Abstract
BackgroundIdentifying risk factors associated with non-home discharge (NHD) following revision hip and knee total joint arthroplasty (TJA) could reduce the rate of preventable discharge to rehabilitation or skilled nursing facilities. Neighborhood-level deprivation indices are becoming an increasingly important measure of socioeconomic disadvantage as these indices consider multiple social determinants of health. This study aimed to compare the utility of widely used neighborhood social vulnerability indices in predicting NHD following revision TJA patients. MethodsThis study included 1,043 consecutive patients who underwent revision TJA at a single tertiary health system. There were three multivariate logistic regression analyses with the outcome of NHD performed using the area deprivation index (ADI), social deprivation index (SDI), and social vulnerability index (SVI) while controlling for other demographic variables. Neighborhood-level indices were included in the analysis as continuous variables and categorical quartiles, with the lowest quartile representing the least deprived neighborhoods of the patient cohort. The strength of the association of significant indices was measured. ResultsPatients in the highest ADI and SDI quartiles demonstrated higher odds of NHD compared to the cohort with the lowest quartile (ADI OR [odds ratio] = 1.93, 95% CI [confidence interval] = 1.23 to 3.03, P = 0.005; SDI OR = 1.86, 95% CI = 1.18 to 2.91, P = 0.007). Discharge disposition was more strongly associated with ADI than SDI (0.68 versus 0.26). Age, ASA status, and alcohol use were independent determinants of discharge disposition. No significant association was seen between SVI and discharge disposition. ConclusionArea-level indices can be utilized to identify patients at higher risk of NHD following revision TJA. This study highlights the important differences between these indices' utility when evaluating their effects on clinical outcomes in this patient population. The findings shed light on the potential of integrating these tools into policy development, clinical preoperative programs, and research to better understand and address the health disparities in arthroplasty outcomes.
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