Health Services and Outcomes Research Methodology最新文献_第2页

Evaluating Federal Policies Using Bayesian Time Series Models: Estimating the Causal Impact of the Hospital Readmissions Reduction Program. 使用贝叶斯时间序列模型评估联邦政策：估计医院再入院减少计划的因果影响。

IF 1.6

Health Services and Outcomes Research Methodology Pub Date : 2023-10-01 Epub Date: 2023-01-05 DOI: 10.1007/s10742-022-00294-8

Georgia Papadogeorgou, Fiammetta Menchetti, Christine Choirat, Jason H Wasfy, Corwin M Zigler, Fabrizia Mealli

{"title":"Evaluating Federal Policies Using Bayesian Time Series Models: Estimating the Causal Impact of the Hospital Readmissions Reduction Program.","authors":"Georgia Papadogeorgou, Fiammetta Menchetti, Christine Choirat, Jason H Wasfy, Corwin M Zigler, Fabrizia Mealli","doi":"10.1007/s10742-022-00294-8","DOIUrl":"10.1007/s10742-022-00294-8","url":null,"abstract":"<p><p>Researchers are often faced with evaluating the effect of a policy or program that was simultaneously initiated across an entire population of units at a single point in time, and its effects over the targeted population can manifest at any time period afterwards. In the presence of data measured over time, Bayesian time series models have been used to impute what would have happened after the policy was initiated, had the policy not taken place, in order to estimate causal effects. However, the considerations regarding the definition of the target estimands, the underlying assumptions, the plausibility of such assumptions, and the choice of an appropriate model have not been thoroughly investigated. In this paper, we establish useful estimands for the evaluation of large-scale policies. We discuss that imputation of missing potential outcomes relies on an assumption which, even though untestable, can be partially evaluated using observed data. We illustrate an approach to evaluate this key causal assumption and facilitate model elicitation based on data from the time interval before policy initiation and using classic statistical techniques. As an illustration, we study the Hospital Readmissions Reduction Program (HRRP), a US federal intervention aiming to improve health outcomes for patients with pneumonia, acute myocardial infraction, or congestive failure admitted to a hospital. We evaluate the effect of the HRRP on population mortality among the elderly across the US and in four geographic subregions, and at different time windows. We find that the HRRP increased mortality from pneumonia and acute myocardial infraction across at least one geographical region and time horizon, and is likely to have had a detrimental effect on public health.</p>","PeriodicalId":45600,"journal":{"name":"Health Services and Outcomes Research Methodology","volume":"56 1","pages":"433-451"},"PeriodicalIF":1.6,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11758246/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72736564","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}

引用次数: 0

Emergency department pathology order support tool (ED POST): a protocol using qualitative inquiry to inform design and development of a prototype to reduce low value care 急诊科病理命令支持工具(ED POST):一种使用定性调查来告知设计和开发原型以减少低价值护理的协议

Health Services and Outcomes Research Methodology Pub Date : 2023-09-15 DOI: 10.1007/s10742-023-00314-1

Judith Thomas, Julie Li, Craig Scowen, Alex Eigenstetter, Andrew Georgiou

{"title":"Emergency department pathology order support tool (ED POST): a protocol using qualitative inquiry to inform design and development of a prototype to reduce low value care","authors":"Judith Thomas, Julie Li, Craig Scowen, Alex Eigenstetter, Andrew Georgiou","doi":"10.1007/s10742-023-00314-1","DOIUrl":"https://doi.org/10.1007/s10742-023-00314-1","url":null,"abstract":"Abstract Laboratory tests have an important role in informing diagnosis and aiding in the determination of appropriate courses of management and/or treatment in the Emergency Department setting. Over-ordering of laboratory tests can lead to increased costs and/or unnecessary patient procedures, whilst under-ordering can lead to patient safety concerns and/or diagnostic error. Reducing over/under ordering through appropriate use of pathology has the potential to improve patient safety and/or reduce healthcare costs. As a dynamic electronic decision support tool, the Emergency Department Pathology Order Support Tool (ED POST) aims to facilitate effective ordering of pathology tests. This protocol details the methodological approach to be undertaken during the design and development of ED POST, commencing from the outset of the initial development of a prototype design. The research will undertake qualitative methods (interviews, focus group, and think-aloud observations) to develop business process models through collaboration with Emergency Department clinicians. The pre-development research will constitute stage 1 of the approach, with stage 2 focussed on evaluating the utility, usability and business process impact of the prototype to refine the prototype’s design. The collaborative and qualitative multi-method approach aims to elucidate an in-depth understanding of existing laboratory test ordering and decision-making processes in the Emergency Department, serving to inform the development of a relevant and practicable solution. Health researchers and digital health developers can draw on this approach to inform research planning activities for health information technology intervention design projects and can follow the developmental journey of ED POST as its outcomes are reported in the literature.","PeriodicalId":45600,"journal":{"name":"Health Services and Outcomes Research Methodology","volume":"242 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135396527","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}

引用次数: 0

Usability evaluation of interoperability interfaces in electronic medical record systems 电子病历系统中互操作性接口的可用性评价

IF 1.5

Health Services and Outcomes Research Methodology Pub Date : 2023-09-04 DOI: 10.1007/s10742-023-00312-3

N. Mehmood, Syed Z. Mahfooz, Saeed Faroom, Steffen Mencke, Nafees Qamar

引用次数: 0

Matching on propensity and prognostic scores can lead to different estimates of heterogeneous treatment effects: a case study and simulation 倾向和预后评分的匹配可以导致对异质治疗效果的不同估计:一个案例研究和模拟

IF 1.5

Health Services and Outcomes Research Methodology Pub Date : 2023-09-04 DOI: 10.1007/s10742-023-00313-2

D. Kabata, Y. Gon, A. Shintani

引用次数: 0

Evaluation via simulation of statistical corrections for network nonindependence 通过模拟评估网络非独立性的统计修正

IF 1.5

Health Services and Outcomes Research Methodology Pub Date : 2023-08-12 DOI: 10.1007/s10742-023-00311-4

Luke J Matthews, Megan S. Schuler, R. Vardavas, J. Breslau, Ioana Popescu

引用次数: 0

A bootstrap DEA approach to estimate residency match rate efficiency: the case of allopathic medical schools in Texas 一种估计住院医师匹配率效率的自举DEA方法:以德州对抗疗法医学院为例

IF 1.5

Health Services and Outcomes Research Methodology Pub Date : 2023-06-29 DOI: 10.1007/s10742-023-00308-z

J. Ablanedo-Rosas, Celia E. Gonzalez, Laird R. Smith, A. Ruiz-Torres, Qinglan Liu

引用次数: 0

Efficiency, quality, and management practices in multidisciplinary and traditional diabetes healthcare services in Mexico 墨西哥多学科和传统糖尿病保健服务的效率、质量和管理实践

IF 1.5

Health Services and Outcomes Research Methodology Pub Date : 2023-06-27 DOI: 10.1007/s10742-023-00309-y

Carlos Chivardi, Alejandro Zamudio Sosa, O. Galárraga, S. Sosa-Rubí

引用次数: 0

Privacy preservation of the internet of medical things using blockchain 利用区块链保护医疗物联网的隐私

IF 1.5

Health Services and Outcomes Research Methodology Pub Date : 2023-03-28 DOI: 10.1007/s10742-023-00306-1

A. Raj, Shiva Prakash

引用次数: 1

Assessing environmental performance of service supply chain using fuzzy TOPSIS method 基于模糊TOPSIS方法的服务供应链环境绩效评价

IF 1.5

Health Services and Outcomes Research Methodology Pub Date : 2023-03-24 DOI: 10.1007/s10742-023-00303-4

Sudhanshu Parashar, Sujoy Bhattacharya, Rohit Titiyal, Diya Guha Roy

引用次数: 0

Iterative proportional fitting as a balancing method in observational studies 迭代比例拟合作为观测研究中的平衡方法

IF 1.5

Health Services and Outcomes Research Methodology Pub Date : 2023-03-15 DOI: 10.1007/s10742-023-00304-3

J. Pickreign

引用次数: 0