Identifying Cohabiting Couples in Administrative Data: Evidence from Medicare Address Data [0.03%]
运用医疗保险地址数据识别同居关系：证据来源 Medicare 地址数据
Sasmira Matta,Joanne W Hsu,Theodore J Iwashyna et al.
Sasmira Matta et al.
Marital status is recognized as an important social determinant of health, income, and social support, but is rarely available in administrative data. We assessed the feasibility of using exact address data and zip code history to identify ...
Bias Reduction Methods for Propensity Scores Estimated from Error-Prone EHR-Derived Covariates [0.03%]
基于不准确的电子健康记录派生协变量估计倾向得分的偏差校正方法
Joanna Harton,Ronac Mamtani,Nandita Mitra et al.
Joanna Harton et al.
As the use of electronic health records (EHR) to estimate treatment effects has become widespread, concern about bias introduced by error in EHR-derived covariates has also grown. While methods exist to address measurement error in individu...
Steven Stern,Elizabeth Merwin,Emily Hauenstein et al.
Steven Stern et al.
The effects of rurality on physical and mental health are examined in analyses of a national dataset, the Community Tracking Survey, 2000-2001, that includes individual level observations from household interviews. We merge it with county l...
Veridical Causal Inference using Propensity Score Methods for Comparative Effectiveness Research with Medical Claims [0.03%]
基于倾向得分的因果推断方法在医疗理赔数据中的应用及验证
Ryan D Ross,Xu Shi,Megan E V Caram et al.
Ryan D Ross et al.
Medical insurance claims are becoming increasingly common data sources to answer a variety of questions in biomedical research. Although comprehensive in terms of longitudinal characterization of disease development and progression for a po...
Assessing Geographical Variations in Hospital Processes of Care Using Multilevel Item Response Models [0.03%]
基于多层次项目反应模型的医院诊疗过程地域差异评价研究
Yulei He,Robert E Wolf,Sharon-Lise T Normand
Yulei He
With health care reform passing in the United States, much effort is directed toward developing and disseminating comparative information on standardized processes of care for health care providers. We propose the use of Bayesian multilevel...
Methodological Challenges and Proposed Solutions for Evaluating Opioid Policy Effectiveness [0.03%]
评估阿片类药物政策有效性的方法挑战及解决方案
Megan S Schuler,Beth Ann Griffin,Magdalena Cerdá et al.
Megan S Schuler et al.
Opioid-related mortality increased by nearly 400% between 2000 and 2018. In response, federal, state, and local governments have enacted a heterogeneous collection of opioid-related policies in an effort to reverse the opioid crisis, produc...
Modelling the size, cost and health impacts of universal basic income: What can be done in advance of a trial? [0.03%]
全民基本收入的规模、成本和健康影响的模型构建：在试验之前可以做什么？
Matthew Thomas Johnson,Elliott Aidan Johnson,Laura Webber et al.
Matthew Thomas Johnson et al.
Opposition to Universal Basic Income (UBI) is encapsulated by Martinelli's claim that 'an affordable basic income would be inadequate, and an adequate basic income would be unaffordable'. In this article, we present a model of health impact...
Estimating Heterogeneous Effects of a Policy Intervention across Organizations when Organization Affiliation is Missing for the Control Group: Application to the Evaluation of Accountable Care Organizations [0.03%]
基于控制组缺乏组织归属信息情况下估计政策干预在不同组织间异质性影响的方法及对问责护理组织评估的应用
Guanqing Chen,Valerie A Lewis,Daniel Gottlieb et al.
Guanqing Chen et al.
First introduced in early 2000s, the accountable care organization (ACO) is designed to lower health care costs while improving quality of care and has become one of the most important coordinated care technologies in the United States. In ...
A Novel Cluster Sampling Design that Couples Multiple Surveys to Support Multiple Inferential Objectives [0.03%]
一种新的聚类抽样设计，结合多种调查以支持多个推理目标
A James O&#x;Malley,Seho Park
A James O&#x;Malley
In the United States the number of health systems that own practices or hospitals have increased in number and complexity leading to interest in assessing the relationship between health organization factors and health outcomes. However, th...
Guest Editorial: Articles selected from the 2020 International Conference on Health Policy Statistics [0.03%]
特邀编辑：从2020年国际医疗政策统计大会中精选的文章
Catherine M Crespi,Ofer Harel
Catherine M Crespi