medRxiv - Health Systems and Quality Improvement最新文献_第9页

Socioeconomic and demographic patterning of family uptake of a paediatric electronic patient portal innovation 儿科电子患者门户网站创新的社会经济和人口结构模式图

medRxiv - Health Systems and Quality Improvement Pub Date : 2024-04-15 DOI: 10.1101/2024.04.13.24305151

Ameenat Lola Solebo, Lisanne Horvat-Gitsels, Christine Twomey, Siegfried Karl Wagner, Jugnoo S Rahi

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Stage-aware Brain Graph Learning for Alzheimer’s Disease 针对阿尔茨海默病的阶段感知脑图学习

medRxiv - Health Systems and Quality Improvement Pub Date : 2024-04-15 DOI: 10.1101/2024.04.14.24305804

Ciyuan Peng, Mujie Liu, Chenxuan Meng, Sha Xue, Kathleen Keogh, Feng Xia

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The development of the gynecologic oncology pathway “VivaPathway GT“ – a qualitative study about the transformation from an implicit to an explicit, evidence-based clinical pathway in a Berlin-based tertiary care hospital 妇科肿瘤路径 "VivaPathway GT "的发展--关于柏林一家三级医院从隐性到显性循证临床路径转变的定性研究

medRxiv - Health Systems and Quality Improvement Pub Date : 2024-04-15 DOI: 10.1101/2024.04.14.24305788

Anne Büscher, Nicolle Reinhold, Joachim Kugler

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A health systems analysis of non-compliance to the maternity referral system by health facilities in Uganda: Findings from a mixed-methods study 对乌干达医疗机构不遵守产科转诊制度的医疗系统分析：混合方法研究的结果

medRxiv - Health Systems and Quality Improvement Pub Date : 2024-04-09 DOI: 10.1101/2024.04.08.24305473

Henry Zakumumpa, Caroline Kyozira, Martin Bulamu, Remmy Buhuguru

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“It’s not about the money, money” - Well, actually it is. Divergent views on drivers of early phase clinical trial participation among ethnically diverse potential trial participants in the United Kingdom: A Mixed Methods Study "这不是钱的问题，是钱的问题"--其实就是钱的问题。英国不同种族的潜在试验参与者对早期临床试验参与驱动因素的不同看法：混合方法研究

medRxiv - Health Systems and Quality Improvement Pub Date : 2024-04-05 DOI: 10.1101/2024.04.04.24305355

Pilar Artiach Hortelano, Neil Morton, Paul Wicks, Michael Young, Rebecca Burdell, Duncan Richards

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DOES QUALITY OF COUNSELING AND EXPOSURE TO FAMILY PLANNING MESSAGES INFLUENCE THE USE OF MODERN CONTRACEPTIVES AMONG WOMEN IN NORTHERN NIGERIA? 咨询质量和接触计划生育信息是否会影响尼日利亚北部妇女使用现代避孕药具？

medRxiv - Health Systems and Quality Improvement Pub Date : 2024-04-03 DOI: 10.1101/2024.04.03.24305214

Matthew Alabi, Leanne Dougherty, Eno-Obong Etim, Adebola Adedimeji

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A simple mathematical model and physical device to estimate a woman-specific probability of skilled birth assistance and associated benefit of maternity waiting home stay 利用简单数学模型和物理装置估算妇女获得熟练助产服务的概率以及待产室留宿的相关益处

medRxiv - Health Systems and Quality Improvement Pub Date : 2024-04-03 DOI: 10.1101/2024.04.02.24305221

Jérémie Gallien, George Chen, Yi Zhang, Yuhang Du, Jody Lori, Joseph Sieka, Bentoe Tehoungue

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Addressing unmet social needs using a health navigator for patients at a major metropolitan hospital in Australia: a mixed-methods feasibility study 利用健康导航仪为澳大利亚一家大型都市医院的患者解决未满足的社会需求：一项混合方法可行性研究

medRxiv - Health Systems and Quality Improvement Pub Date : 2024-04-03 DOI: 10.1101/2024.04.02.24305238

K Neadley, C Shoubridge, A Smith, S Martin, M Boyd, C Hocking

引用次数: 0

“…but I know something’s not right here”: Exploring the diagnosis and disclosure experiences of persons living with ALS "......但我知道这里有些不对劲"：探讨 ALS 患者的诊断和披露经历

medRxiv - Health Systems and Quality Improvement Pub Date : 2024-03-19 DOI: 10.1101/2024.03.14.24304312

Kathleen M. Foldvari, Paul Stolee, Elena Neiterman, Veronique M. Boscart, Catherine Tong

{"title":"“…but I know something’s not right here”: Exploring the diagnosis and disclosure experiences of persons living with ALS","authors":"Kathleen M. Foldvari, Paul Stolee, Elena Neiterman, Veronique M. Boscart, Catherine Tong","doi":"10.1101/2024.03.14.24304312","DOIUrl":"https://doi.org/10.1101/2024.03.14.24304312","url":null,"abstract":"Background: Amyotrophic Lateral Sclerosis (ALS), an incurable motor neuron disease, primarily affects those between the ages of 60-79, and has an approximate post-diagnosis life--expectancy of only two to five years. The condition has an unpredictable but ultimately terminal trajectory that poses a number of challenges for patients, caregivers and healthcare providers. While the diagnosis and disclosure are critical periods for intervention and support, knowledge regarding the relational, communicational and psychodynamic forces that occur within the process of diagnostic disclosure is relatively limited. Objectives: The purpose of this study was to explore the experiences of persons living with ALS in the diagnosis and disclosure of the condition, and the experiences of their caregivers. Methods: We conducted a focus group and in-depth individual interviews with Canadians living with ALS (n = 9), family caregivers (n = 7), a professional caregiver (n = 1), and one past caregiver (1). The interviews were transcribed, cleaned, and anonymized, and then entered into NVivo 11 for thematic analysis. Results: Participants discussed the diagnosis process, including the inklings and subtle changes prior to diagnosis, attempts at self-diagnosis, and the lengthy assessment process. Time was also a consideration in the disclosure process, in which participants shared how the diagnosis disclosure was the product of longstanding conversations with their care providers. It was described as rarely a shock to finally have confirmation. Additionally, participants shared their information seeking strategies and needs for a diagnosis that, for them, typically came with insufficient information on the disease, prognosis, and next steps. Significance: This project serves as an initial step in bridging the relevant gaps in our knowledge and understanding towards improved patient-centered care practices in the diagnosis and disclosure of ALS.","PeriodicalId":501556,"journal":{"name":"medRxiv - Health Systems and Quality Improvement","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140168957","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

A Survey on Optimization and Machine -learning-based Fair Decision Making in Healthcare 基于优化和机器学习的医疗公平决策调查

medRxiv - Health Systems and Quality Improvement Pub Date : 2024-03-18 DOI: 10.1101/2024.03.16.24304403

Zequn Chen, Wesley J. Marrero

{"title":"A Survey on Optimization and Machine -learning-based Fair Decision Making in Healthcare","authors":"Zequn Chen, Wesley J. Marrero","doi":"10.1101/2024.03.16.24304403","DOIUrl":"https://doi.org/10.1101/2024.03.16.24304403","url":null,"abstract":"Background. Unintended biases introduced by optimization and machine learning (ML) models are of great interest to medical professionals. Bias in healthcare decisions can cause patients from vulnerable populations (e.g., racially minoritized, low-income) to have lower access to resources, exacerbating societal unfairness. Purpose. This review aims to identify, describe, and categorize literature regarding bias types, fairness metrics, and bias mitigation methods in healthcare decision making. Data Sources. Google Scholar database was searched to identify published studies. Study Selection. Eligible studies were required to present 1) types of bias 2) fairness metrics and 3) bias mitigation methods within decision-making in healthcare. Data Extraction. Studies were classified according to the three themes mentioned in the Study Selection. Information was extracted concerning the definitions, examples, applications, and limitations of bias types, fairness metrics, and bias mitigation methods. Data Synthesis. In bias type section, we included studies (n=15) concerning different biases. In the fairness metric section, we included studies (n=6) regarding common fairness metrics. In bias mitigation method section, themes included pre-processing methods (n=5), in-processing methods (n=16), and post-processing methods (n=4). Limitations. Most examples in our survey are from the United States since the majority of studies included in this survey were conducted in the United States. In the meanwhile, we limited the search language to English, so we may not capture some meaningful articles in other languages. Conclusions. Several types of bias, fairness metrics, and bias mitigation methods (especially optimization and machine learning-based methods) were identified in this review, with common themes based on analytical approaches. We also found topics such as explainability, fairness metric selection, and integration of prediction and optimization are promising directions for future studies.","PeriodicalId":501556,"journal":{"name":"medRxiv - Health Systems and Quality Improvement","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140168960","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