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Health Services and Outcomes Research Methodology最新文献

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Limitations of the Inter-Unit Reliability: A Set of Practical Examples. 单位间可靠性的局限性:一组实际案例。
IF 1.6 Q3 HEALTH CARE SCIENCES & SERVICES Pub Date : 2024-06-01 Epub Date: 2023-06-28 DOI: 10.1007/s10742-023-00307-0
Nicholas Hartman, Vahakn B Shahinian, Valarie B Ashby, Katrina J Price, Kevin He

Healthcare quality measures are statistics that serve to evaluate healthcare providers and identify those that need to improve their care. Before using these measures in clinical practice, developers and reviewers assess measure reliability, which describes the degree to which differences in the measure values reflect actual variation in healthcare quality, as opposed to random noise. The Inter-Unit Reliability (IUR) is a popular statistic for assessing reliability, and it describes the proportion of total variation in a measure that is attributable to between-provider variation. However, Kalbfleisch, He, Xia, and Li (2018) [Health Services and Outcomes Research Methodology, 18, 215-225] have argued that the IUR has a severe limitation in that some of the between-provider variation may be unrelated to quality of care. In this paper, we illustrate the practical implications of this limitation through several concrete examples. We show that certain best-practices in measure development, such as careful risk adjustment and exclusion of unstable measure values, can decrease the sample IUR value. These findings uncover potential negative consequences of discarding measures with IUR values below some arbitrary threshold.

医疗质量测量是一种统计方法,用于评估医疗服务提供者,并找出需要改进的医疗服务提供者。在临床实践中使用这些测量指标之前,开发人员和审核人员要对测量指标的可靠性进行评估,可靠性描述了测量值的差异在多大程度上反映了医疗质量的实际变化,而不是随机噪音。单位间信度(IUR)是评估信度的常用统计量,它描述了医疗服务提供者之间的差异在测量值总差异中所占的比例。然而,Kalbfleisch、He、Xia 和 Li(2018)[《医疗服务与结果研究方法》,18,215-225] 认为,IUR 有一个严重的局限性,即部分医疗服务提供者之间的变异可能与医疗质量无关。在本文中,我们通过几个具体的例子来说明这一局限性的实际影响。我们表明,制定衡量标准时的某些最佳做法(如谨慎的风险调整和排除不稳定的衡量值)可以降低样本 IUR 值。这些发现揭示了剔除IUR值低于某个任意阈值的测量值可能带来的负面影响。
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引用次数: 0
Home- and community-based care in the new generation of Medicaid administrative data 新一代医疗补助管理数据中的家庭和社区护理
IF 1.5 Q2 Medicine Pub Date : 2024-05-23 DOI: 10.1007/s10742-024-00325-6
Sijiu Wang, Mingyu Qi, R. Tamara Konetzka
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引用次数: 0
Entropy balancing versus vector-based kernel weighting for causal inference in categorical treatment settings 熵平衡与基于矢量的核加权在分类处理设置中的因果推断关系
IF 1.5 Q2 Medicine Pub Date : 2024-05-16 DOI: 10.1007/s10742-024-00331-8
Y. Feyman, Jessica Lum, Daniel Asfaw, Steven Pizer, Melissa Garrido
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引用次数: 0
A terminal trend model for longitudinal medical cost data and survival 用于纵向医疗费用数据和生存的终端趋势模型
IF 1.5 Q2 Medicine Pub Date : 2024-04-18 DOI: 10.1007/s10742-024-00326-5
Qian Yang, Tor D. Tosteson, Anna N. A. Tosteson, Jeffrey C. Munson
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引用次数: 0
Multimodal mental state analysis 多模态心理状态分析
IF 1.5 Q2 Medicine Pub Date : 2024-04-16 DOI: 10.1007/s10742-024-00329-2
Bipin Kumar Rai, Ishika Jain, Baibhav Tiwari, Abhay Saxena
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引用次数: 0
Correction to: Disjunctive answer options complicate communication – a linguistic analysis of the danish EQ-5D (5 L) version 更正:非连续性答案选项使交流复杂化--对丹麦 EQ-5D (5 L) 版本的语言分析
IF 1.5 Q2 Medicine Pub Date : 2024-04-04 DOI: 10.1007/s10742-024-00328-3
Esben Nedenskov Petersen, Birgitte Nørgaard
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引用次数: 0
A machine learning approach for diagnostic and prognostic predictions, key risk factors and interactions 诊断和预后预测、关键风险因素和相互作用的机器学习方法
IF 1.5 Q2 Medicine Pub Date : 2024-03-18 DOI: 10.1007/s10742-024-00324-7
Murtaza Nasir, Nichalin S. Summerfield, Stephanie Carreiro, Dan Berlowitz, Asil Oztekin
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引用次数: 0
Evaluating medical providers in terms of patient health disparities: a statistical framework 从患者健康差异的角度评估医疗服务提供者:统计框架
IF 1.5 Q2 Medicine Pub Date : 2024-02-15 DOI: 10.1007/s10742-024-00323-8
Nicholas Hartman, Claudia Dahlerus
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引用次数: 0
Evaluating medical providers in terms of patient health disparities: a statistical framework 从患者健康差异的角度评估医疗服务提供者:统计框架
IF 1.5 Q2 Medicine Pub Date : 2024-02-15 DOI: 10.1007/s10742-024-00323-8
Nicholas Hartman, Claudia Dahlerus
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引用次数: 0
Exact-matching algorithms using administrative health claims database equivalence factors for real-world data analysis based on the target trial emulation framework 基于目标试验仿真框架,使用行政健康索赔数据库等效因子进行真实世界数据分析的精确匹配算法
IF 1.5 Q2 Medicine Pub Date : 2024-02-02 DOI: 10.1007/s10742-024-00322-9
Y. Nishioka, Emiri Morita, Saki Takeshita, Sakura Tamamoto, Tomoya Myojin, T. Noda, T. Imamura
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引用次数: 0
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Health Services and Outcomes Research Methodology
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