Patient Characteristics and Differences in Hospital Readmission Rates.
Patient Characteristics and Differences in Hospital Readmission Rates.
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DOI：
10.1001/jamainternmed.2015.4660
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发表时间：
2015-11
影响因子：
39
通讯作者：
McWilliams JM
中科院分区：
文献类型：
--
作者：
Barnett ML;Hsu J;McWilliams JM
医疗保险对再入院率高于预期的医院处以最高达年度住院费用3%的罚款。预期率仅根据患者的年龄、性别、出院诊断和最近的诊断进行调整。评估综合患者特征对再入院率差异的影响程度。使用来自全国代表性健康与退休研究（HRS）和相关医疗保险索赔的调查数据，我们评估了29名患者的调查数据和索赔特征，并将其作为30天再入院率的潜在预测因素，加入标准的医疗保险再入院率调整。然后，我们比较了这些特征在医疗保险报告的医院再入院率较高和较低的参与者之间的分布。最后，我们估计了这些组参与者在调整额外患者特征之前和之后再入院概率的差异。2009-2012年住院的HRS参与者（n= 8067例入院）。出院后30天内全因再入院。在评估的另外29个患者特征中，22个显著预测再入院超出标准调整，其中17个在公开报告的全院再入院率最高五分位数与最低五分位数的医院之间分布不同（所有p≤0.04）。几乎所有这些差异（17个中的16个）都表明，在再入院率最高的五分之一的医院入院的参与者更有可能具有与再入院概率较高相关的特征。住院率最高五分位数与最低五分位数的住院患者再入院概率的差异减少了48%，从医疗保险使用的标准调整后的4.41个百分点减少到所有患者特征评估后的2.29个百分点（差异减少：- 2.12,95% CI - 3.33, - 0.67; p=0.003）。医疗保险现行风险调整方法中未包括的患者特征解释了入院率较高与较低医院的患者再入院风险差异的大部分原因。再入院率高的医院可能在很大程度上因其所服务的病人而受到处罚。
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. Using survey data from the nationally representative Health and Retirement Study (HRS) and linked Medicare claims, 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. HRS participants enrolled in Medicare who were hospitalized from 2009–2012 (n=8,067 admissions). 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≤0.04 for all). 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, −0.67; p=0.003). 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 versus lower readmission rates. Hospitals with high readmission rates may be penalized to a large extent based on the patients they serve.