Setting.
| Academic, n (%) | Privademic, n (%) | Private, n (%) | Public, n (%) |
| |
|---|---|---|---|---|---|
| Diagnosed with COVID-19 | 4 (1) | 3 (1.5) | 0 (0) | 2 (1.6) | .53 |
| Personally quarantined | 81 (21.3) | 53 (26.8) | 35 (25.7) | 21 (17.1) | .16 |
| Performed medical duties outside of normal scope | 92 (24.9) | 39 (20.9) | 21 (16.5) | 30 (25.9) | .19 |
| Mean worry (1 = | 3.6 ± 1.2 | 3.9 ± 1.1 | 3.8 ± 1.1 | 3.8 ± 1.1 | .019 |
| 3 greatest stressors | |||||
| Personal health | 161 (39.8) | 86 (42.2) | 52 (36.1) | 57 (41) | .71 |
| Family health | 287 (70.9) | 153 (75) | 101 (70.1) | 95 (68.4) | .55 |
| Community health | 160 (39.5) | 97 (47.6) | 61 (42.4) | 51 (36.7) | .17 |
| Hospital ability to treat COVID-19 positive patients | 170 (42) | 73 (5.8) | 37 (25.7) | 70 (50.4) | .0001 |
| Timeline to resume regular clinic work | 170 (42) | 92 (45.1) | 66 (45.8) | 49 (35.3) | .24 |
| Government/leadership | 75 (18.5) | 28 (13.7) | 26 (18.1) | 25 (18) | .48 |
| Return to nonessential activities | 59 (14.6) | 19 (9.3) | 21 (14.6) | 16 (11.5) | .27 |
| Economic issues | 148 (36.5) | 106 (52) | 82 (56.9) | 47 (33.8) | <.0001 |
| Hospital restrictions | |||||
| Quarantine on return from international travel | 244 (60.3) | 112 (54.9) | 71 (49.3) | 77 (55.4) | .13 |
| Limitations on domestic travel | 260 (64.2) | 98 (48) | 56 (38.9) | 66 (47.5) | <.0001 |
| Cancellation of all education activities | 328 (81) | 162 (79.4) | 97 (67.4) | 98 (70.5) | .0018 |
| Nonessential staff to work from home | 270 (66.7) | 132 (64.7) | 74 (51.4) | 78 (56.1) | .004 |
| Cancellation of hospital meetings | 311 (76.8) | 159 (77.9) | 101 (70.1) | 99 (71.2) | .21 |
| Cancellation of elective surgeries | 320 (79) | 170 (83.3) | 110 (76.4) | 110 (79.1) | .43 |
| Satisfaction with hospital response | .0046 | ||||
| Appears in disarray/disorganized | 241 (67.7) | 94 (51.7) | 79 (64.8) | 61 (53) | |
| Taken some action but not enough | 9 (2.5) | 2 (1.1) | 4 (3.3) | 2 (1.7) | |
| Acceptable/appropriate | 24 (6.7) | 20 (11) | 8 (6.6) | 16 (13.9) | |
| Actions are excessive and unnecessary | 82 (23) | 66 (36.3) | 31 (25.4) | 36 (31.3) |
Figure 3.Radar chart depictions of current COVID-19 hospital policies by practice setting. Six-sided (hexagon) radar charts visually depicting cumulative percentage of responses verifying the enactment of a given COVID-19 hospital policy at the time of survey distribution. Queried policies are listed at the vertex of a given figure, whereby points falling on a vertex of the innermost pentagon correspond to a cumulative total of 0% of survey responses received. Each subsequent pentagon corresponds to a 20% increase in responses for a given category. *Indicates difference significant at the 95% confidence level (P < .05).
Economic Impact of COVID-19 by Practice Setting.
| Academic, n (%) | Privademic, n (%) | Private, n (%) | Public, n (%) |
| |
|---|---|---|---|---|---|
| Performing elective spine cases | 89 (24.2) | 25 (13.2) | 14 (11.2) | 20 (17) | .0011 |
| Performing essential/emergent spine cases | 342 (92.9) | 162 (85.7) | 101 (80.8) | 94 (80.3) | .0001 |
| Decrease in case volume | .0095 | ||||
| ≤25% | 40 (10.8) | 10 (5.3) | 12 (9.6) | 10 (8.6) | |
| 26%-50% | 40 (10.8) | 12 (6.3) | 8 (6.4) | 18 (15.5) | |
| 51%-75% | 65 (17.6) | 32 (16.8) | 8 (6.4) | 18 (15.5) | |
| >75% | 224 (60.7) | 136 (71.6) | 97 (77.6) | 80 (69) | |
| Time spent performing clinical duties | .31 | ||||
| Increased | 19 (5.1) | 14 (7.4) | 6 (4.8) | 7 (6) | |
| Stayed the same | 44 (11.9) | 15 (18.1) | 8 (6.4) | 16 (13.8) | |
| Decreased | 307 (83) | 161 (84.7) | 111 (88.8) | 93 (80.2) | |
| Impact on income | <.0001 | ||||
| Planned reduction—on salary | 63 (18.2) | 39 (22) | 18 (14.9) | 18 (15.7) | |
| No impact—on salary | 151 (43.6) | 32 (18.1) | 15 (12.4) | 45 (39.1) | |
| Planned reduction—productivity-based income | 30 (8.7) | 10 (5.7) | 11 (9.1) | 13 (11.3) | |
| No impact—productivity-based income | 5 (1.5) | 1 (0.6) | 1 (0.8) | 0 (0) | |
| Losing income | 97 (28) | 95 (53.7) | 76 (62.8) | 39 (33.9) | |
| Impact on personal revenue | <.0001 | ||||
| ≤25% | 141 (41) | 24 (13.6) | 12 (9.8) | 42 (37.2) | |
| 26%-50% | 108 (31.4) | 53 (29.9) | 28 (23) | 37 (32.7) | |
| 51%-75% | 61 (17.7) | 39 (22) | 25 (20.5) | 17 (15) | |
| >75% | 34 (9.9) | 61 (34.5) | 57 (46.7) | 17 (15) | |
| Impact on hospital revenue | <.0001 | ||||
| ≤25% | 93 (26.9) | 29 (16.4) | 9 (7.6) | 38 (33.6) | |
| 26%-50% | 96 (27.8) | 53 (29.9) | 19 (16) | 31 (27.4) | |
| 51%-75% | 100 (28.9) | 39 (22) | 40 (33.6) | 26 (23) | |
| >75% | 57 (16.5) | 56 (31.6) | 51 (42.9) | 18 (15.9) |
Figure 4.COVID-19 economic impact by practice setting. (a) Bar graph comparing performance of elective and emergent spine case during the COVID-19 pandemic stratified by practice setting. (b) Bar graph comparing self-reported impact on surgeon income stratified by practice setting.
Long-Term Impacts of COVID-19 by Practice Setting.
| Academic, n (%) | Privademic, n (%) | Private, n (%) | Public, n (%) |
| |
|---|---|---|---|---|---|
| Impact on patient care in 1 year | |||||
| No change | 60 (14.8) | 21 (10.3) | 20 (13.9) | 31 (22.3) | .022 |
| Heightened awareness of hygiene | 203 (50.1) | 116 (58.9) | 65 (45.1) | 51 (38.7) | .0023 |
| Will increase use of PPE | 154 (38) | 97 (47.6) | 45 (31.3) | 48 (34.5) | .011 |
| Ask patient to reschedule if they feel sick | 128 (31.6) | 67 (32.8) | 45 (31.3) | 45 (33.4) | .99 |
| Pursue increased nonoperative measures prior to surgery | 68 (16.8) | 40 (19.6) | 18 (12.5) | 24 (17.3) | 0.38 |
| Growth in digital options for communication | 153 (37.8) | 76 (37.3) | 39 (27.1) | 45 (32.4) | .1 |
| Likelihood to attend conference in 1 year | .33 | ||||
| Likely | 215 (63.2) | 119 (68) | 85 (71.4) | 76 (67.9) | |
| Unsure | 101 (29.7) | 46 (26.3) | 26 (21.9) | 24 (21.4) | |
| Not likely | 24 (7.1) | 10 (5.7) | 8 (6.7) | 12 (10.7) | |
| Need for formal guidelines | 320 (97.9) | 168 (100) | 114 (99) | 106 (100) | .1 |
Abbreviation: PPE, personal protective equipment.