Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor.
Department of Systems, Populations and Leadership, University of Michigan School of Nursing, Ann Arbor.
JAMA Netw Open. 2019 May 3;2(5):e193290. doi: 10.1001/jamanetworkopen.2019.3290.
The measured severity of illness of hospitalized Medicare beneficiaries has increased. Whether this change is associated with payment reforms, concentrated among hospitalizations with principal diagnoses targeted by payment reform, and reflective of true increases in severity of illness is unknown.
To assess whether the expansion of secondary diagnosis codes in January 2011 and the incentive payments for health information technology under the US Health Information Technology for Economic and Clinical Health Act were associated with changes in measured severity of illness and whether those changes are reflective of true increases in underlying patient severity.
DESIGN, SETTING, AND PARTICIPANTS: This cohort study of Medicare fee-for-service beneficiary discharges (N = 47 951 443) between January 1, 2008, and August 31, 2015, used a regression-discontinuity design to evaluate changes in measured severity of illness after the expansion of secondary diagnoses. Discharge-level linear regression model with hospital fixed effects was used to evaluate changes in measured severity of illness after hospitals' receipt of incentives for health information technology. The change in predictive accuracy of measured severity of illness on 30-day readmissions after the implementation of both policies was evaluated. Data analysis was performed from November 1, 2018, to March 5, 2019.
The primary outcome was patients' measured severity of illness determined by the number of condition categories from secondary discharge diagnosis codes. Measured severity of illness for diagnoses commonly targeted by Medicare policies and untargeted diagnoses was assessed.
In total, 47 951 443 discharges at 2850 hospitals were included. In 2008, these beneficiaries included 3 882 672 women (58.5%) with a mean (SD) age of 78.5 (8.4) years. In 2014, the discharges included 3 377 137 women (57.8%) with the mean (SD) age of 78.4 (8.7) years. The Centers for Medicare & Medicaid Services expansion of secondary diagnoses was associated with a 0.348 (95% CI, 0.328-0.367; P < .001) change in condition categories for all diagnoses, 0.445 (95% CI, 0.419-0.470; P < .001) for targeted diagnoses, and 0.321 (95% CI, 0.302-0.341; P < .001) for untargeted diagnoses. Health information technology incentives were associated with a 0.013 (95% CI, 0.004-0.022; P = .005) change in condition categories for all diagnoses, 0.195 (95% CI, 0.184-0.207; P < .001) for targeted diagnoses, and -0.016 (95% CI, -0.025 to -0.007; P < .001) for untargeted diagnoses. Minimal improvements in predictive accuracy were observed.
Changes in Centers for Medicare & Medicaid Services policies appear to be associated with increases in measured severity of illness; these increases do not appear to reflect substantive changes in true patient severity.
住院的医疗保险受益人的疾病严重程度的衡量标准有所提高。这种变化是否与支付改革有关,是否集中在支付改革针对的主要诊断的住院治疗中,以及是否反映了疾病严重程度的真实增加,目前尚不清楚。
评估 2011 年 1 月二级诊断代码的扩展以及美国健康信息技术经济和临床健康法案下的健康信息技术激励措施是否与疾病严重程度的衡量变化相关,以及这些变化是否反映了潜在患者严重程度的真实增加。
设计、设置和参与者:本研究为医疗保险按服务收费受益人的出院患者队列研究(N=47951443),时间为 2008 年 1 月 1 日至 2015 年 8 月 31 日,使用回归不连续性设计来评估二级诊断扩展后疾病严重程度的衡量变化。使用具有医院固定效应的出院水平线性回归模型评估医院获得健康信息技术激励后的疾病严重程度的衡量变化。评估这两项政策实施后 30 天再入院预测准确性的变化。数据分析于 2018 年 11 月 1 日至 2019 年 3 月 5 日进行。
主要结果是患者的疾病严重程度,由二级出院诊断代码的类别数量决定。评估了常见的医疗保险政策和未针对的诊断目标的诊断的疾病严重程度。
共纳入 2850 家医院的 47951443 次出院。2008 年,这些患者包括 3882672 名女性(58.5%),平均(SD)年龄为 78.5(8.4)岁。2014 年,出院患者包括 3377137 名女性(57.8%),平均(SD)年龄为 78.4(8.7)岁。医疗保险和医疗补助服务中心二级诊断的扩展与所有诊断的条件类别变化 0.348(95%置信区间,0.328-0.367;P<0.001)、目标诊断的 0.445(95%置信区间,0.419-0.470;P<0.001)和非目标诊断的 0.321(95%置信区间,0.302-0.341;P<0.001)相关。健康信息技术激励措施与所有诊断的条件类别变化 0.013(95%置信区间,0.004-0.022;P=0.005)、目标诊断的 0.195(95%置信区间,0.184-0.207;P<0.001)和非目标诊断的-0.016(95%置信区间,-0.025 至-0.007;P<0.001)相关。观察到预测准确性的微小改善。
医疗保险政策的变化似乎与衡量的疾病严重程度的增加有关;这些增加似乎并没有反映患者严重程度的实质性变化。