Abstract
Background
This study assesses if post-operative outcomes following THA vary by racial groups.
Methods
A review of the ACS-NSQIP database was performed to compare THA patient outcomes from 2008 to 2016 according to race.
Results
During the study period, 117,389 THA patients were identified. Blacks were at significantly increased risk of peri-operative complications in comparison to non-Hispanic Whites, including serious medical morbidity (+27%), and prolonged length of stay (+53%).
Conclusions
Despite multivariate control and propensity-matched analysis of important risk factors, race independently predicts longer operative times and higher rates of discharge to non-home facilities.
Keywords: Arthroplasty, Racial disparity, Complications, Primary total hip replacement, Operative time, Discharge location
1. Introduction
Total hip arthroplasty (THA) procedure volumes have increased over the past several decades, and are among the most commonly performed surgeries in the United States.1,2 This procedure has demonstrated long lasting positive functional improvements and pain relief to a wide variety of demographic groups.3, 4, 5, 6 Additionally, it has been proven to be one of the most cost effective procedures for patients with advanced hip arthritis.7 However, the rate of post-operative complication may not be equivalent when comparing outcomes between racial groups.
Racial disparities have been previously demonstrated between non-Hispanic White and Black racial groups in post-operative complications in procedures such as congenital heart surgery,8 neurological procedures,9,10 and appendectomies.11 Similar trends have been observed in total joint arthroplasty (TJA), specifically in regards to the Black population. For several types of TJA, Black patients have shown reduced utilization rates and higher complication rates compared to non-Hispanic White populations – most notably with increased length of stay.12, 13, 14 There is evidence to suggest that 30-day readmission rates are increasing in the Black population.15 Similar racial disparities have been observed in Hispanic populations.16
The NSQIP is a surgical database with over 150 patient-specific variables, including preoperative risk factors, intraoperative variables, and 30-day post-operative mortality and morbidity outcomes for a population spanning participating institutions across the United States. Each institution has a certified reviewer to verify validity of the data collected prior to entry into the database.17
To our knowledge, there are no prior studies evaluating the impact of race on surgical complications with the quantity of cases available from the most recent years of NSQIP. Our goal was to evaluate if differences existed in post-surgical outcomes and care based on self-identified race using the NSQIP database. We hypothesized that Black, Hispanic, and Asian patients would have higher mean operative time, length of stay, re-operation rate, mortality and morbidity rate, and a lower rate of discharge to home. However, we expected some of these differences to be mitigated when controlling for medical comorbidities via propensity score matching and multivariate analysis.
2. Materials and methods
The 2008 to 2016 NSQIP database was accessed, and patients undergoing total hip arthroplasty were identified using the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) coding system. Patients undergoing total hip arthroplasty as a treatment for fracture were excluded from the study. Over 400 participating hospitals contributed to the NSQIP database.17
Self-identified race was used as a discrete variable to group patients having undergone the procedure. Additional categorical information analyzed included sex, advanced age (≥70 years old), functional status (independent, partially dependent, or totally dependent), American Society of Anesthesiologists (ASA) classification, diabetes, obesity (BMI > 30 kg/m∧2), hypertension medication use, arthritis diagnosis (osteoarthritis or rheumatoid arthritis), smoking history, general anesthesia, COPD, chronic steroid use, dialysis dependence, and cancer diagnosis. Pre-operative laboratory value cutoffs utilized included low hematocrit (<30), high creatinine (≥2 mg/dL), low albumin (<3.5 g/dL), low platelets (<100 billion cells/L), and high bilirubin (≥2 mg/dL).
The primary outcome measures of this study included death or serious morbidity within 30 days of surgery. Serious morbidity was defined as surgical site infection, cardiac complication requiring intervention, respiratory complication requiring intervention, postoperative blood transfusion, sepsis, deep venous thrombosis (DVT), or pulmonary embolus (PE). Time variables including operative time, length of stay, discharge location, readmission or reoperation within 30 days were assessed. Outcome variables compared each racial group (Black, Hispanic, and Asian) with the “control” group (non-Hispanic Whites).
Univariate analysis was performed using Chi-square or Fischer's Exact test to compare categorical data and t-test to compare means for continuous data. A p-value of less than 0.05 was deemed significant. A reverse-stepwise multivariate logistic regression model incorporating all significant univariate factors was used to determine the impact of race on primary and secondary outcomes. Covariates were included for analysis if the p-value for the covariate effect in the model was <0.05 after inclusion of all other covariates.
Propensity score matching was used to eliminate the effect of confounding variables on outcome differences between groups and as a supplement to the multivariate model for comparison. A propensity score was determined based on the relative contribution of each covariate included in the multivariate model. A matched dataset was derived for each control:case analysis using 1:1 nearest neighbor matching with a caliper set at 1x10−7. This propensity-matched dataset then underwent univariate evaluation of risk factors to confirm adequacy of the matching algorithm. Finally, simple logistic regression was used within the matched dataset to derive a propensity-matched risk for outcomes of interest comparing each racial group to the control, the non-Hispanic white group.18 Stata version 14.2 (Statacorp, College Station, TX) was used for all statistical analyses.
This study was reviewed and was deemed exempt by institutional review board.
3. Results
3.1. Patient demographics
Our survey of the NSQIP database yielded a total of 117,389 individuals undergoing total hip arthroplasty (THA) for arthritis. Of these, 104,693 (89.18%) identified as Non-Hispanic White, 9,968 (8.49%) as Black, 905 (0.77%) as Hispanic, and 1,823 (1.55%) as Asian.
Comparison between each racial group and the Non-Hispanic White group using Pearson Chi-Squared test revealed statistically significant differences in a variety of demographic variables, and also in the distribution of comorbidities at presentation[Insert Table 1).
Table 1.
Comparative demographics for patients undergoing total hip replacement grouped by race.
| Overall n (%) | White THA n (%) | Black THA n (%) | P Value* | Hispanic THA n (%) | P Value* | Asian THA n (%) | P Value* | |
|---|---|---|---|---|---|---|---|---|
| Total | 117389 (100) | 104693 (89.18) | 9968 (8.49) | 905 (0.77) | 1823 (1.55) | |||
| Sex | 0.001 | 0.152 | <0.001 | |||||
| Male | 52949 (45.11) | 47252 (45.13) | 4669 (46.84) | 430 (47.51) | 598 (32.8) | |||
| Female | 64440 (54.89) | 57441 (54.87) | 5299 (53.16) | 475 (52.49) | 1225 (67.2) | |||
| Age | <0.001 | <0.001 | 0.657 | |||||
| < 70 yr | 77447 (65.97) | 67579 (64.54) | 7985 (80.1) | 715 (79.01) | 1168 (64.04) | |||
| ≥ 70 yr | 39964 (34.04) | 37134 (35.46) | 1984 (19.9) | 190 (20.99) | 656 (35.96) | |||
| Functional status | <0.001 | <0.001 | 0.287 | |||||
| Independent | 114271 (97.34) | 102039 (97.8) | 9635 (97.09) | 862 (95.67) | 1735 (97.31) | |||
| Partially Dependent | 2571 (2.19) | 2207 (2.12) | 279 (2.81) | 38 (4.22) | 47 (2.64) | |||
| Totally Dependent | 105 (0.09) | 93 (0.09) | 10 (0.1) | 1 (0.11) | 1 (0.06) | |||
| ASA class | <0.001 | 0.355 | <0.001 | |||||
| Low | 67463 (57.47) | 60949 (58.21) | 4766 (47.81) | 513 (56.69) | 1235 (67.71) | |||
| High | 49946 (42.55) | 43762 (41.79) | 5203 (52.19) | 392 (43.31) | 589 (32.29) | |||
| Comorbidities | ||||||||
| Obesity (BMI >30 kg/m∧2) | 54750 (46.64) | 48179 (46.01) | 5630 (56.48) | <0.001 | 484 (53.48) | <0.001 | 457 (25.05) | <0.001 |
| Diabetes | 13532 (11.53) | 11374 (10.89) | 1754 (17.64) | <0.001 | 160 (17.76) | <0.001 | 244 (13.41) | 0.001 |
| Hypertension Medications | 67537 (57.53) | 59126 (56.46) | 6916 (69.38) | <0.001 | 450 (49.72) | <0.001 | 1045 (57.32) | 0.464 |
| Arthritis | 0.013 | <0.001 | 0.183 | |||||
| Osteo | 105683 (90.03) | 95151 (99.67) | 8299 (99.51) | 714 (98.21) | 1519 (99.48) | |||
| Rheumatoid | 374 (0.32) | 312 (0.33) | 41 (0.49) | 13 (1.79) | 8 (0.52) | |||
| Smoking History | 15720 (13.39) | 13000 (12.41) | 2459 (24.67) | <0.001 | 114 (12.6) | 0.869 | 147 (8.06) | <0.001 |
| General Anesthesia | 66106 (56.31) | 58305 (55.74) | 6430 (64.6) | <0.001 | 527 (58.23) | 0.133 | 844 (46.3) | <0.001 |
| COPD | 4788 (4.08) | 4323 (4.13) | 409 (4.1) | 0.902 | 27 (2.98) | 0.084 | 29 (1.59) | <0.001 |
| Chronic Steroid Use | 4352 (3.71) | 3680 (3.51) | 514 (5.16) | <0.001 | 75 (8.29) | <0.001 | 83 (4.55) | 0.017 |
| Dialysis | 272 (0.23) | 165 (0.16) | 94 (0.94) | <0.001 | 4 (0.44) | 0.033 | 9 (0.49) | <0.001 |
| Cancer | 361 (0.31) | 313 (0.3) | 32 (0.32) | 0.7 | 7 (0.77) | 0.01 | 9 (0.49) | 0.134 |
| Low Hematocrit (<30) | 1134 (0.97) | 871 (0.86) | 241 (2.48) | <0.001 | 12 (1.37) | 0.101 | 10 (0.56) | 0.172 |
| High Creatinine (≥2 mg/dL) | 7868 (6.7) | 6881 (6.77) | 745 (7.68) | 0.001 | 80 (9.15) | 0.005 | 162 (9.05) | <0.001 |
| Low Albumin (<3.5 g/dL) | 2615 (2.23) | 2240 (2.21) | 321 (3.31) | <0.001 | 25 (2.86) | 0.19 | 29 (1.62) | 0.093 |
| Low Platelets (<100 billion cells/L) | 689 (0.59) | 608 (0.58) | 63 (0.63) | 0.521 | 6 (0.66) | 0.746 | 12 (0.66) | 0.667 |
| High Bilirubin (≥2 mg/dL) | 59411 (50.61) | 53044 (50.66) | 4936 (49.51) | 0.029 | 386 (42.65) | <0.001 | 1045 (57.29) | <0.001 |
*All P Values indicate comparisons to White THA reference group.
3.2. Univariate analysis
Out of the 117,389 patients in the NSQIP database, 12,604 (10.74%) experienced serious medical morbidity, with a total of 157 (0.13%) deaths within 30 days of surgery. Serious morbidities included surgical site infection (n = 11, 0.01%), respiratory dysfunction (n = 208, 0.18%), cardiac complications (n = 1,106, 0.94%), postoperative anemia requiring transfusion (n = 11,412, 9.72%), or sepsis diagnosis (n = 342, 0.29%). Notably, postoperative transfusion accounted for the vast majority of these negative outcomes.
Significant unadjusted differences were observed when comparing Black, Hispanic, and Asians to the non-Hispanic White reference group. Blacks were more likely to experience death or a serious morbidity when analyzed as a whole as a result of their surgery. Differences were seen in operative time and length of stay between each racial group and the reference group. We observed differences in discharge location, with non-Hispanic Whites having higher discharge rates to home when compared to the Black and Hispanic groups. There was no significant difference in discharge location between non-Hispanic White and Asian patients (Insert Table 2).
Table 2.
Univariate analysis of all total hip arthroplasty complications by race.
| Overall n (%) | White THA n (%) | Black THA n (%) | P Value* | Hispanic THA n (%) | P Value* | Asian THA n (%) | P Value* | |
|---|---|---|---|---|---|---|---|---|
| Death or serious morbidity | 12604 (10.74) | 10961 (10.79) | 1273 (13.12) | <0.001 | 110 (12.59) | 0.089 | 260 (13.42) | <0.001 |
| Death | 157 (0.13) | 137 (0.13) | 16 (0.16) | 0.438 | 1 (0.11) | 0.866 | 3 (0.16) | 0.694 |
| Serious morbidity | 12572 (10.71) | 10931 (10.76) | 1273 (13.12) | <0.001 | 110 (12.59) | 0.083 | 258 (14.41) | <0.001 |
| Surgical Site Infection | 11 (0.01) | 9 (0.01) | 2 (0.02) | 0.27 | 0 (0) | 0.779 | 0 (0) | 0.688 |
| Respiratory | 208 (0.18) | 177 (0.17) | 28 (0.28) | 0.012 | 1 (0.11) | 0.669 | 2 (0.11) | 0.539 |
| Cardiac | 1106 (0.94) | 953 (0.91) | 129 (1.29) | <0.001 | 13 (1.44) | 0.098 | 11 (0.6) | 0.17 |
| Postop Transfusion | 11412 (9.72) | 9930 (9.48) | 1136 (11.4) | <0.001 | 97 (10.72) | 0.207 | 249 (13.65) | <0.001 |
| Sepsis | 342 (0.29) | 290 (0.28) | 44 (0.44) | 0.004 | 5 (0.55) | 0.118 | 3 (0.16) | 0.363 |
| Time variables | ||||||||
| Operative Time | <0.001 | <0.001 | <0.001 | |||||
| Expected | 99989 (85.18) | 90009 (85.96) | 7760 (77.84) | 715 (79.01) | 1505 (82.51) | |||
| Long Operative Time | 17422 (14.84) | 14704 (14.04) | 2209 (22.16) | 190 (20.99) | 319 (17.49) | |||
| Total length of stay | <0.001 | 0.001 | 0.023 | |||||
| 0–5 days | 110492 (94.12) | 98889 (94.44) | 9072 (91) | 831 (91.82) | 1700 (93.2) | |||
| >5 days | 6919 (5.89) | 5824 (5.56) | 897 (9) | 74 (8.18) | 124 (6.8) | |||
| Discharge To | <0.001 | 0.007 | 0.587 | |||||
| Non-Home Facility | 26194 (22.31) | 22738 (23.14) | 2826 (29.93) | 232 (27.07) | 398 (22.59) | |||
| Home | 84138 (71.67) | 75532 (76.86) | 6617 (70.07) | 625 (72.93) | 1364 (77.41) | |||
| Readmission Within 30 Days | 3968 (3.38) | 3503 (3.6) | 381 (4.11) | 0.013 | 37 (4.36) | 0.239 | 47 (2.75) | 0.062 |
| Required Reoperation | 2224 (1.89) | 1970 (2.01) | 213 (2.26) | 0.099 | 18 (2.1) | 0.844 | 23 (1.31) | 0.038 |
*All P Values indicate comparisons to White THA reference group.
Further analysis of operative time showed that non-Hispanic White patients had the lowest mean operative time (94.0 min) compared to Black (105.0 min), Hispanic (105.3 min), and Asian (99.0 min) patients. Similar trends were observed when comparing BMI, with the non-Hispanic White group having significantly lower BMI (30.2) than the Black (31.7) and the Hispanic (31.1) groups Insert Table 3).
Table 3.
Comparison of average operative variables by race.
| White THA | Black THA | P Value* | Hispanic THA | P Value* | Asian THA | P Value* | |
|---|---|---|---|---|---|---|---|
| Operative time, min | 94.0 | 105.0 | <0.001 | 105.3 | <0.001 | 99.0 | <0.001 |
| Age, years | 65.0 | 59.5 | <0.001 | 57.7 | <0.001 | 64.7 | 0.3636 |
| Length of Stay, days | 2.7 | 3.0 | <0.001 | 2.9 | 0.0119 | 2.7 | 0.9532 |
| Body Mass Index, kg/m∧2 | 30.2 | 31.7 | <0.001 | 31.1 | <0.001 | 26.8 | <0.001 |
*All P Values indicate comparisons to White THA reference group.
3.3. Propensity score-matched model
Propensity score-matching was performed to create three separate cohorts comparing non-Hispanic White and Black patients, non-Hispanic White and Hispanic patients, and non-Hispanic White and Asian patients with total cohort sizes of 18,748, 1,704, and 3,442, respectively. This matching demonstrated acceptable control of covariates compared with the overall cohort (Insert Table 4).
Table 4.
Patient characteristics of propensity score matched cohorts.
| White (vs. Black) n (%) | Black n (%) | P Value | White (vs. Hispanic), n (%) | Hispanic n (%) | P Value | White (vs. Asian) n (%) | Asian n (%) | P Value | |
|---|---|---|---|---|---|---|---|---|---|
| Sex | 1 | 0.961 | 1 | ||||||
| Male | 4420 (47.15) | 4420 (47.15) | 409 (48) | 408 (47.89) | 565 (32.83) | 565 (32.83) | |||
| Female | 4954 (52.85) | 4954 (52.85) | 443 (52) | 444 (52.11) | 1156 (67.17) | 1156 (67.17) | |||
| Age | 1 | 0.953 | 1 | ||||||
| < 70 yr | 7510 (80.12) | 7510 (80.12) | 673 (78.99) | 672 (78.87) | 1109 (64.44) | 1109 (64.44) | |||
| ≥ 70 yr | 1864 (19.88) | 1864 (19.88) | 179 (21.01) | 180 (21.13) | 612 (35.56) | 612 (35.56) | |||
| Inpatient | |||||||||
| Functional status | 1 | 0.891 | 1 | ||||||
| Independent | 9167 (97.79) | 9167 (97.79) | 825 (96.83) | 824 (96.71) | 1681 (97.68) | 1681 (97.68) | |||
| Partially Dependent | 203 (2.17) | 203 (2.17) | 27 (3.17) | 28 (3.29) | 40 (2.32) | 40 (2.32) | |||
| Totally Dependent | 4 (0.04) | 4 (0.04) | 0 (0) | 0 (0) | |||||
| ASA class | 1 | 0.961 | 1 | ||||||
| Low | 4551 (48.55) | 4551 (48.55) | 488 (57.28) | 489 (57.39) | 1172 (68.1) | 1172 (68.1) | |||
| High | 4823 (51.45) | 4823 (51.45) | 364 (42.72) | 363 (42.61) | 549 (31.9) | 549 (31.9) | |||
| Comorbidities | |||||||||
| Obese (BMI >30 kg/m∧2) | 5338 (56.94) | 5338 (56.94) | 1 | 456 (53.52) | 456 (53.52) | 1 | 434 (25.22) | 434 (25.22) | 1 |
| Diabetes | 1637 (17.46) | 1637 (17.46) | 1 | 152 (17.84) | 152 (17.84) | 1 | 222 (12.9) | 222 (12.9) | 1 |
| Hypertension Medication | 6500 (69.34) | 6500 (69.34) | 1 | 421 (49.41) | 422 (49.53) | 0.961 | 981 (57) | 981 (57) | 1 |
| Smoker | 2259 (24.1) | 2259 (24.1) | 1 | 108 (12.68) | 108 (12.68) | 1 | 139 (8.08) | 139 (8.08) | 1 |
| COPD | 346 (3.69) | 346 (3.69) | 1 | 26 (3.05) | 26 (3.05) | 1 | 23 (1.34) | 23 (1.34) | 1 |
| Chronic steroid | 423 (3.51) | 423 (3.51) | 1 | 66 (7.75) | 66 (7.75) | 1 | 70 (4.07) | 70 (4.07) | 1 |
| Dialysis | 31 (0.33) | 31 (0.33) | 1 | 2 (0.23) | 2 (0.23) | 1 | 3 (0.17) | 3 (0.17) | 1 |
| Cancer | 15 (0.16) | 15 (0.16) | 1 | 2 (0.23) | 2 (0.23) | 1 | 7 (0.41) | 7 (0.41) | 1 |
| Low Hematocrit (<30) | 136 (1.45) | 136 (1.45) | 1 | 7 (0.82) | 7 (0.82) | 1 | 6 (0.35) | 6 (0.35) | 1 |
| High Creatinine (≥2 mg/dL) | 645 (6.88) | 645 (6.88) | 1 | 74 (8.69) | 74 (8.69) | 1 | 150 (8.72) | 150 (8.72) | 1 |
| Low Albumin (<3.5 g/dL) | 251 (2.68) | 251 (2.68) | 1 | 20 (2.35) | 21 (2.46) | 0.874 | 20 (1.16) | 20 (1.16) | 1 |
| Low Platelets (<100 billion cells/L) | 41 (0.44) | 41 (0.44) | 1 | 4 (0.47) | 3 (0.35) | 0.705 | 5 (0.29) | 5 (0.29) | 1 |
| High Bilirubin (≥2 mg/dL) | 4639 (49.49) | 4639 (49.49) | 1 | 370 (43.43) | 369 (43.31) | 0.961 | 984 (57.18) | 984 (57.18) | 1 |
Univariate analysis on our propensity score-matched cohort showed that serious medical co-morbidities and total length of hospital stay was higher among black patients compared with non-Hispanic Whites. Additionally, Black and Hispanic groups experienced discharge to a non-home facility at a higher rate than the non-Hispanic White group. It was also noted that the Asian group had a significantly lower rate of readmission and reoperation rate than non-Hispanic white group (Insert Table 5).
Table 5.
Outcomes of propensity score matched cohorts.
| White (vs. Black) n (%) | Black n (%) | P Value | White (vs. Hispanic) n (%) | Hispanic, n (%) | P Value | White (vs. Asian) n (%) | Asian n (%) | P Value | |
|---|---|---|---|---|---|---|---|---|---|
| Death or serious morbidity | 949 (10.12) | 1170 (12.48) | <0.001 | 94 (11.03) | 101 (11.85) | 0.594 | 212 (12.32) | 247 (14.35) | 0.079 |
| Death | 9 (0.1) | 13 (0.14) | 0.393 | 0 (0) | 0 (0) | 1 | 1 (0.06) | 3 (0.17) | 0.317 |
| Serious morbidity | 947 (10.1) | 1170 (12.48) | <0.001 | 94 (11.03) | 101 (11.85) | 0.594 | 212 (12.32) | 245 (14.24) | 0.097 |
| Surgical Site Infection | 2 (0.02) | 1 (0.01) | 0.557 | 0 (0) | 0 (0) | 1 | 0 (0) | 0 (0) | 1 |
| Respiratory | 16 (0.17) | 22 (0.23) | 0.33 | 1 (0.12) | 1 (0.12) | 1 | 3 (0.17) | 2 (0.12) | 0.654 |
| Cardiac | 59 (0.63) | 117 (1.25) | <0.001 | 5 (0.59) | 12 (1.41) | 0.088 | 9 (0.52) | 11 (0.64) | 0.654 |
| Post Operative Transfusion | 876 (9.34) | 1043 (11.13) | <0.001 | 87 (10.21) | 88 (10.33) | 0.936 | 198 (11.5) | 236 (13.71) | 0.051 |
| Sepsis | 20 (0.21) | 35 (0.37) | 0.043 | 1 (0.12) | 4 (0.47) | 0.179 | 6 (0.35) | 2 (0.12) | 0.157 |
| Time variables | |||||||||
| Operative Time | <0.001 | 0.01 | <0.001 | ||||||
| Expected Operative Time | 7978 (85.11) | 7329 (78.18) | 719 (84.39) | 678 (79.58) | 1520 (88.32) | 1421 (82.57) | |||
| Long Operative Time (1 SD > Mean) | 1396 (14.89) | 2045 (21.82) | 133 (15.61) | 174 (20.42) | 201 (11.68) | 300 (17.43) | |||
| Total length of stay | <0.001 | 0.198 | 0.235 | ||||||
| 0–5 days | 8860 (94.52) | 8610 (91.85) | 804 (94.37) | 791 (92.84) | 1633 (94.89) | 1617 (93.96) | |||
| >5 days | 514 (5.48) | 764 (8.15) | 48 (5.63) | 61 (7.16) | 88 (5.11) | 104 (6.04) | |||
| Discharge | <0.001 | <0.001 | 0.527 | ||||||
| Discharged to Non-Home Facility | 1903 (21.07) | 2689 (29.45) | 158 (19.04) | 223 (26.71) | 382 (22.94) | 373 (22.03) | |||
| Discharged to Home | 7130 (78.93) | 6442 (70.55) | 672 (80.96) | 612 (73.29) | 1283 (77.06) | 1320 (77.97) | |||
| Readmission Within 30 Days | 326 (3.64) | 355 (3.96) | 0.267 | 36 (4.37) | 34 (4.11) | 0.791 | 60 (3.65) | 40 (2.4) | 0.036 |
| Required Reoperation | 201 (2.23) | 206 (2.26) | 0.894 | 20 (2.41) | 17 (2.04) | 0.608 | 37 (2.23) | 22 (1.3) | 0.041 |
3.4. Multivariate model
In a logistic, reverse stepwise regression model, there was a similar significant association between patient race and increased death or serious medical morbidity when comparing Black to non-Hispanic White patients (p < 0.001). These differences were not seen in regards to the other races examined. However, differences were seen in operative time, with all racial groups having increased procedural time in comparison to the non-Hispanic white reference group. Additionally, Black and Hispanic ethnicity was associated with decreased discharge rates to home (p < 0.001). [Insert Table 6.].
Table 6.
Impact of race on outcomes compared to non-hispanic whites after multivariate analysis.
| Outcomes | Black |
Hispanic |
Asian |
|||
|---|---|---|---|---|---|---|
| OR | P Value* | OR | P Value* | OR | P Value* | |
| Complications | ||||||
| Death or serious morbidity | 1.27 | <0.001 | 1.08 | 0.594 | 1.19 | 0.08 |
| Death | 1.45 | 0.396 | N/A | N/A | 3.00 | 0.341 |
| Serious morbidity | 1.27 | <0.001 | 1.08 | 0.594 | 1.18 | 0.098 |
| Time Variables | ||||||
| Long Operation Time | 1.59 | <0.001 | 2.95 | 0.006 | 1.60 | <0.001 |
| Length of Stay >5 days | 1.53 | <0.001 | 1.29 | 0.199 | 1.19 | 0.235 |
| Reoperation | 1.01 | 0.894 | 0.84 | 0.608 | 0.58 | 0.044 |
| Readmission Within 30 Days | 1.09 | 0.267 | 0.94 | 0.791 | 0.65 | 0.038 |
| Discharge Home | 0.64 | <0.001 | 0.65 | <0.001 | 1.05 | 0.527 |
*All P Values indicate comparisons to White THA reference group.
4. Discussion
Using the NSQIP database to assemble a large, national cohort of American THA patients, we were able to evaluate the impact of race on 30-day post surgical complications, and other important perioperative quality metrics. When using propensity score matched comparisons between racial groups, significant differences between Black and non-Hispanic Whites were observed in serious medical morbidity, rate of prolonged operative time, total length of stay exceeding 5 days, and discharge to non-home facility. Disparities between Hispanic and non-Hispanic Whites were observed for rate of prolonged operative time and discharge to non-home facility. Asians had higher rates of prolonged operative time compared to non-Hispanic Whites, but had significantly lower readmission and reoperation rates within 30 days of THA. These discrepancies were all confirmed with multivariate analysis.
Similar disparities with complication rates between Black, Hispanic and non-Hispanic White patients have been shown in the literature, however a comprehensive study comparing multiple racial groups using our rigorous statistical methodology has not been previously attempted. Additionally, our report of decreased rate of readmission and re-operation among Asians has not been previously reported.
Discrepancies in rates of discharge to home compared to non-home facility were observed between both Black and Hispanic groups when compared to the non-Hispanic White group. Differences in discharge disposition between blacks and non-Hispanic Whites have been confirmed in previous studies.19 Discharge to a non-home facility following elective procedures has been shown to worsen clinical outcomes,20 and is associated with increased risk of complications and 30-day readmissions.21 This discrepancy in discharge location could be influencing differences observed in our cohort.
A limitation of our study was that our assessment of complications only included the first 30 days after THA. Additionally, our study was limited because the majority of patients (89.18%) were listed as non-Hispanic White. The relatively few number of Black, Hispanic, and Asian patients limited our ability to make substantial claims when comparing populations. This is most likely in part due to the differences in utilization rates of arthroplasty in the United States.13 Additional factors, such as socioeconomic status, social support and regional differences in care could not be controlled for in this study, but undoubtedly play a role in healthcare related racial disparities. In addition, it is difficult to determine whether differences in trust, compliance or racial bias are a contributing factor to the differences noted.
Despite the NSQIPs limitations, including likely under-reporting of morbidities, using the NSQIP has been shown to be a reliable method of examining short-term complications following surgery.22,23 Furthermore, since the majority of surgical complications occur within 30 days of the original surgery, we do not believe that including long-term complications would have altered our results dramatically. Additionally, any potential underreporting among surgeons is likely to be consistent across racial groups. The NSQIP dataset is limited to general medical and administrative complications such as reoperation and readmission, so analysis of complications specific to THA, such as dislocation and periprosthetic fracture were unable to be evaluated. The dataset also lacks patient reported outcome or functional outcome measures.
Our results show profound differences in surgical outcomes based on race, even after controlling for comorbidities. Identification of patients at greater risk of complications can provide physicians a better estimate of operative risks. This work opens up the possibility for further study of these differences, as well as assessing the consistency of trends across a variety of both elective and non-elective surgical procedures. Future research may focus on identifying differences in functional and patient reported outcomes between racial groups following THA.
Declaration of competing interest
Mr. Johnson has nothing to disclose.
Dr. Sloan has nothing to disclose.
Dr. Serra Lopez has nothing to disclose.
Dr. Andah has nothing to disclose.
Dr. Sheth reports consultation fees from Zimmer Biomet, consultation fees from Medacta, consultation fees from Smith and Nephew, outside the submitted work.
Dr. Nelson reports consultation fees from Exactech, consultation fees from Zimmer Biomet, outside the submitted work.
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