Pub Date : 2024-02-02DOI: 10.1007/s10742-024-00322-9
Y. Nishioka, Emiri Morita, Saki Takeshita, Sakura Tamamoto, Tomoya Myojin, T. Noda, T. Imamura
{"title":"Exact-matching algorithms using administrative health claims database equivalence factors for real-world data analysis based on the target trial emulation framework","authors":"Y. Nishioka, Emiri Morita, Saki Takeshita, Sakura Tamamoto, Tomoya Myojin, T. Noda, T. Imamura","doi":"10.1007/s10742-024-00322-9","DOIUrl":"https://doi.org/10.1007/s10742-024-00322-9","url":null,"abstract":"","PeriodicalId":45600,"journal":{"name":"Health Services and Outcomes Research Methodology","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139871191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-24DOI: 10.1007/s10742-023-00321-2
Bipin Kumar Rai, Vedant Dubey, Khushi Dubey
{"title":"Blockchain based E-procurement system in healthcare","authors":"Bipin Kumar Rai, Vedant Dubey, Khushi Dubey","doi":"10.1007/s10742-023-00321-2","DOIUrl":"https://doi.org/10.1007/s10742-023-00321-2","url":null,"abstract":"","PeriodicalId":45600,"journal":{"name":"Health Services and Outcomes Research Methodology","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139601416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-01Epub Date: 2023-03-16DOI: 10.1007/s10742-023-00305-2
Leslie Myint
This article clarifies how the biostatistical literature on time-varying treatments (TVT) can provide tools for dealing with time-varying confounding in difference-in-differences (DiD) studies. I use a simulation study to compare the bias and standard error of inverse probability weighting estimators from the TVT framework, a DiD framework, and hybrid approaches that combine ideas from both frameworks. I simulated longitudinal data with treatment effect heterogeneity over multiple time points using linear and logistic models. Simulation settings looked at both time-invariant confounders and time-varying confounders affected by prior treatment. Estimators that combined ideas from both frameworks had lower bias than standard TVT and DiD estimators when assumptions were unmet. The TVT framework provides estimation tools that can complement DiD tools in a wide range of applied settings. It also provides alternate estimands for consideration in policy settings.
本文阐明了关于时变处理（TVT）的生物统计文献如何为处理差分（DiD）研究中的时变混杂提供工具。我利用模拟研究比较了 TVT 框架、DiD 框架和结合了这两种框架思想的混合方法的反概率加权估计器的偏差和标准误差。我使用线性和逻辑模型模拟了多个时间点上具有治疗效果异质性的纵向数据。模拟设置既考虑了时间不变的混杂因素，也考虑了受先前治疗影响的时变混杂因素。在未满足假设条件的情况下，结合两种框架的估计方法比标准 TVT 和 DiD 估计方法的偏差更小。TVT 框架提供的估计工具可以在广泛的应用环境中补充 DiD 工具。它还提供了其他估算方法，供政策制定者考虑。
{"title":"Controlling time-varying confounding in difference-in-differences studies using the time-varying treatments framework.","authors":"Leslie Myint","doi":"10.1007/s10742-023-00305-2","DOIUrl":"10.1007/s10742-023-00305-2","url":null,"abstract":"<p><p>This article clarifies how the biostatistical literature on time-varying treatments (TVT) can provide tools for dealing with time-varying confounding in difference-in-differences (DiD) studies. I use a simulation study to compare the bias and standard error of inverse probability weighting estimators from the TVT framework, a DiD framework, and hybrid approaches that combine ideas from both frameworks. I simulated longitudinal data with treatment effect heterogeneity over multiple time points using linear and logistic models. Simulation settings looked at both time-invariant confounders and time-varying confounders affected by prior treatment. Estimators that combined ideas from both frameworks had lower bias than standard TVT and DiD estimators when assumptions were unmet. The TVT framework provides estimation tools that can complement DiD tools in a wide range of applied settings. It also provides alternate estimands for consideration in policy settings.</p>","PeriodicalId":45600,"journal":{"name":"Health Services and Outcomes Research Methodology","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10891225/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83447901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-29DOI: 10.1007/s10742-023-00319-w
Marc L. Berger, William H. Crown, Jim Z. Li, Kelly H. Zou
{"title":"ATRAcTR (Authentic Transparent Relevant Accurate Track-Record): a screening tool to assess the potential for real-world data sources to support creation of credible real-world evidence for regulatory decision-making","authors":"Marc L. Berger, William H. Crown, Jim Z. Li, Kelly H. Zou","doi":"10.1007/s10742-023-00319-w","DOIUrl":"https://doi.org/10.1007/s10742-023-00319-w","url":null,"abstract":"","PeriodicalId":45600,"journal":{"name":"Health Services and Outcomes Research Methodology","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139211718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-28DOI: 10.1007/s10742-023-00320-3
N. Disher, Jennifer Scott, Anna Tyzik, S. Golden, Georgia Baker, Denise M. Hynes, C. Slatore
{"title":"Evaluation of survey delivery methods in a national study of Veteran’s healthcare preferences","authors":"N. Disher, Jennifer Scott, Anna Tyzik, S. Golden, Georgia Baker, Denise M. Hynes, C. Slatore","doi":"10.1007/s10742-023-00320-3","DOIUrl":"https://doi.org/10.1007/s10742-023-00320-3","url":null,"abstract":"","PeriodicalId":45600,"journal":{"name":"Health Services and Outcomes Research Methodology","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139219232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-18DOI: 10.1007/s10742-023-00317-y
Chen Yang, M. Cuerden, Wei Zhang, Melissa Aldridge, Lihua Li
{"title":"Propensity score weighting with survey weighted data when outcomes are binary: a simulation study","authors":"Chen Yang, M. Cuerden, Wei Zhang, Melissa Aldridge, Lihua Li","doi":"10.1007/s10742-023-00317-y","DOIUrl":"https://doi.org/10.1007/s10742-023-00317-y","url":null,"abstract":"","PeriodicalId":45600,"journal":{"name":"Health Services and Outcomes Research Methodology","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2023-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139262444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-13DOI: 10.1007/s10742-023-00318-x
Gary C. McDonald, Joseph F. Willard
{"title":"Bootstrap approach to disparity testing with source uncertainty in the data","authors":"Gary C. McDonald, Joseph F. Willard","doi":"10.1007/s10742-023-00318-x","DOIUrl":"https://doi.org/10.1007/s10742-023-00318-x","url":null,"abstract":"","PeriodicalId":45600,"journal":{"name":"Health Services and Outcomes Research Methodology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136281938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-01DOI: 10.1007/s10742-023-00316-z
Saiyed Umer, Ranjeet Kumar Rout
{"title":"Descriptive and inferential analysis of features for Dysphonia and Dysarthria Parkinson’s disease symptoms","authors":"Saiyed Umer, Ranjeet Kumar Rout","doi":"10.1007/s10742-023-00316-z","DOIUrl":"https://doi.org/10.1007/s10742-023-00316-z","url":null,"abstract":"","PeriodicalId":45600,"journal":{"name":"Health Services and Outcomes Research Methodology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135270791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-24DOI: 10.1007/s10742-023-00315-0
Daniel Gomon, Julie Sijmons, Hein Putter, Jan Willem Dekker, Rob Tollenaar, Michel Wouters, Pieter Tanis, Marta Fiocco, Mirko Signorelli
Abstract During the past 14 years, a clinical audit has been used in the Netherlands to provide hospitals with data on their performance in colorectal cancer care. Continuous feedback on the quality of care provided at each hospital is essential to improve patient outcomes. It is unclear which methods should be used to generate most informative output for the identification of potential quality issues. Our aim is to compare the commonly employed funnel plot with existing cumulative sum (CUSUM) methodology for the evaluation of postoperative survival and hospital stay outcomes of patients who underwent colorectal surgery in the Netherlands. Data from the Dutch ColoRectal Audit on 25367 patients in the Netherlands who underwent surgical resection for colorectal cancer in 71 hospitals between 2019 and 2021 is used to compare four methods for the detection of deviations in the quality of care. Two methods based on binary outcomes (funnel plot, binary CUSUM) and two CUSUM charts based on survival outcomes (BK-CUSUM and CGR-CUSUM) are considered. A novel approach for determining hospital specific control limits for CUSUM charts is proposed. The ability to detect deviations as well as the time until detection are compared for the four methods. Charts were constructed for the inspection of both postoperative survival and hospital stay. Methods using survival outcomes always yielded faster detection times compared to approaches employing binary outcomes. Detections between methods mostly coincided for postoperative survival. For hospital stay detections varied strongly, with methods based on survival outcomes signalling over half the hospitals. Further pros and cons as well as pitfalls of all methods under consideration are discussed. Methodology for the continuous inspection of the quality of care should be tailored to the specific outcome. Properly understanding how the mechanism of a control chart functions is crucial for the correct interpretation of results. This is particularly true for CUSUM charts, which require the choice of a parameter that greatly influences the results. When applying CUSUM charts, consideration of these issues is strongly recommended.
{"title":"Inspecting the quality of care: a comparison of CUSUM methods for inter hospital performance","authors":"Daniel Gomon, Julie Sijmons, Hein Putter, Jan Willem Dekker, Rob Tollenaar, Michel Wouters, Pieter Tanis, Marta Fiocco, Mirko Signorelli","doi":"10.1007/s10742-023-00315-0","DOIUrl":"https://doi.org/10.1007/s10742-023-00315-0","url":null,"abstract":"Abstract During the past 14 years, a clinical audit has been used in the Netherlands to provide hospitals with data on their performance in colorectal cancer care. Continuous feedback on the quality of care provided at each hospital is essential to improve patient outcomes. It is unclear which methods should be used to generate most informative output for the identification of potential quality issues. Our aim is to compare the commonly employed funnel plot with existing cumulative sum (CUSUM) methodology for the evaluation of postoperative survival and hospital stay outcomes of patients who underwent colorectal surgery in the Netherlands. Data from the Dutch ColoRectal Audit on 25367 patients in the Netherlands who underwent surgical resection for colorectal cancer in 71 hospitals between 2019 and 2021 is used to compare four methods for the detection of deviations in the quality of care. Two methods based on binary outcomes (funnel plot, binary CUSUM) and two CUSUM charts based on survival outcomes (BK-CUSUM and CGR-CUSUM) are considered. A novel approach for determining hospital specific control limits for CUSUM charts is proposed. The ability to detect deviations as well as the time until detection are compared for the four methods. Charts were constructed for the inspection of both postoperative survival and hospital stay. Methods using survival outcomes always yielded faster detection times compared to approaches employing binary outcomes. Detections between methods mostly coincided for postoperative survival. For hospital stay detections varied strongly, with methods based on survival outcomes signalling over half the hospitals. Further pros and cons as well as pitfalls of all methods under consideration are discussed. Methodology for the continuous inspection of the quality of care should be tailored to the specific outcome. Properly understanding how the mechanism of a control chart functions is crucial for the correct interpretation of results. This is particularly true for CUSUM charts, which require the choice of a parameter that greatly influences the results. When applying CUSUM charts, consideration of these issues is strongly recommended.","PeriodicalId":45600,"journal":{"name":"Health Services and Outcomes Research Methodology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135267079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01Epub Date: 2022-12-14DOI: 10.1007/s10742-022-00297-5
Melissa McInerney, Jennifer M Mellor, Venkatesh Ramamoorthy, Lindsay M Sabik
Analysis of public policy affecting dual eligibles requires accurate identification of survey respondents eligible for both Medicare and Medicaid. Doing so for Medicaid is particularly challenging given the complex eligibility rules tied to income and assets. In this paper we provide guidance on how to best identify eligible respondents in household surveys that have limited income or asset information, such as the National Health Interview Survey (NHIS), American Community Survey (ACS), Current Population Survey (CPS), and Medical Expenditure Panel Survey (MEPS). We show how two types of errors-false negative and false positive errors-are impacted by incorporating limited income or asset information, relative to the commonly-used approach of solely comparing total income to the income threshold. With the 2018 Health and Retirement Study (HRS), which has detailed income and asset information, we mimic the income and asset information available in those other household surveys and quantify how errors change when imposing income or asset tests with limited information. We show that incorporating all available income and asset data results in the lowest number of errors and the lowest overall error rates. We recommend that researchers adjust income and impose the asset test to the fullest extent possible when imputing Medicaid eligibility for Medicare enrollees.
{"title":"Improving Identification of Medicaid Eligible Community-Dwelling Older Adults in Major Household Surveys with Limited Income or Asset Information.","authors":"Melissa McInerney, Jennifer M Mellor, Venkatesh Ramamoorthy, Lindsay M Sabik","doi":"10.1007/s10742-022-00297-5","DOIUrl":"10.1007/s10742-022-00297-5","url":null,"abstract":"<p><p>Analysis of public policy affecting dual eligibles requires accurate identification of survey respondents eligible for both Medicare and Medicaid. Doing so for Medicaid is particularly challenging given the complex eligibility rules tied to income and assets. In this paper we provide guidance on how to best identify eligible respondents in household surveys that have limited income or asset information, such as the National Health Interview Survey (NHIS), American Community Survey (ACS), Current Population Survey (CPS), and Medical Expenditure Panel Survey (MEPS). We show how two types of errors-false negative and false positive errors-are impacted by incorporating limited income or asset information, relative to the commonly-used approach of solely comparing total income to the income threshold. With the 2018 Health and Retirement Study (HRS), which has detailed income and asset information, we mimic the income and asset information available in those other household surveys and quantify how errors change when imposing income or asset tests with limited information. We show that incorporating all available income and asset data results in the lowest number of errors and the lowest overall error rates. We recommend that researchers adjust income and impose the asset test to the fullest extent possible when imputing Medicaid eligibility for Medicare enrollees.</p>","PeriodicalId":45600,"journal":{"name":"Health Services and Outcomes Research Methodology","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10598802/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54232673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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