Kulkarni K, Shah R, Mangwani J, Ullah A, Gabbar O, James E, Dias J. Utilising the impact of COVID-19 on trauma throughput to adapt elective care models for more efficient trauma care. World J Orthop 2022; 13(10): 921-931 [PMID: 36312523 DOI: 10.5312/wjo.v13.i10.921]
Corresponding Author of This Article
Kunal Kulkarni, BMBCh, MA (Oxon), MSc, FRCS (Tr&Orth), European Board of Hand Surgery Diploma, Consultant Trauma & Orthopaedic Surgeon, Department of Trauma & Orthopaedics, University Hospitals of Leicester NHS Trust, Leicester General Hospital, Gwendolen Road, Leicester LE5 4PW, United Kingdom. kunalkulkarni@doctors.org.uk
Research Domain of This Article
Orthopedics
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Orthop. Oct 18, 2022; 13(10): 921-931 Published online Oct 18, 2022. doi: 10.5312/wjo.v13.i10.921
Table 1 Timelines for each phase evaluated
Phase
Description
Dates
Days
Phase 0
Pre-lockdown
1st January - 22nd March
81
Phase 1
Lockdown
23rd March - 31st May
70
Phase 2
Post-lockdown
1st June - 30st September
122
Phase 3
To year end
1st October - 31st December
92
Table 2 Subspecialty trauma breakdown (2018-2020)
Subspecialty
Year
Phase 0
Phase 1
Phase 2
Phase 3
Total
Pre-lockdown
Lockdown
Post-lockdown
To year end
Hip
2018
183 (39.8%)
131 (37.9%)
311 (37.0%)
118 (39.6%)
743 (38.2%)
2019
172 (39.3%)
146 (41.6%)
339 (40.4%)
139 (45.4%)
796 (41.2%)
2020
163 (41.3%)
146 (48.8%)
291 (36.6%)
76 (35.3%)
676 (39.7%)
Knee
2018
26 (5.7%)
14 (4.0%)
47 (5.6%)
16 (5.4%)
103 (5.3%)
2019
37 (8.4%)
24 (6.8%)
53 (6.3%)
27 (8.8%)
141 (7.3%)
2020
36 (9.1%)
16 (5.4%)
55 (6.9%)
7 (3.3%)
114 (6.7%)
Foot & ankle
2018
69 (15.0%)
60 (17.3%)
120 (14.3%)
45 (15.1%)
294 (15.1%)
2019
65 (14.8%)
47 (13.4%)
102 (12.2%)
39 (12.7%)
253 (13.1%)
2020
45 (11.4%)
26 (8.7%)
98 (12.3%)
36 (16.7%)
205 (12.0%)
Hand & wrist
2018
70 (15.2%)
53 (15.3%)
148 (17.6%)
51 (17.1%)
322 (16.6%)
2019
58 (13.2%)
54 (15.4%)
149 (17.8%)
33 (10.8%)
294 (15.2%)
2020
60 (15.2%)
44 (14.7%)
147 (18.5%)
42 (19.5%)
293 (17.2%)
Shoulder
2018
27 (5.9%)
25 (7.2%)
45 (5.4%)
20 (6.7%)
117 (6.0%)
2019
30 (6.8%)
22 (6.3%)
47 (5.6%)
21 (6.9%)
120 (6.2%)
2020
27 (6.8%)
13 (4.3%)
52 (6.5%)
21 (9.8%)
113 (6.6%)
Elbow
2018
32 (7.0%)
32 (9.2%)
87 (10.3%)
16 (5.4%)
167 (8.6%)
2019
29 (6.6%)
19 (5.4%)
62 (7.4%)
12 (3.9%)
122 (6.3%)
2020
24 (6.1%)
21 (7.0%)
75 (9.4%)
15 (7.0%)
135 (7.9%)
Complex multi-site
2018
16 (3.5%)
8 (2.3%)
16 (1.9%)
7 (2.3%)
47 (2.4%)
2019
4 (0.9%)
7 (2.0%)
14 (1.7%)
7 (2.3%)
32 (1.7%)
2020
4 (1.0%)
1 (0.3%)
9 (1.1%)
3 (1.4%)
17 (1.0%)
Polytrauma
2018
37 (8.0%)
23 (6.6%)
67 (8.0%)
25 (8.4%)
152 (7.8%)
2019
43 (9.8%)
32 (9.1%)
73 (8.7%)
28 (9.2%)
176 (9.1%)
2020
36 (9.1%)
32 (10.7%)
68 (8.6%)
15 (7.0%)
151 (8.9%)
Table 3 Patient demographics, length of stay, comorbidity indices and theatre parameters for 2018
Phase 0 (n = 709)
Phase 1 (n = 571)
Phase 2 (n = 1363)
Phase 3 (n = 486)
Total (n = 3129)
mean ± SD
Age at injury
61.23 ± 22.40
56.40 ± 24.04
57.52 ± 24.36
59.06 ± 23.79
58.39 ± 23.83
Length of spell (d)
8.39 ± 10.31
6.84 ± 8.57
6.76 ± 10.19
7.02 ± 9.45
7.18 ± 9.84
Charlson Comorbidity Index
0.72 ± 1.31
0.65 ± 1.24
0.68 ± 1.26
0.60 ± 1.21
0.67 ± 1.26
Elixhauser Comorbidity Index
1.19 ± 1.39
1.09 ± 1.36
1.14 ± 1.38
1.06 ± 1.31
1.13 ± 1.37
Hours to surgery
29.24 ± 50.75
31.46 ± 48.29
34.72 ± 91.27
26.22 ± 52.95
31.54 ± 71.10
Time in theatre
98.59 ± 58.34
92.86 ± 48.23
94.33 ± 46.30
95.49 ± 48.66
95.23 ± 50.04
Time in theatre/recovery
61.23 ± 22.40
56.40 ± 24.04
57.52 ± 24.36
59.06 ± 23.79
58.39 ± 23.83
Sex: Female
383 ± 54.0%
296 ± 51.8%
726 ± 53.3%
249 ± 51.2%
1654 ± 52.9%
Sex: Male
326 ± 46.0%
275 ± 48.2%
637 ± 46.7%
237 ± 48.8%
1475 ± 47.1%
Table 4 Patient demographics, length of stay, comorbidity indices and theatre parameters for 2019
Phase 0 (n = 664)
Phase 1 (n = 563)
Phase 2 (n = 1315)
Phase 3 (n = 471)
Total (n = 3013)
mean ± SD
Age at injury
58.89 ± 24.03
60.66 ± 23.17
58.66 ± 23.95
61.11 ± 22.98
59.47 ± 23.68
Length of spell (d)
7.30 ± 8.05
7.50 ± 9.90
6.67 ± 8.60
8.01 ± 10.88
7.18 ± 9.14
Charlson Comorbidity Index
0.71 ± 1.28
0.84 ± 1.49
0.78 ± 1.35
0.77 ± 1.30
0.77 ± 1.35
Elixhauser Comorbidity Index
1.20 ± 1.38
1.36 ± 1.55
1.39 ± 1.53
1.34 ± 1.42
1.33 ± 1.49
Hours to surgery
32.02 ± 57.64
32.13 ± 51.56
29.17 ± 47.03
31.96 ± 56.83
30.79 ± 51.99
Time in theatre
101.03 ± 49.49
96.30 ± 67.04
94.85 ± 57.61
95.95 ± 47.63
96.64 ± 56.36
Time in theatre/recovery
213.08 ± 110.23
208.29 ± 115.17
214.99 ± 141.51
228.39 ± 146.20
215.56 ± 131.70
Sex: Female
332 ± 50.0%
291 ± 51.7%
675 ± 51.3%
239 ± 50.7%
1537 ± 51.0%
Sex: Male
332 ± 50.0%
272 ± 48.3%
640 ± 48.7%
232 ± 49.3%
1476 ± 49.0%
Table 5 Patient demographics, length of stay, comorbidity indices and theatre parameters for 2020
Phase 0 (n = 640)
Phase 1 (n = 425)
Phase 2 (n = 1210)
Phase 3 (n = 413)
Total (n = 2688)
mean ± SD
Age at injury
59.46 ± 23.95
62.16 ± 23.61
57.70 ± 24.07
60.97 ± 23.47
59.33 ± 23.93
Length of spell (d)
7.05 ± 7.87
5.69 ± 5.90
5.71 ± 7.54
7.53 ± 8.86
6.30 ± 7.64
Charlson Comorbidity Index
0.77 ± 1.23
0.90 ± 1.45
0.68 ± 1.19
0.68 ± 1.25
0.73 ± 1.26
Elixhauser Comorbidity Index
1.27 ± 1.46
1.55 ± 1.63
1.21 ± 1.37
1.19 ± 1.39
1.28 ± 1.44
Hours to surgery
30.71 ± 49.37
30.84 ± 34.56
24.50 ± 37.98
24.59 ± 37.14
26.97 ± 40.41
Time in theatre
95.62 ± 50.10
144.25 ± 64.24
127.98 ± 54.37
123.20 ± 54.48
122.11 ± 57.35
Time in theatre/recovery
215.97 ± 124.31
175.22 ± 117.92
195.23 ± 106.09
203.28 ± 132.37
199.65 ± 117.42
Sex: Female
347 ± 54.2%
237 ± 55.8%
649 ± 53.6%
234 ± 56.7%
1467 ± 54.6%
Sex: Male
293 ± 45.8%
188 ± 44.2%
561 ± 46.4%
179 ± 43.3%
1221 ± 45.4%
Citation: Kulkarni K, Shah R, Mangwani J, Ullah A, Gabbar O, James E, Dias J. Utilising the impact of COVID-19 on trauma throughput to adapt elective care models for more efficient trauma care. World J Orthop 2022; 13(10): 921-931