Suppr超能文献

医院在全范围 30 天再入院指标上的绩效模式:比赛场地是否公平?

Patterns of Hospital Performance on the Hospital-Wide 30-Day Readmission Metric: Is the Playing Field Level?

机构信息

Department of Physical Medicine and Rehabilitation, Johns Hopkins Health System, Baltimore, MD, USA.

Medicine, Johns Hopkins Health System, Baltimore, MD, USA.

出版信息

J Gen Intern Med. 2018 Jan;33(1):57-64. doi: 10.1007/s11606-017-4193-9. Epub 2017 Oct 2.

Abstract

BACKGROUND

Hospital performance on the 30-day hospital-wide readmission (HWR) metric as calculated by the Centers for Medicare and Medicaid Services (CMS) is currently reported as a quality measure. Focusing on patient-level factors may provide an incomplete picture of readmission risk at the hospital level to explain variations in hospital readmission rates.

OBJECTIVE

To evaluate and quantify hospital-level characteristics that track with hospital performance on the current HWR metric.

DESIGN

Retrospective cohort study.

SETTING/PATIENTS: A total of 4785 US hospitals.

METRICS

We linked publically available data on individual hospitals published by CMS on patient-level adjusted 30-day HWR rates from July 1, 2011, through June 30, 2014, to the 2014 American Hospital Association annual survey. Primary outcome was performance in the worst CMS-calculated HWR quartile. Primary hospital-level exposure variables were defined as: size (total number of beds), safety net status (top quartile of disproportionate share), academic status [member of the Association of American Medical Colleges (AAMC)], National Cancer Institute Comprehensive Cancer Center (NCI-CCC) status, and hospital services offered (e.g., transplant, hospice, emergency department). Multilevel regression was used to evaluate the association between 30-day HWR and the hospital-level factors.

RESULTS

Hospital-level characteristics significantly associated with performing in the worst CMS-calculated HWR quartile included: safety net status [adjusted odds ratio (aOR) 1.99, 95% confidence interval (95% CI) 1.61-2.45, p < 0.001], large size (> 400 beds, aOR 1.42, 95% CI 1.07-1.90, p = 0.016), AAMC alone status (aOR 1.95, 95% CI 1.35-2.83, p < 0.001), and AAMC plus NCI-CCC status (aOR 5.16, 95% CI 2.58-10.31, p < 0.001). Hospitals with more critical care beds (aOR 1.26, 95% CI 1.02-1.56, p = 0.033), those with transplant services (aOR 2.80, 95% CI 1.48-5.31,p = 0.001), and those with emergency room services (aOR 3.37, 95% CI 1.12-10.15, p = 0.031) demonstrated significantly worse HWR performance. Hospice service (aOR 0.64, 95% CI 0.50-0.82, p < 0.001) and having a higher proportion of total discharges being surgical cases (aOR 0.62, 95% CI 0.50-0.76, p < 0.001) were associated with better performance.

LIMITATION

The study approach was not intended to be an alternate readmission metric to compete with the existing CMS metric, which would require a re-examination of patient-level data combined with hospital-level data.

CONCLUSION

A number of hospital-level characteristics (such as academic tertiary care center status) were significantly associated with worse performance on the CMS-calculated HWR metric, which may have important health policy implications. Until the reasons for readmission variability can be addressed, reporting the current HWR metric as an indicator of hospital quality should be reevaluated.

摘要

背景

目前,医疗保险和医疗补助服务中心(CMS)计算的 30 天医院整体再入院(HWR)指标的医院绩效作为一项质量指标进行报告。关注患者层面的因素可能无法全面了解医院层面的再入院风险,从而无法解释医院再入院率的差异。

目的

评估和量化与当前 HWR 指标的医院绩效相关的医院层面特征。

设计

回顾性队列研究。

设置/患者:共 4785 家美国医院。

指标

我们将 CMS 公布的有关 2011 年 7 月 1 日至 2014 年 6 月 30 日期间个体医院患者调整后 30 天 HWR 率的公开数据与 2014 年美国医院协会年度调查相关联。主要结果是在 CMS 计算的最差 HWR 四分位数中表现不佳。主要医院层面的暴露变量定义为:规模(总床位数)、安全网状态(不成比例份额的前四分之一)、学术地位[美国医学院协会(AAMC)成员]、国家癌症研究所综合癌症中心(NCI-CCC)地位和提供的医院服务(如移植、临终关怀、急诊部)。使用多水平回归来评估 30 天 HWR 与医院层面因素之间的关联。

结果

与 CMS 计算的最差 HWR 四分位数表现相关的医院层面特征包括:安全网状态(调整后优势比[aOR]1.99,95%置信区间[95%CI]1.61-2.45,p<0.001)、规模较大(>400 张床位,aOR 1.42,95%CI 1.07-1.90,p=0.016)、仅 AAMC 状态(aOR 1.95,95%CI 1.35-2.83,p<0.001)和 AAMC 加 NCI-CCC 状态(aOR 5.16,95%CI 2.58-10.31,p<0.001)。拥有更多重症监护床位的医院(aOR 1.26,95%CI 1.02-1.56,p=0.033)、提供移植服务的医院(aOR 2.80,95%CI 1.48-5.31,p=0.001)和提供急诊服务的医院(aOR 3.37,95%CI 1.12-10.15,p=0.031)的 HWR 表现明显更差。临终关怀服务(aOR 0.64,95%CI 0.50-0.82,p<0.001)和更高比例的总出院人数为手术病例(aOR 0.62,95%CI 0.50-0.76,p<0.001)与更好的表现相关。

局限性

该研究方法并非旨在作为替代再入院指标与现有的 CMS 指标竞争,这将需要重新检查患者层面的数据,并结合医院层面的数据。

结论

许多医院层面的特征(如学术性三级保健中心地位)与 CMS 计算的 HWR 指标的较差表现显著相关,这可能具有重要的卫生政策意义。在能够解决再入院变异性的原因之前,应该重新评估将当前 HWR 指标作为医院质量指标的报告。

相似文献

1
Patterns of Hospital Performance on the Hospital-Wide 30-Day Readmission Metric: Is the Playing Field Level?
J Gen Intern Med. 2018 Jan;33(1):57-64. doi: 10.1007/s11606-017-4193-9. Epub 2017 Oct 2.
3
Incorporating Medicare Advantage Admissions Into the CMS Hospital-Wide Readmission Measure.
JAMA Netw Open. 2024 Jun 3;7(6):e2414431. doi: 10.1001/jamanetworkopen.2024.14431.
4
Hospital Evaluations by Social Media: A Comparative Analysis of Facebook Ratings among Performance Outliers.
J Gen Intern Med. 2015 Oct;30(10):1440-6. doi: 10.1007/s11606-015-3236-3. Epub 2015 Mar 7.
8
Factors Associated With Unplanned 30-Day Readmissions After Hematopoietic Cell Transplantation Among US Hospitals.
JAMA Netw Open. 2019 Jul 3;2(7):e196476. doi: 10.1001/jamanetworkopen.2019.6476.
9
Hospital Quality Metrics: "America's Best Hospitals" and Outcomes After Ischemic Stroke.
J Stroke Cerebrovasc Dis. 2019 Feb;28(2):430-434. doi: 10.1016/j.jstrokecerebrovasdis.2018.10.022. Epub 2018 Nov 8.

引用本文的文献

2
Association of hospital and market characteristics with 30-day readmission rates from 2009 to 2015.
SAGE Open Med. 2024 Jan 18;12:20503121231220815. doi: 10.1177/20503121231220815. eCollection 2024.
3
Is there an association between hospital staffing levels and inpatient-COVID-19 mortality rates?
PLoS One. 2022 Oct 19;17(10):e0275500. doi: 10.1371/journal.pone.0275500. eCollection 2022.
4
Area Deprivation Index and Cardiac Readmissions: Evaluating Risk-Prediction in an Electronic Health Record.
J Am Heart Assoc. 2021 Jul 6;10(13):e020466. doi: 10.1161/JAHA.120.020466. Epub 2021 Jul 2.
5
Disease-dependent variations in the timing and causes of readmissions in Germany: A claims data analysis for six different conditions.
PLoS One. 2021 Apr 26;16(4):e0250298. doi: 10.1371/journal.pone.0250298. eCollection 2021.
6
Consolidating Emergency Department-specific Data to Enable Linkage with Large Administrative Datasets.
West J Emerg Med. 2020 Oct 27;21(6):141-145. doi: 10.5811/westjem.2020.8.48305.
7
8
Increased 30-day readmission rate after craniotomy for tumor resection at safety net hospitals in small metropolitan areas.
J Neurooncol. 2020 May;148(1):141-154. doi: 10.1007/s11060-020-03507-7. Epub 2020 Apr 28.

本文引用的文献

1
Association Between Teaching Status and Mortality in US Hospitals.
JAMA. 2017 May 23;317(20):2105-2113. doi: 10.1001/jama.2017.5702.
4
Timing and Frequency of Unplanned Readmissions After Lung Transplantation Impact Long-Term Survival.
Ann Thorac Surg. 2016 Aug;102(2):378-84. doi: 10.1016/j.athoracsur.2016.02.083. Epub 2016 May 4.
6
Understanding Medicare Hospital Readmission Rates And Differing Penalties Between Safety-Net And Other Hospitals.
Health Aff (Millwood). 2016 Jan;35(1):124-31. doi: 10.1377/hlthaff.2015.0534.
7
Examination of unplanned 30-day readmissions to a comprehensive cancer hospital.
J Oncol Pract. 2015 Mar;11(2):e177-81. doi: 10.1200/JOP.2014.001546. Epub 2015 Jan 13.
8
10
Identification of process measures to reduce postoperative readmission.
J Gastrointest Surg. 2014 Aug;18(8):1407-15. doi: 10.1007/s11605-013-2429-5. Epub 2014 Jun 10.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验