Socioeconomic factors affecting outcomes in total shoulder arthroplasty
Background: A lack of comprehensive research on socioeconomic factors affecting total shoulder arthroplasty (TSA) outcomes has demonstrated the need for further study. The purpose of this study is to determine the effects of socioeconomic factors such as ethnicity, income, and insurance status on th...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Schell, Lauren E. [verfasserIn] Kunkle, Bryce F. [verfasserIn] Barfield, William R. [verfasserIn] Eichinger, Josef K. [verfasserIn] Friedman, Richard J. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Seminars in arthroplasty - Philadelphia, Pa. : Elsevier, 2003, 34, Seite 156-165 |
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| Übergeordnetes Werk: |
volume:34 ; pages:156-165 |
| DOI / URN: |
10.1053/j.sart.2023.09.011 |
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| Katalog-ID: |
ELV067082378 |
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| 520 | |a Background: A lack of comprehensive research on socioeconomic factors affecting total shoulder arthroplasty (TSA) outcomes has demonstrated the need for further study. The purpose of this study is to determine the effects of socioeconomic factors such as ethnicity, income, and insurance status on the outcomes following TSA.Methods: All anatomic TSA and reverse TSA cases from the National Inpatient Sample (NIS; N = 128,376) database from 2011 to 2019 as well as the Nationwide Readmission Database (NRD; N = 103,023) from 2010 to 2019 were analyzed. Self-identified ethnicities assessed in NIS included Caucasian (CC), African American (AA), and Hispanic (H), and ethnicities were compared to Caucasians. NRD cases were assessed by insurance status (Medicare, Medicaid, and private) and zip code income Quartiles (Q1-4, with Q1 being the lowest). Insurance types and Q1-3 were compared to private insurance and Q4, respectively. Demographic data, quantitative variables, and binary categorical variables were analyzed using chi-square test of independence, one-way ANOVA with Tukey-Kramer post hoc analyses, and binary logistic regression, respectively.Results: For NIS, AA had the highest percent Q1 and comorbidities of all ethnicities (P < .001), increased lengths of stay and hospital stay extensions (both P < .001). The majority of H were Q1 (P < .001) with increased comorbidities (P < .001), lengths of stay (P < .001), stay extensions (P = .027) and complications (P = .043). For NRD, Medicare patients had a 1.5 times higher mean comorbidity score (P < .001) and increased risk of complication (P = .007), readmission (P < .001), revision (P = .028), hospital stay extension (P < .001), and discharge to a new facility (P < .001). Similarly, Medicaid patients had a 1.6 times increased mean comorbidity score (P < .001), and the highest risk of the following adverse outcomes: length of stay extension (odds ratio [OR]: 1.43, P < .001), complication (OR: 1.24, P = .017), and readmission (OR: 1.18; P = .041). Additionally, they had an increased risk of discharge to a new facility (OR: 1.78, P < .001). Comparing TSA patients in the Q1-3 to Q4, first quartile income was significantly associated with increased risk of hospital stay extension (P = .043), complication (P < .001), and readmission (P < .001). Second and third quartile patients had increased risks of any complication (Q2: P = .003; Q3: P = .016).Conclusion: The socioeconomic factors studied - ethnicity (AA and H), zip code income (Q1, Q2, and Q3), and insurance status (Medicare or Medicaid) - were all shown to have significantly increased risk for adverse outcomes following TSA. Private insurance status, CC, and zip code income Q4 were all predictive of significantly less adverse outcomes. Further study is needed to assess specific social differences associated with these results. | ||
| 650 | 4 | |a Shoulder | |
| 650 | 4 | |a Arthroplasty | |
| 650 | 4 | |a Socioeconomic factors | |
| 650 | 4 | |a Insurance | |
| 650 | 4 | |a Payor | |
| 650 | 4 | |a Ethnicity | |
| 650 | 4 | |a Income | |
| 700 | 1 | |a Kunkle, Bryce F. |e verfasserin |4 aut | |
| 700 | 1 | |a Barfield, William R. |e verfasserin |4 aut | |
| 700 | 1 | |a Eichinger, Josef K. |e verfasserin |0 (orcid)0000-0001-8563-7307 |4 aut | |
| 700 | 1 | |a Friedman, Richard J. |e verfasserin |0 (orcid)0000-0002-5641-470X |4 aut | |
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10.1053/j.sart.2023.09.011 doi (DE-627)ELV067082378 (ELSEVIER)S1045-4527(23)00163-3 DE-627 ger DE-627 rda eng 610 VZ 44.83 bkl Schell, Lauren E. verfasserin (orcid)0009-0001-5271-4481 aut Socioeconomic factors affecting outcomes in total shoulder arthroplasty 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: A lack of comprehensive research on socioeconomic factors affecting total shoulder arthroplasty (TSA) outcomes has demonstrated the need for further study. The purpose of this study is to determine the effects of socioeconomic factors such as ethnicity, income, and insurance status on the outcomes following TSA.Methods: All anatomic TSA and reverse TSA cases from the National Inpatient Sample (NIS; N = 128,376) database from 2011 to 2019 as well as the Nationwide Readmission Database (NRD; N = 103,023) from 2010 to 2019 were analyzed. Self-identified ethnicities assessed in NIS included Caucasian (CC), African American (AA), and Hispanic (H), and ethnicities were compared to Caucasians. NRD cases were assessed by insurance status (Medicare, Medicaid, and private) and zip code income Quartiles (Q1-4, with Q1 being the lowest). Insurance types and Q1-3 were compared to private insurance and Q4, respectively. Demographic data, quantitative variables, and binary categorical variables were analyzed using chi-square test of independence, one-way ANOVA with Tukey-Kramer post hoc analyses, and binary logistic regression, respectively.Results: For NIS, AA had the highest percent Q1 and comorbidities of all ethnicities (P < .001), increased lengths of stay and hospital stay extensions (both P < .001). The majority of H were Q1 (P < .001) with increased comorbidities (P < .001), lengths of stay (P < .001), stay extensions (P = .027) and complications (P = .043). For NRD, Medicare patients had a 1.5 times higher mean comorbidity score (P < .001) and increased risk of complication (P = .007), readmission (P < .001), revision (P = .028), hospital stay extension (P < .001), and discharge to a new facility (P < .001). Similarly, Medicaid patients had a 1.6 times increased mean comorbidity score (P < .001), and the highest risk of the following adverse outcomes: length of stay extension (odds ratio [OR]: 1.43, P < .001), complication (OR: 1.24, P = .017), and readmission (OR: 1.18; P = .041). Additionally, they had an increased risk of discharge to a new facility (OR: 1.78, P < .001). Comparing TSA patients in the Q1-3 to Q4, first quartile income was significantly associated with increased risk of hospital stay extension (P = .043), complication (P < .001), and readmission (P < .001). Second and third quartile patients had increased risks of any complication (Q2: P = .003; Q3: P = .016).Conclusion: The socioeconomic factors studied - ethnicity (AA and H), zip code income (Q1, Q2, and Q3), and insurance status (Medicare or Medicaid) - were all shown to have significantly increased risk for adverse outcomes following TSA. Private insurance status, CC, and zip code income Q4 were all predictive of significantly less adverse outcomes. Further study is needed to assess specific social differences associated with these results. Shoulder Arthroplasty Socioeconomic factors Insurance Payor Ethnicity Income Kunkle, Bryce F. verfasserin aut Barfield, William R. verfasserin aut Eichinger, Josef K. verfasserin (orcid)0000-0001-8563-7307 aut Friedman, Richard J. verfasserin (orcid)0000-0002-5641-470X aut Enthalten in Seminars in arthroplasty Philadelphia, Pa. : Elsevier, 2003 34, Seite 156-165 Online-Ressource (DE-627)521469325 (DE-600)2260910-6 (DE-576)336961561 1558-4437 nnns volume:34 pages:156-165 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.83 Rheumatologie Orthopädie VZ AR 34 156-165 |
| spelling |
10.1053/j.sart.2023.09.011 doi (DE-627)ELV067082378 (ELSEVIER)S1045-4527(23)00163-3 DE-627 ger DE-627 rda eng 610 VZ 44.83 bkl Schell, Lauren E. verfasserin (orcid)0009-0001-5271-4481 aut Socioeconomic factors affecting outcomes in total shoulder arthroplasty 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: A lack of comprehensive research on socioeconomic factors affecting total shoulder arthroplasty (TSA) outcomes has demonstrated the need for further study. The purpose of this study is to determine the effects of socioeconomic factors such as ethnicity, income, and insurance status on the outcomes following TSA.Methods: All anatomic TSA and reverse TSA cases from the National Inpatient Sample (NIS; N = 128,376) database from 2011 to 2019 as well as the Nationwide Readmission Database (NRD; N = 103,023) from 2010 to 2019 were analyzed. Self-identified ethnicities assessed in NIS included Caucasian (CC), African American (AA), and Hispanic (H), and ethnicities were compared to Caucasians. NRD cases were assessed by insurance status (Medicare, Medicaid, and private) and zip code income Quartiles (Q1-4, with Q1 being the lowest). Insurance types and Q1-3 were compared to private insurance and Q4, respectively. Demographic data, quantitative variables, and binary categorical variables were analyzed using chi-square test of independence, one-way ANOVA with Tukey-Kramer post hoc analyses, and binary logistic regression, respectively.Results: For NIS, AA had the highest percent Q1 and comorbidities of all ethnicities (P < .001), increased lengths of stay and hospital stay extensions (both P < .001). The majority of H were Q1 (P < .001) with increased comorbidities (P < .001), lengths of stay (P < .001), stay extensions (P = .027) and complications (P = .043). For NRD, Medicare patients had a 1.5 times higher mean comorbidity score (P < .001) and increased risk of complication (P = .007), readmission (P < .001), revision (P = .028), hospital stay extension (P < .001), and discharge to a new facility (P < .001). Similarly, Medicaid patients had a 1.6 times increased mean comorbidity score (P < .001), and the highest risk of the following adverse outcomes: length of stay extension (odds ratio [OR]: 1.43, P < .001), complication (OR: 1.24, P = .017), and readmission (OR: 1.18; P = .041). Additionally, they had an increased risk of discharge to a new facility (OR: 1.78, P < .001). Comparing TSA patients in the Q1-3 to Q4, first quartile income was significantly associated with increased risk of hospital stay extension (P = .043), complication (P < .001), and readmission (P < .001). Second and third quartile patients had increased risks of any complication (Q2: P = .003; Q3: P = .016).Conclusion: The socioeconomic factors studied - ethnicity (AA and H), zip code income (Q1, Q2, and Q3), and insurance status (Medicare or Medicaid) - were all shown to have significantly increased risk for adverse outcomes following TSA. Private insurance status, CC, and zip code income Q4 were all predictive of significantly less adverse outcomes. Further study is needed to assess specific social differences associated with these results. Shoulder Arthroplasty Socioeconomic factors Insurance Payor Ethnicity Income Kunkle, Bryce F. verfasserin aut Barfield, William R. verfasserin aut Eichinger, Josef K. verfasserin (orcid)0000-0001-8563-7307 aut Friedman, Richard J. verfasserin (orcid)0000-0002-5641-470X aut Enthalten in Seminars in arthroplasty Philadelphia, Pa. : Elsevier, 2003 34, Seite 156-165 Online-Ressource (DE-627)521469325 (DE-600)2260910-6 (DE-576)336961561 1558-4437 nnns volume:34 pages:156-165 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.83 Rheumatologie Orthopädie VZ AR 34 156-165 |
| allfields_unstemmed |
10.1053/j.sart.2023.09.011 doi (DE-627)ELV067082378 (ELSEVIER)S1045-4527(23)00163-3 DE-627 ger DE-627 rda eng 610 VZ 44.83 bkl Schell, Lauren E. verfasserin (orcid)0009-0001-5271-4481 aut Socioeconomic factors affecting outcomes in total shoulder arthroplasty 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: A lack of comprehensive research on socioeconomic factors affecting total shoulder arthroplasty (TSA) outcomes has demonstrated the need for further study. The purpose of this study is to determine the effects of socioeconomic factors such as ethnicity, income, and insurance status on the outcomes following TSA.Methods: All anatomic TSA and reverse TSA cases from the National Inpatient Sample (NIS; N = 128,376) database from 2011 to 2019 as well as the Nationwide Readmission Database (NRD; N = 103,023) from 2010 to 2019 were analyzed. Self-identified ethnicities assessed in NIS included Caucasian (CC), African American (AA), and Hispanic (H), and ethnicities were compared to Caucasians. NRD cases were assessed by insurance status (Medicare, Medicaid, and private) and zip code income Quartiles (Q1-4, with Q1 being the lowest). Insurance types and Q1-3 were compared to private insurance and Q4, respectively. Demographic data, quantitative variables, and binary categorical variables were analyzed using chi-square test of independence, one-way ANOVA with Tukey-Kramer post hoc analyses, and binary logistic regression, respectively.Results: For NIS, AA had the highest percent Q1 and comorbidities of all ethnicities (P < .001), increased lengths of stay and hospital stay extensions (both P < .001). The majority of H were Q1 (P < .001) with increased comorbidities (P < .001), lengths of stay (P < .001), stay extensions (P = .027) and complications (P = .043). For NRD, Medicare patients had a 1.5 times higher mean comorbidity score (P < .001) and increased risk of complication (P = .007), readmission (P < .001), revision (P = .028), hospital stay extension (P < .001), and discharge to a new facility (P < .001). Similarly, Medicaid patients had a 1.6 times increased mean comorbidity score (P < .001), and the highest risk of the following adverse outcomes: length of stay extension (odds ratio [OR]: 1.43, P < .001), complication (OR: 1.24, P = .017), and readmission (OR: 1.18; P = .041). Additionally, they had an increased risk of discharge to a new facility (OR: 1.78, P < .001). Comparing TSA patients in the Q1-3 to Q4, first quartile income was significantly associated with increased risk of hospital stay extension (P = .043), complication (P < .001), and readmission (P < .001). Second and third quartile patients had increased risks of any complication (Q2: P = .003; Q3: P = .016).Conclusion: The socioeconomic factors studied - ethnicity (AA and H), zip code income (Q1, Q2, and Q3), and insurance status (Medicare or Medicaid) - were all shown to have significantly increased risk for adverse outcomes following TSA. Private insurance status, CC, and zip code income Q4 were all predictive of significantly less adverse outcomes. Further study is needed to assess specific social differences associated with these results. Shoulder Arthroplasty Socioeconomic factors Insurance Payor Ethnicity Income Kunkle, Bryce F. verfasserin aut Barfield, William R. verfasserin aut Eichinger, Josef K. verfasserin (orcid)0000-0001-8563-7307 aut Friedman, Richard J. verfasserin (orcid)0000-0002-5641-470X aut Enthalten in Seminars in arthroplasty Philadelphia, Pa. : Elsevier, 2003 34, Seite 156-165 Online-Ressource (DE-627)521469325 (DE-600)2260910-6 (DE-576)336961561 1558-4437 nnns volume:34 pages:156-165 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.83 Rheumatologie Orthopädie VZ AR 34 156-165 |
| allfieldsGer |
10.1053/j.sart.2023.09.011 doi (DE-627)ELV067082378 (ELSEVIER)S1045-4527(23)00163-3 DE-627 ger DE-627 rda eng 610 VZ 44.83 bkl Schell, Lauren E. verfasserin (orcid)0009-0001-5271-4481 aut Socioeconomic factors affecting outcomes in total shoulder arthroplasty 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: A lack of comprehensive research on socioeconomic factors affecting total shoulder arthroplasty (TSA) outcomes has demonstrated the need for further study. The purpose of this study is to determine the effects of socioeconomic factors such as ethnicity, income, and insurance status on the outcomes following TSA.Methods: All anatomic TSA and reverse TSA cases from the National Inpatient Sample (NIS; N = 128,376) database from 2011 to 2019 as well as the Nationwide Readmission Database (NRD; N = 103,023) from 2010 to 2019 were analyzed. Self-identified ethnicities assessed in NIS included Caucasian (CC), African American (AA), and Hispanic (H), and ethnicities were compared to Caucasians. NRD cases were assessed by insurance status (Medicare, Medicaid, and private) and zip code income Quartiles (Q1-4, with Q1 being the lowest). Insurance types and Q1-3 were compared to private insurance and Q4, respectively. Demographic data, quantitative variables, and binary categorical variables were analyzed using chi-square test of independence, one-way ANOVA with Tukey-Kramer post hoc analyses, and binary logistic regression, respectively.Results: For NIS, AA had the highest percent Q1 and comorbidities of all ethnicities (P < .001), increased lengths of stay and hospital stay extensions (both P < .001). The majority of H were Q1 (P < .001) with increased comorbidities (P < .001), lengths of stay (P < .001), stay extensions (P = .027) and complications (P = .043). For NRD, Medicare patients had a 1.5 times higher mean comorbidity score (P < .001) and increased risk of complication (P = .007), readmission (P < .001), revision (P = .028), hospital stay extension (P < .001), and discharge to a new facility (P < .001). Similarly, Medicaid patients had a 1.6 times increased mean comorbidity score (P < .001), and the highest risk of the following adverse outcomes: length of stay extension (odds ratio [OR]: 1.43, P < .001), complication (OR: 1.24, P = .017), and readmission (OR: 1.18; P = .041). Additionally, they had an increased risk of discharge to a new facility (OR: 1.78, P < .001). Comparing TSA patients in the Q1-3 to Q4, first quartile income was significantly associated with increased risk of hospital stay extension (P = .043), complication (P < .001), and readmission (P < .001). Second and third quartile patients had increased risks of any complication (Q2: P = .003; Q3: P = .016).Conclusion: The socioeconomic factors studied - ethnicity (AA and H), zip code income (Q1, Q2, and Q3), and insurance status (Medicare or Medicaid) - were all shown to have significantly increased risk for adverse outcomes following TSA. Private insurance status, CC, and zip code income Q4 were all predictive of significantly less adverse outcomes. Further study is needed to assess specific social differences associated with these results. Shoulder Arthroplasty Socioeconomic factors Insurance Payor Ethnicity Income Kunkle, Bryce F. verfasserin aut Barfield, William R. verfasserin aut Eichinger, Josef K. verfasserin (orcid)0000-0001-8563-7307 aut Friedman, Richard J. verfasserin (orcid)0000-0002-5641-470X aut Enthalten in Seminars in arthroplasty Philadelphia, Pa. : Elsevier, 2003 34, Seite 156-165 Online-Ressource (DE-627)521469325 (DE-600)2260910-6 (DE-576)336961561 1558-4437 nnns volume:34 pages:156-165 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.83 Rheumatologie Orthopädie VZ AR 34 156-165 |
| allfieldsSound |
10.1053/j.sart.2023.09.011 doi (DE-627)ELV067082378 (ELSEVIER)S1045-4527(23)00163-3 DE-627 ger DE-627 rda eng 610 VZ 44.83 bkl Schell, Lauren E. verfasserin (orcid)0009-0001-5271-4481 aut Socioeconomic factors affecting outcomes in total shoulder arthroplasty 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: A lack of comprehensive research on socioeconomic factors affecting total shoulder arthroplasty (TSA) outcomes has demonstrated the need for further study. The purpose of this study is to determine the effects of socioeconomic factors such as ethnicity, income, and insurance status on the outcomes following TSA.Methods: All anatomic TSA and reverse TSA cases from the National Inpatient Sample (NIS; N = 128,376) database from 2011 to 2019 as well as the Nationwide Readmission Database (NRD; N = 103,023) from 2010 to 2019 were analyzed. Self-identified ethnicities assessed in NIS included Caucasian (CC), African American (AA), and Hispanic (H), and ethnicities were compared to Caucasians. NRD cases were assessed by insurance status (Medicare, Medicaid, and private) and zip code income Quartiles (Q1-4, with Q1 being the lowest). Insurance types and Q1-3 were compared to private insurance and Q4, respectively. Demographic data, quantitative variables, and binary categorical variables were analyzed using chi-square test of independence, one-way ANOVA with Tukey-Kramer post hoc analyses, and binary logistic regression, respectively.Results: For NIS, AA had the highest percent Q1 and comorbidities of all ethnicities (P < .001), increased lengths of stay and hospital stay extensions (both P < .001). The majority of H were Q1 (P < .001) with increased comorbidities (P < .001), lengths of stay (P < .001), stay extensions (P = .027) and complications (P = .043). For NRD, Medicare patients had a 1.5 times higher mean comorbidity score (P < .001) and increased risk of complication (P = .007), readmission (P < .001), revision (P = .028), hospital stay extension (P < .001), and discharge to a new facility (P < .001). Similarly, Medicaid patients had a 1.6 times increased mean comorbidity score (P < .001), and the highest risk of the following adverse outcomes: length of stay extension (odds ratio [OR]: 1.43, P < .001), complication (OR: 1.24, P = .017), and readmission (OR: 1.18; P = .041). Additionally, they had an increased risk of discharge to a new facility (OR: 1.78, P < .001). Comparing TSA patients in the Q1-3 to Q4, first quartile income was significantly associated with increased risk of hospital stay extension (P = .043), complication (P < .001), and readmission (P < .001). Second and third quartile patients had increased risks of any complication (Q2: P = .003; Q3: P = .016).Conclusion: The socioeconomic factors studied - ethnicity (AA and H), zip code income (Q1, Q2, and Q3), and insurance status (Medicare or Medicaid) - were all shown to have significantly increased risk for adverse outcomes following TSA. Private insurance status, CC, and zip code income Q4 were all predictive of significantly less adverse outcomes. Further study is needed to assess specific social differences associated with these results. Shoulder Arthroplasty Socioeconomic factors Insurance Payor Ethnicity Income Kunkle, Bryce F. verfasserin aut Barfield, William R. verfasserin aut Eichinger, Josef K. verfasserin (orcid)0000-0001-8563-7307 aut Friedman, Richard J. verfasserin (orcid)0000-0002-5641-470X aut Enthalten in Seminars in arthroplasty Philadelphia, Pa. : Elsevier, 2003 34, Seite 156-165 Online-Ressource (DE-627)521469325 (DE-600)2260910-6 (DE-576)336961561 1558-4437 nnns volume:34 pages:156-165 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 44.83 Rheumatologie Orthopädie VZ AR 34 156-165 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">ELV067082378</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240217093110.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240217s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1053/j.sart.2023.09.011</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV067082378</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S1045-4527(23)00163-3</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">44.83</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Schell, Lauren E.</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0009-0001-5271-4481</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Socioeconomic factors affecting outcomes in total shoulder arthroplasty</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Background: A lack of comprehensive research on socioeconomic factors affecting total shoulder arthroplasty (TSA) outcomes has demonstrated the need for further study. The purpose of this study is to determine the effects of socioeconomic factors such as ethnicity, income, and insurance status on the outcomes following TSA.Methods: All anatomic TSA and reverse TSA cases from the National Inpatient Sample (NIS; N = 128,376) database from 2011 to 2019 as well as the Nationwide Readmission Database (NRD; N = 103,023) from 2010 to 2019 were analyzed. Self-identified ethnicities assessed in NIS included Caucasian (CC), African American (AA), and Hispanic (H), and ethnicities were compared to Caucasians. NRD cases were assessed by insurance status (Medicare, Medicaid, and private) and zip code income Quartiles (Q1-4, with Q1 being the lowest). Insurance types and Q1-3 were compared to private insurance and Q4, respectively. Demographic data, quantitative variables, and binary categorical variables were analyzed using chi-square test of independence, one-way ANOVA with Tukey-Kramer post hoc analyses, and binary logistic regression, respectively.Results: For NIS, AA had the highest percent Q1 and comorbidities of all ethnicities (P < .001), increased lengths of stay and hospital stay extensions (both P < .001). The majority of H were Q1 (P < .001) with increased comorbidities (P < .001), lengths of stay (P < .001), stay extensions (P = .027) and complications (P = .043). For NRD, Medicare patients had a 1.5 times higher mean comorbidity score (P < .001) and increased risk of complication (P = .007), readmission (P < .001), revision (P = .028), hospital stay extension (P < .001), and discharge to a new facility (P < .001). Similarly, Medicaid patients had a 1.6 times increased mean comorbidity score (P < .001), and the highest risk of the following adverse outcomes: length of stay extension (odds ratio [OR]: 1.43, P < .001), complication (OR: 1.24, P = .017), and readmission (OR: 1.18; P = .041). Additionally, they had an increased risk of discharge to a new facility (OR: 1.78, P < .001). Comparing TSA patients in the Q1-3 to Q4, first quartile income was significantly associated with increased risk of hospital stay extension (P = .043), complication (P < .001), and readmission (P < .001). Second and third quartile patients had increased risks of any complication (Q2: P = .003; Q3: P = .016).Conclusion: The socioeconomic factors studied - ethnicity (AA and H), zip code income (Q1, Q2, and Q3), and insurance status (Medicare or Medicaid) - were all shown to have significantly increased risk for adverse outcomes following TSA. Private insurance status, CC, and zip code income Q4 were all predictive of significantly less adverse outcomes. 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Schell, Lauren E. |
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610 VZ 44.83 bkl Socioeconomic factors affecting outcomes in total shoulder arthroplasty Shoulder Arthroplasty Socioeconomic factors Insurance Payor Ethnicity Income |
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Socioeconomic factors affecting outcomes in total shoulder arthroplasty |
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Socioeconomic factors affecting outcomes in total shoulder arthroplasty |
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10.1053/j.sart.2023.09.011 |
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socioeconomic factors affecting outcomes in total shoulder arthroplasty |
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Socioeconomic factors affecting outcomes in total shoulder arthroplasty |
| abstract |
Background: A lack of comprehensive research on socioeconomic factors affecting total shoulder arthroplasty (TSA) outcomes has demonstrated the need for further study. The purpose of this study is to determine the effects of socioeconomic factors such as ethnicity, income, and insurance status on the outcomes following TSA.Methods: All anatomic TSA and reverse TSA cases from the National Inpatient Sample (NIS; N = 128,376) database from 2011 to 2019 as well as the Nationwide Readmission Database (NRD; N = 103,023) from 2010 to 2019 were analyzed. Self-identified ethnicities assessed in NIS included Caucasian (CC), African American (AA), and Hispanic (H), and ethnicities were compared to Caucasians. NRD cases were assessed by insurance status (Medicare, Medicaid, and private) and zip code income Quartiles (Q1-4, with Q1 being the lowest). Insurance types and Q1-3 were compared to private insurance and Q4, respectively. Demographic data, quantitative variables, and binary categorical variables were analyzed using chi-square test of independence, one-way ANOVA with Tukey-Kramer post hoc analyses, and binary logistic regression, respectively.Results: For NIS, AA had the highest percent Q1 and comorbidities of all ethnicities (P < .001), increased lengths of stay and hospital stay extensions (both P < .001). The majority of H were Q1 (P < .001) with increased comorbidities (P < .001), lengths of stay (P < .001), stay extensions (P = .027) and complications (P = .043). For NRD, Medicare patients had a 1.5 times higher mean comorbidity score (P < .001) and increased risk of complication (P = .007), readmission (P < .001), revision (P = .028), hospital stay extension (P < .001), and discharge to a new facility (P < .001). Similarly, Medicaid patients had a 1.6 times increased mean comorbidity score (P < .001), and the highest risk of the following adverse outcomes: length of stay extension (odds ratio [OR]: 1.43, P < .001), complication (OR: 1.24, P = .017), and readmission (OR: 1.18; P = .041). Additionally, they had an increased risk of discharge to a new facility (OR: 1.78, P < .001). Comparing TSA patients in the Q1-3 to Q4, first quartile income was significantly associated with increased risk of hospital stay extension (P = .043), complication (P < .001), and readmission (P < .001). Second and third quartile patients had increased risks of any complication (Q2: P = .003; Q3: P = .016).Conclusion: The socioeconomic factors studied - ethnicity (AA and H), zip code income (Q1, Q2, and Q3), and insurance status (Medicare or Medicaid) - were all shown to have significantly increased risk for adverse outcomes following TSA. Private insurance status, CC, and zip code income Q4 were all predictive of significantly less adverse outcomes. Further study is needed to assess specific social differences associated with these results. |
| abstractGer |
Background: A lack of comprehensive research on socioeconomic factors affecting total shoulder arthroplasty (TSA) outcomes has demonstrated the need for further study. The purpose of this study is to determine the effects of socioeconomic factors such as ethnicity, income, and insurance status on the outcomes following TSA.Methods: All anatomic TSA and reverse TSA cases from the National Inpatient Sample (NIS; N = 128,376) database from 2011 to 2019 as well as the Nationwide Readmission Database (NRD; N = 103,023) from 2010 to 2019 were analyzed. Self-identified ethnicities assessed in NIS included Caucasian (CC), African American (AA), and Hispanic (H), and ethnicities were compared to Caucasians. NRD cases were assessed by insurance status (Medicare, Medicaid, and private) and zip code income Quartiles (Q1-4, with Q1 being the lowest). Insurance types and Q1-3 were compared to private insurance and Q4, respectively. Demographic data, quantitative variables, and binary categorical variables were analyzed using chi-square test of independence, one-way ANOVA with Tukey-Kramer post hoc analyses, and binary logistic regression, respectively.Results: For NIS, AA had the highest percent Q1 and comorbidities of all ethnicities (P < .001), increased lengths of stay and hospital stay extensions (both P < .001). The majority of H were Q1 (P < .001) with increased comorbidities (P < .001), lengths of stay (P < .001), stay extensions (P = .027) and complications (P = .043). For NRD, Medicare patients had a 1.5 times higher mean comorbidity score (P < .001) and increased risk of complication (P = .007), readmission (P < .001), revision (P = .028), hospital stay extension (P < .001), and discharge to a new facility (P < .001). Similarly, Medicaid patients had a 1.6 times increased mean comorbidity score (P < .001), and the highest risk of the following adverse outcomes: length of stay extension (odds ratio [OR]: 1.43, P < .001), complication (OR: 1.24, P = .017), and readmission (OR: 1.18; P = .041). Additionally, they had an increased risk of discharge to a new facility (OR: 1.78, P < .001). Comparing TSA patients in the Q1-3 to Q4, first quartile income was significantly associated with increased risk of hospital stay extension (P = .043), complication (P < .001), and readmission (P < .001). Second and third quartile patients had increased risks of any complication (Q2: P = .003; Q3: P = .016).Conclusion: The socioeconomic factors studied - ethnicity (AA and H), zip code income (Q1, Q2, and Q3), and insurance status (Medicare or Medicaid) - were all shown to have significantly increased risk for adverse outcomes following TSA. Private insurance status, CC, and zip code income Q4 were all predictive of significantly less adverse outcomes. Further study is needed to assess specific social differences associated with these results. |
| abstract_unstemmed |
Background: A lack of comprehensive research on socioeconomic factors affecting total shoulder arthroplasty (TSA) outcomes has demonstrated the need for further study. The purpose of this study is to determine the effects of socioeconomic factors such as ethnicity, income, and insurance status on the outcomes following TSA.Methods: All anatomic TSA and reverse TSA cases from the National Inpatient Sample (NIS; N = 128,376) database from 2011 to 2019 as well as the Nationwide Readmission Database (NRD; N = 103,023) from 2010 to 2019 were analyzed. Self-identified ethnicities assessed in NIS included Caucasian (CC), African American (AA), and Hispanic (H), and ethnicities were compared to Caucasians. NRD cases were assessed by insurance status (Medicare, Medicaid, and private) and zip code income Quartiles (Q1-4, with Q1 being the lowest). Insurance types and Q1-3 were compared to private insurance and Q4, respectively. Demographic data, quantitative variables, and binary categorical variables were analyzed using chi-square test of independence, one-way ANOVA with Tukey-Kramer post hoc analyses, and binary logistic regression, respectively.Results: For NIS, AA had the highest percent Q1 and comorbidities of all ethnicities (P < .001), increased lengths of stay and hospital stay extensions (both P < .001). The majority of H were Q1 (P < .001) with increased comorbidities (P < .001), lengths of stay (P < .001), stay extensions (P = .027) and complications (P = .043). For NRD, Medicare patients had a 1.5 times higher mean comorbidity score (P < .001) and increased risk of complication (P = .007), readmission (P < .001), revision (P = .028), hospital stay extension (P < .001), and discharge to a new facility (P < .001). Similarly, Medicaid patients had a 1.6 times increased mean comorbidity score (P < .001), and the highest risk of the following adverse outcomes: length of stay extension (odds ratio [OR]: 1.43, P < .001), complication (OR: 1.24, P = .017), and readmission (OR: 1.18; P = .041). Additionally, they had an increased risk of discharge to a new facility (OR: 1.78, P < .001). Comparing TSA patients in the Q1-3 to Q4, first quartile income was significantly associated with increased risk of hospital stay extension (P = .043), complication (P < .001), and readmission (P < .001). Second and third quartile patients had increased risks of any complication (Q2: P = .003; Q3: P = .016).Conclusion: The socioeconomic factors studied - ethnicity (AA and H), zip code income (Q1, Q2, and Q3), and insurance status (Medicare or Medicaid) - were all shown to have significantly increased risk for adverse outcomes following TSA. Private insurance status, CC, and zip code income Q4 were all predictive of significantly less adverse outcomes. Further study is needed to assess specific social differences associated with these results. |
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| title_short |
Socioeconomic factors affecting outcomes in total shoulder arthroplasty |
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| author2 |
Kunkle, Bryce F. Barfield, William R. Eichinger, Josef K. Friedman, Richard J. |
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Kunkle, Bryce F. Barfield, William R. Eichinger, Josef K. Friedman, Richard J. |
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| doi_str |
10.1053/j.sart.2023.09.011 |
| up_date |
2024-07-06T20:01:43.132Z |
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The purpose of this study is to determine the effects of socioeconomic factors such as ethnicity, income, and insurance status on the outcomes following TSA.Methods: All anatomic TSA and reverse TSA cases from the National Inpatient Sample (NIS; N = 128,376) database from 2011 to 2019 as well as the Nationwide Readmission Database (NRD; N = 103,023) from 2010 to 2019 were analyzed. Self-identified ethnicities assessed in NIS included Caucasian (CC), African American (AA), and Hispanic (H), and ethnicities were compared to Caucasians. NRD cases were assessed by insurance status (Medicare, Medicaid, and private) and zip code income Quartiles (Q1-4, with Q1 being the lowest). Insurance types and Q1-3 were compared to private insurance and Q4, respectively. Demographic data, quantitative variables, and binary categorical variables were analyzed using chi-square test of independence, one-way ANOVA with Tukey-Kramer post hoc analyses, and binary logistic regression, respectively.Results: For NIS, AA had the highest percent Q1 and comorbidities of all ethnicities (P < .001), increased lengths of stay and hospital stay extensions (both P < .001). The majority of H were Q1 (P < .001) with increased comorbidities (P < .001), lengths of stay (P < .001), stay extensions (P = .027) and complications (P = .043). For NRD, Medicare patients had a 1.5 times higher mean comorbidity score (P < .001) and increased risk of complication (P = .007), readmission (P < .001), revision (P = .028), hospital stay extension (P < .001), and discharge to a new facility (P < .001). Similarly, Medicaid patients had a 1.6 times increased mean comorbidity score (P < .001), and the highest risk of the following adverse outcomes: length of stay extension (odds ratio [OR]: 1.43, P < .001), complication (OR: 1.24, P = .017), and readmission (OR: 1.18; P = .041). Additionally, they had an increased risk of discharge to a new facility (OR: 1.78, P < .001). Comparing TSA patients in the Q1-3 to Q4, first quartile income was significantly associated with increased risk of hospital stay extension (P = .043), complication (P < .001), and readmission (P < .001). Second and third quartile patients had increased risks of any complication (Q2: P = .003; Q3: P = .016).Conclusion: The socioeconomic factors studied - ethnicity (AA and H), zip code income (Q1, Q2, and Q3), and insurance status (Medicare or Medicaid) - were all shown to have significantly increased risk for adverse outcomes following TSA. 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