THU0442 SOCIAL VULNERABILITY AND DISCHARGE DISPOSITION AFTER ELECTIVE TOTAL HIP REPLACEMENT? RISK-ADJUSTED ANALYSIS OF LARGE REGIONAL DATASET. (June 2019)

• Record Type: Journal Article
• Authors: Mehta, Bella; Goodman, Susan; Ho, Kaylee; D'angelo, Debra; Parks, Michael; Ibrahim, Said
• Is Part Of: Annals of the rheumatic diseases. Volume 78(2019)Supplement 2
• Page Start: 510
• Page End: 511
• Publication Date: 2019-06
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2019-eular.6114
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: With the aging of the world population and the rising prevalence of Osteoarthritis (OA), elective joint replacement (JR) has become one of the fastest growing procedures in the management of end-stage OA. There is also increasing evidence that social determinants of health such as where one lives impact healthcare utilization and decision-making. Furthermore, elective JR of the hip and knee is one of the most important cost-centers for Medicare, the largest payer in the US, and has therefore been the subject of ongoing payment reform models that shape discharge destination and risk of readmission. Objectives: In a large regional dataset, we sought to examine how social vulnerability impacts discharge destination after elective THR, and what is the role in this relationship of patient race, another key social determinant of health which has been previously associated with disposition after surgery. Methods: We used the Pennsylvania Health Care Cost Containment Council (PHC4) database to identify all patients who underwent elective THR between 2012 and 2016. Community level Social Vulnerability Index (SVI) was derived from the American Census Survey, which draws 15 different measures of vulnerability including socioeconomic, housing, and disability among others. SVI ranges from 0 (least vulnerable) to 1 (most vulnerable). SVI was dichotomized into low (below median) and high (above median). We used binary logistic regression to test the association between community SVI and discharge disposition: Institution (Nursing home or inpatient rehabilitation vs Home with/out home health). We adjusted for important clinical, demographic, and facility level covariates. To examine the role race (African American (AA) vs White) in this relationship, we included in the model an interaction term for SVI and race. Results: There were a total 86, 215 THR done between Jan 2012 and Dec 2016 that met our inclusion criteria. About 40, 881 were <65 years of age; and 45, 334 were ≥ 65 years of age. Patients from low SVI community went to high volume hospitals as compared to high SVI in all age groups. Figure 1 shows the geospatial localization and relationship of THR patients in the State of Pennsylvania by community SVI level. Compared to white patients, AA patients were more likely to live in higher SVI communities (median SVIAA 0.66; IQR 0.48-0.83 vs median SVIW 0.42; IQR 0.28-0.55, respectively). Compared to low SVI communities, patients from high SVI communities were more likely to be discharged to an institution (vs home) (for age <65; aOR= 1.22, 95% CI: 1.14, 1.30, p<0.001; for ages ≥ 65; aOR= 1.11, 95% CI: 1.07, 1.16, p<0.001). The odds of discharge to an institution (vs Home) for patients living in high SVI communities (vs low SVI) was higher in AA compared to whites in all age groups. [Figure 2 ]. Conclusion: In this large regional dataset of patients who underwent THR, social vulnerability index of the community is associated with discharge disposition after surgery. Moreover, this association was stronger in African-Americans compared to Whites. This association when coupled with ongoing payment reform models may have implications for access to care for socially vulnerable populations. a Adjusted covariates for all models include patient sex, age, insurance, facility metro status, volume of cases, surgical complications, and Elixhauser Index. Disclosure of Interests: Bella Mehta: None declared, Susan Goodman Grant/research support from: Novartis: research support, Consultant for: Novartis, UCB, Pfizer: consulting, Kaylee Ho: None declared, Debra D'Angelo: None declared, Michael Parks Grant/research support from: Zimmer Biomet, Employee of: Zimmer Biomet, Said Ibrahim: None declared