| Literature DB >> 35977293 |
Thomas C Tsai1,2,3, Ava Ferguson Bryan1,2,4, Ning Rosenthal5, Jie Zheng3, E John Orav6, Austin B Frakt7,8, Jose F Figueroa3,6.
Abstract
Importance: The extent of the disruption to surgical care during the COVID-19 pandemic has not been empirically characterized on a national level. Objective: To characterize the use of surgical care across cohorts of surgical urgency during the COVID-19 pandemic, and to assess for racial and ethnic disparities. Design Setting and Participants: This was a retrospective observational study using the geographically diverse, all payer data from 767 hospitals in the Premier Healthcare Database. Procedures were categorized into 4 cohorts of surgical urgency (elective, nonelective, emergency, and trauma). A generalized linear regression model with hospital-fixed effects assessed the relative monthly within-hospital reduction in surgical encounters in 2020 compared with 2019. Main Outcomes and Measures: Outcomes were the monthly relative reduction in overall surgical encounters and across surgical urgency cohorts and race and ethnicity.Entities:
Mesh:
Year: 2021 PMID: 35977293 PMCID: PMC8796934 DOI: 10.1001/jamahealthforum.2021.4214
Source DB: PubMed Journal: JAMA Health Forum ISSN: 2689-0186
Patient Characteristics in 2020 vs 2019
| Characteristic | Patient, % | ||
|---|---|---|---|
| 2019 | 2020 | ||
| Surgical urgency cohorts per hospital, No. | |||
| Elective | 756 | 616 | <.001 |
| Urgent | 154 | 140 | <.001 |
| Emergency | 293 | 249 | <.001 |
| Trauma | 8396 | 6635 | <.001 |
| Patient characteristics | |||
| No. | 7 338 765 | 5 837 042 | NA |
| Age, y | |||
| ≤18 | 19.6 | 17.4 | <.001 |
| 19-49 | 35.9 | 37.0 | <.001 |
| 50-64 | 19.2 | 19.7 | <.001 |
| ≥65 | 24.7 | 25.4 | <.001 |
| Sex | |||
| Male | 51.8 | 51.3 | .02 |
| Female | 47.5 | 48.0 | .008 |
| Unknown | 0.2 | 0.3 | .31 |
| Race | |||
| Black | 12.9 | 12.8 | .15 |
| Hispanic | 10.8 | 11.0 | .55 |
| White | 69.2 | 68.8 | .38 |
| Other | 8.6 | 8.7 | .63 |
| Insurance | |||
| Medicare | 26.7 | 27.1 | .001 |
| Medicaid | 23.0 | 23.2 | .42 |
| Commercial | 31.0 | 31.2 | .28 |
| Self-pay | 8.9 | 8.4 | <.001 |
| Other | 9.9 | 9.6 | .07 |
P value obtained from Pearson χ2 test of independence except where indicated.
In our analyses, the “other” racial and ethnic category consisted of individuals classified as “Asian,” “other,” or “unable to determine.”
Hospital Characteristics
| Characteristic | % |
|---|---|
| No. | 767 |
| Size, beds | |
| ≤99 | 33.1 |
| 100-399 | 49.4 |
| ≥400 | 17.5 |
| Teaching hospital status | |
| Nonteaching | 73.1 |
| Teaching | 26.9 |
| Region | |
| Northeast | 12.4 |
| Midwest | 42.2 |
| South | 29.6 |
| West | 15.8 |
| Geography | |
| Rural | 31.6 |
| Urban | 68.4 |
Figure 1. Overall Change in Surgical Encounters, 2020 vs 2019
Results from a generalized linear regression model with a log link to assess for relative reduction in hospital monthly surgical use in 2020 vs 2019.
Figure 2. Trends in Surgical Encounters by Surgical Urgency Cohort, 2020 vs 2019
Results from a generalized linear regression model with a log link to assess for relative reduction in hospital monthly surgical use in 2020 vs 2019, stratified by surgical urgency cohort.
Figure 3. Change in Surgical Encounters by Race and Ethnicity and Surgical Urgency Cohort, 2020 vs 2019
Results from a generalized linear regression model with a log link to assess for relative reduction in hospital monthly surgical use in 2020 vs 2019, stratified by surgical urgency cohort and race and ethnicity. For ease of presentation, only results for Black, Hispanic, and White patients are displayed.