Barnett Michael L, Hsu John, McWilliams J Michael
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts2Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts3Mongan Institute for Health Care Policy, Massachusetts General Hospital, Boston.
JAMA Intern Med. 2015 Nov;175(11):1803-12. doi: 10.1001/jamainternmed.2015.4660.
Medicare penalizes hospitals with higher than expected readmission rates by up to 3% of annual inpatient payments. Expected rates are adjusted only for patients' age, sex, discharge diagnosis, and recent diagnoses.
To assess the extent to which a comprehensive set of patient characteristics accounts for differences in hospital readmission rates.
DESIGN, SETTING, AND PARTICIPANTS: Using survey data from the nationally representative Health and Retirement Study (HRS) and linked Medicare claims for HRS participants enrolled in Medicare who were hospitalized from 2009 to 2012 (n = 8067 admissions), we assessed 29 patient characteristics from survey data and claims as potential predictors of 30-day readmission when added to standard Medicare adjustments of hospital readmission rates. We then compared the distribution of these characteristics between participants admitted to hospitals with higher vs lower hospital-wide readmission rates reported by Medicare. Finally, we estimated differences in the probability of readmission between these groups of participants before vs after adjusting for the additional patient characteristics.
All-cause readmission within 30 days of discharge.
Of the additional 29 patient characteristics assessed, 22 significantly predicted readmission beyond standard adjustments, and 17 of these were distributed differently between hospitals in the highest vs lowest quintiles of publicly reported hospital-wide readmission rates (P ≤ .04 for all comparisons). Almost all of these differences (16 of 17) indicated that participants admitted to hospitals in the highest quintile of readmission rates were more likely to have characteristics that were associated with a higher probability of readmission. The difference in the probability of readmission between participants admitted to hospitals in the highest vs lowest quintile of hospital-wide readmission rates was reduced by 48% from 4.41 percentage points with standard adjustments used by Medicare to 2.29 percentage points after adjustment for all patient characteristics assessed (reduction in difference: -2.12; 95% CI, -3.33 to -0.67; P = .003).
Patient characteristics not included in Medicare's current risk-adjustment methods explained much of the difference in readmission risk between patients admitted to hospitals with higher vs lower readmission rates. Hospitals with high readmission rates may be penalized to a large extent based on the patients they serve.
医疗保险会对再入院率高于预期的医院处以高达年度住院费用3%的罚款。预期再入院率仅根据患者的年龄、性别、出院诊断和近期诊断进行调整。
评估一套全面的患者特征在多大程度上可以解释医院再入院率的差异。
设计、地点和参与者:利用具有全国代表性的健康与退休研究(HRS)的调查数据以及与参加医疗保险的HRS参与者的医疗保险理赔记录相链接的数据(2009年至2012年期间住院的参与者,n = 8067次入院),我们从调查数据和理赔记录中评估了29项患者特征,将其作为在医疗保险对医院再入院率的标准调整基础上预测30天再入院的潜在因素。然后,我们比较了医疗保险报告的全院再入院率较高和较低的医院中入院参与者的这些特征分布情况。最后,我们估计了在调整这些额外的患者特征之前和之后,这些参与者组之间再入院概率的差异。
出院后30天内的全因再入院情况。
在评估的另外29项患者特征中,有22项在标准调整之外显著预测了再入院情况,其中17项在公开报告的全院再入院率最高和最低五分位数的医院之间分布不同(所有比较的P≤0.04)。几乎所有这些差异(17项中的16项)表明,再入院率最高五分位数的医院中的入院参与者更有可能具有与再入院概率较高相关的特征。全院再入院率最高和最低五分位数的医院中入院参与者之间的再入院概率差异从医疗保险使用标准调整时的4.41个百分点降低到调整所有评估的患者特征后的2.29个百分点,降低了48%(差异减少:-2.12;95%CI,-3.33至-0.67;P = 0.003)。
医疗保险当前风险调整方法中未包含的患者特征解释了再入院率较高和较低的医院中入院患者再入院风险差异的很大一部分。再入院率高的医院可能在很大程度上因其所服务的患者而受到惩罚。