Demographic, Comorbidity, and Episode of Care Trends in Primary Hip Arthroplasty: 2008 to 2018

The Journal of Hip Surgery(2021)

引用 0|浏览0
暂无评分
摘要
Abstract Background While previous studies have provided insight into time-trends in age and comorbidities of total hip arthroplasty (THA) patients, there is limited recent literature from within the past decade. The implication of these findings is relevant due to the projected THA volume increase and continued emphasis on healthcare system cost-containment policies. Therefore, the purpose of this study was to identify trends in THA patient demographics, comorbidities, and episode of care from 2008 to 2018. Methods The National Surgical Quality Improvement Program (NSQIP) was queried to identify patient demographics, comorbidities, and episodes of care outcomes in patients undergoing primary THA from 2008 to 2018 (n = 216,524). Trends were analyzed using analysis of variances for continuous variables, while categorical variables were analyzed using chi-squared or Monte Carlo tests, where applicable. Results From 2008 to 2018, there were no clinically significant differences in age and body mass index (BMI) in patients with BMI over 40 kg/m2. However, modifiable comorbidities including patients with hypertension (60.2% in 2008, 54.3 in 2018%, p < 0.001) and anemia (19% in 2008, 11.2%, in 2016, p < 0.001) improved. Functional status and the overall morbidity probability have improved with a decrease in hospital lengths of stay (4.0 ± 2.8 days in 2008, 2.1 ± 2.2 days in 2018, p < 0.001), 30-day readmissions (4.2% in 2009, 3.3% in 2018, p < 0.001), and significant increase in home-discharges (70.1% in 2008, 87.3% in 2018, p < 0.001). Conclusion Patient overall health status improved from 2008 to 2018. While conjectural, our findings may be a reflection of a global shift toward value-based comprehensive care centering on patient optimization prior to arthroplasty, quality-of-care, and curtailing costs by mitigating perioperative adverse events.This study's level of evidence is III.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要