Christie M Bartels1, Ann Chodara2, Yi Chen3, Xing Wang3, W Ryan Powell4, Fangfang Shi4, Maria Schletzbaum5, Ann M Sheehy6, Farah A Kaiksow6, Andrea L Gilmore-Bykovskyi7, Shivani Garg8, Menggang Yu3, Amy J Kind9. 1. University of Wisconsin School of Medicine and Public Health, Department of Medicine, Rheumatology Division, Madison, WI, USA; University of Wisconsin School of Medicine and Public Health, Department of Medicine, Health Services & Care Research Program, Madison, WI, USA. Electronic address: Cb4@medicine.wisc.edu. 2. University of Wisconsin School of Medicine and Public Health, Department of Medicine, Rheumatology Division, Madison, WI, USA; University of Wisconsin Hospital and Clinics, Madison, WI, USA. 3. University of Wisconsin School of Medicine and Public Health, Department of Biostatistics and Medical Informatics, Madison, WI, USA. 4. University of Wisconsin School of Medicine and Public Health, Department of Medicine, Geriatrics Division, Madison, WI, USA; University of Wisconsin School of Medicine and Public Health, Department of Medicine, Health Services & Care Research Program, Madison, WI, USA. 5. University of Wisconsin School of Medicine and Public Health, Department of Population Health Sciences, Madison, WI, USA. 6. University of Wisconsin School of Medicine and Public Health, Department of Medicine, Health Services & Care Research Program, Madison, WI, USA; University of Wisconsin School of Medicine and Public Health, Department of Medicine, Hospital Medicine Division, Madison, WI, USA. 7. University of Wisconsin School of Medicine and Public Health, Department of Medicine, Geriatrics Division, Madison, WI, USA; University of Wisconsin School of Medicine and Public Health, Department of Medicine, Health Services & Care Research Program, Madison, WI, USA; University of Wisconsin-Madison, School of Nursing, Madison, WI, USA. 8. University of Wisconsin School of Medicine and Public Health, Department of Medicine, Rheumatology Division, Madison, WI, USA. 9. University of Wisconsin School of Medicine and Public Health, Department of Medicine, Geriatrics Division, Madison, WI, USA; University of Wisconsin School of Medicine and Public Health, Department of Medicine, Health Services & Care Research Program, Madison, WI, USA; VA Geriatrics Research Education and Clinical Center, William S Middleton VA Hospital, Madison, WI, USA.
Abstract
OBJECTIVE: Thirty-day hospital readmissions in systemic lupus erythematosus (SLE) approach proportions in Medicare-reported conditions including heart failure (HF). We compared adjusted 30-day readmission and mortality among SLE, HF, and general Medicare to assess predictors informing readmission prevention. METHODS: This database study used a 20% sample of all US Medicare 2014 adult hospitalizations to compare risk of 30-day readmission and mortality among admissions with SLE, HF, and neither per discharge diagnoses (if both SLE and HF, classified as SLE). Inclusion required live discharge and ≥12 months of Medicare A/B before admission to assess baseline covariates including patient, geographic, and hospital factors. Analysis used observed and predicted probabilities, and multivariable GEE models clustered by patient to report adjusted risk ratios (ARRs) of 30-day readmission and mortality. RESULTS: SLE admissions (n=10,868) were younger, predominantly female, more likely to be Black, disabled, and have Medicaid or end-stage renal disease (ESRD). Observed 30-day readmissions of 24% were identical for SLE and HF (p = 0.6), and higher than other Medicare (16%, p < 0.001). Both SLE and HF had elevated readmission risk (ARR 1.08, (95% CI (1.04, 1.13)); 1.11, (1.09, 1.13)). SLE readmissions were higher for Black (30%) versus White (21%) populations, and highest in ages 18-33 (39%) and ESRD (37%). Admissions of Black patients with SLE from least disadvantaged neighborhoods had highest 30-day mortality (9% versus 3% White). CONCLUSION: Thirty-day SLE readmissions rivaled HF at 24%. Readmission prevention programs should engage young, ESRD patients with SLE and examine potential causal gaps in SLE care and transitions.
OBJECTIVE: Thirty-day hospital readmissions in systemic lupus erythematosus (SLE) approach proportions in Medicare-reported conditions including heart failure (HF). We compared adjusted 30-day readmission and mortality among SLE, HF, and general Medicare to assess predictors informing readmission prevention. METHODS: This database study used a 20% sample of all US Medicare 2014 adult hospitalizations to compare risk of 30-day readmission and mortality among admissions with SLE, HF, and neither per discharge diagnoses (if both SLE and HF, classified as SLE). Inclusion required live discharge and ≥12 months of Medicare A/B before admission to assess baseline covariates including patient, geographic, and hospital factors. Analysis used observed and predicted probabilities, and multivariable GEE models clustered by patient to report adjusted risk ratios (ARRs) of 30-day readmission and mortality. RESULTS: SLE admissions (n=10,868) were younger, predominantly female, more likely to be Black, disabled, and have Medicaid or end-stage renal disease (ESRD). Observed 30-day readmissions of 24% were identical for SLE and HF (p = 0.6), and higher than other Medicare (16%, p < 0.001). Both SLE and HF had elevated readmission risk (ARR 1.08, (95% CI (1.04, 1.13)); 1.11, (1.09, 1.13)). SLE readmissions were higher for Black (30%) versus White (21%) populations, and highest in ages 18-33 (39%) and ESRD (37%). Admissions of Black patients with SLE from least disadvantaged neighborhoods had highest 30-day mortality (9% versus 3% White). CONCLUSION: Thirty-day SLE readmissions rivaled HF at 24%. Readmission prevention programs should engage young, ESRD patients with SLE and examine potential causal gaps in SLE care and transitions.
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