Cory K. Mayfield MD , Julian Wier MD , Kevin C. Liu MD , Eric H. Lin BA , Cailan L. Feingold BS , Alexander E. Weber MD , Seth C. Gamradt MD , Joseph N. Liu MD , Frank A. Petrigliano MD
{"title":"虚弱和合并症负担独立预测全肩关节置换术后更高的医疗费用和非家庭出院","authors":"Cory K. Mayfield MD , Julian Wier MD , Kevin C. Liu MD , Eric H. Lin BA , Cailan L. Feingold BS , Alexander E. Weber MD , Seth C. Gamradt MD , Joseph N. Liu MD , Frank A. Petrigliano MD","doi":"10.1016/j.jseint.2025.05.024","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>With an aging population, total shoulder arthroplasty (TSA) will more frequently be performed in older adults. Comorbidity burden and frailty are two distinct risk factors for adverse outcomes; however, their independent effect on outcomes after TSA is unknown. The aim of this study was to determine the effect of frailty and comorbidities on postoperative healthcare utilization after TSA.</div></div><div><h3>Methods</h3><div>Patients who underwent primary, elective anatomic or reverse TSA between January 1, 2016, and December 31, 2020, were identified using the Premier Healthcare Database. Frailty was defined using the Johns Hopkins Adjusted Clinical Groups Frailty Index. Comorbidity burden was defined via the Elixhauser Comorbidity Index (unhealthy >2 comorbidities). These were then used to define healthy, frail, unhealthy, and frail/unhealthy patients. Rates of protracted (>2 days) length of stay (LOS), skilled nursing facility (SNF) discharges, and readmission were then compared between groups. Multivariable models were conducted to evaluate the adjusted effect of frailty and comorbidity burden.</div></div><div><h3>Results</h3><div>86,356 patients who underwent TSA were identified. 53,913 were categorized as healthy, 29,461 as unhealthy, 1,640 as frail, and 1,342 as frail/unhealthy. The frail/unhealthy cohort had the highest rates of protracted LOS (65.06%), SNF discharges (29.90%), and readmissions (5.00%). The frail cohort had higher rates of protracted LOS (48.96% vs. 39.78%) and SNF discharges (16.77% vs. 9.94%), with similar readmission rates (3.35% vs. 3.18%) when compared to the unhealthy group. These overall trends persisted after accounting for potential confounding factors.</div></div><div><h3>Conclusion</h3><div>When both present, frailty and comorbidity appear to be a major driver of increased healthcare utilization after TSA. These data can be used to guide patient expectations and illustrate the need for postoperative pathways for these patients.</div></div>","PeriodicalId":34444,"journal":{"name":"JSES International","volume":"9 5","pages":"Pages 1698-1704"},"PeriodicalIF":0.0000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Frailty and comorbidity burden independently predict higher healthcare costs and nonhome discharges after total shoulder arthroplasty\",\"authors\":\"Cory K. Mayfield MD , Julian Wier MD , Kevin C. Liu MD , Eric H. Lin BA , Cailan L. Feingold BS , Alexander E. Weber MD , Seth C. Gamradt MD , Joseph N. Liu MD , Frank A. Petrigliano MD\",\"doi\":\"10.1016/j.jseint.2025.05.024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>With an aging population, total shoulder arthroplasty (TSA) will more frequently be performed in older adults. Comorbidity burden and frailty are two distinct risk factors for adverse outcomes; however, their independent effect on outcomes after TSA is unknown. The aim of this study was to determine the effect of frailty and comorbidities on postoperative healthcare utilization after TSA.</div></div><div><h3>Methods</h3><div>Patients who underwent primary, elective anatomic or reverse TSA between January 1, 2016, and December 31, 2020, were identified using the Premier Healthcare Database. Frailty was defined using the Johns Hopkins Adjusted Clinical Groups Frailty Index. Comorbidity burden was defined via the Elixhauser Comorbidity Index (unhealthy >2 comorbidities). These were then used to define healthy, frail, unhealthy, and frail/unhealthy patients. Rates of protracted (>2 days) length of stay (LOS), skilled nursing facility (SNF) discharges, and readmission were then compared between groups. Multivariable models were conducted to evaluate the adjusted effect of frailty and comorbidity burden.</div></div><div><h3>Results</h3><div>86,356 patients who underwent TSA were identified. 53,913 were categorized as healthy, 29,461 as unhealthy, 1,640 as frail, and 1,342 as frail/unhealthy. The frail/unhealthy cohort had the highest rates of protracted LOS (65.06%), SNF discharges (29.90%), and readmissions (5.00%). The frail cohort had higher rates of protracted LOS (48.96% vs. 39.78%) and SNF discharges (16.77% vs. 9.94%), with similar readmission rates (3.35% vs. 3.18%) when compared to the unhealthy group. These overall trends persisted after accounting for potential confounding factors.</div></div><div><h3>Conclusion</h3><div>When both present, frailty and comorbidity appear to be a major driver of increased healthcare utilization after TSA. These data can be used to guide patient expectations and illustrate the need for postoperative pathways for these patients.</div></div>\",\"PeriodicalId\":34444,\"journal\":{\"name\":\"JSES International\",\"volume\":\"9 5\",\"pages\":\"Pages 1698-1704\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JSES International\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666638325001896\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JSES International","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666638325001896","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
Frailty and comorbidity burden independently predict higher healthcare costs and nonhome discharges after total shoulder arthroplasty
Background
With an aging population, total shoulder arthroplasty (TSA) will more frequently be performed in older adults. Comorbidity burden and frailty are two distinct risk factors for adverse outcomes; however, their independent effect on outcomes after TSA is unknown. The aim of this study was to determine the effect of frailty and comorbidities on postoperative healthcare utilization after TSA.
Methods
Patients who underwent primary, elective anatomic or reverse TSA between January 1, 2016, and December 31, 2020, were identified using the Premier Healthcare Database. Frailty was defined using the Johns Hopkins Adjusted Clinical Groups Frailty Index. Comorbidity burden was defined via the Elixhauser Comorbidity Index (unhealthy >2 comorbidities). These were then used to define healthy, frail, unhealthy, and frail/unhealthy patients. Rates of protracted (>2 days) length of stay (LOS), skilled nursing facility (SNF) discharges, and readmission were then compared between groups. Multivariable models were conducted to evaluate the adjusted effect of frailty and comorbidity burden.
Results
86,356 patients who underwent TSA were identified. 53,913 were categorized as healthy, 29,461 as unhealthy, 1,640 as frail, and 1,342 as frail/unhealthy. The frail/unhealthy cohort had the highest rates of protracted LOS (65.06%), SNF discharges (29.90%), and readmissions (5.00%). The frail cohort had higher rates of protracted LOS (48.96% vs. 39.78%) and SNF discharges (16.77% vs. 9.94%), with similar readmission rates (3.35% vs. 3.18%) when compared to the unhealthy group. These overall trends persisted after accounting for potential confounding factors.
Conclusion
When both present, frailty and comorbidity appear to be a major driver of increased healthcare utilization after TSA. These data can be used to guide patient expectations and illustrate the need for postoperative pathways for these patients.
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