Frontiers in digital health最新文献_第5页

Barriers to healthcare data quality and recommendations in public health facilities in Dire Dawa city administration, eastern Ethiopia: a qualitative study 埃塞俄比亚东部迪雷达瓦市公共医疗机构医疗数据质量的障碍和建议：一项定性研究

Q3 Medicine

Frontiers in digital health

Pub Date : 2024-03-14 DOI: 10.3389/fdgth.2024.1261031

Abebe Tolera, Dawit Firdisa, H. S. Roba, Aboma Motuma, Monas Kitesa, Admas Abera Abaerei

Maintaining good quality of healthcare data at various levels is a critical challenge in developing countries. The barriers to healthcare data quality remain largely unexplored in eastern Ethiopia.This study aimed to assess the barriers to quality of healthcare data in urban public health facilities in the Dire Dawa city administration from 7 April to 7 May 2019.An institutional-based qualitative exploratory approach was used among 17 purposefully selected key informants. In-depth interviews were inductively coded using the ATLAS.ti 7.5.4 version software. Inductive analysis was used by semantically analyzing the explicit content of the data to determine our themes.Several key themes and subthemes with different barriers, some of which are mutually non-exclusive, were identified. These include: Organizational Barriers: Lack of an adequate health management information system and data clerk staff, poor management commitment, lack of post-training follow-up, work overload, frequent duty rotation, lack of incentives for good performers, lack of targeted feedback, and poor culture of information use. Behavioral/Individual Barriers: Gaps in the skill of managers and health professionals, lack of adequate awareness of each indicator and its definitions, inadequate educational competence, lack of feeling of ownership, poor commitment, lack of daily tallying, and lack of value for data. Technical Barriers: Lack of a standard form, diverse and too many data entry formats, manual data collection, shortage of supplies, failure to repair system break down in a timely manner, interruption in electricity and network, delay in digitizing health information systems, lack of post-training follow-up, and inadequate supervision. External Barriers: Poor collaboration between stakeholders, dependence on the software program of non-governmental organizations, and very hot weather conditions.Diverse and complex barriers to maintenance of data quality were identified. Developing standardized health management information system implementation plans, providing advanced supervisory-level training, supportive supervision, and site-level mentorship may be very effective in identifying and resolving bottleneck data quality issues. Healthcare managers should understand the imperative of data quality and accept responsibility for its improvement and maintenance. Interventions targeted only at supplies will not fully overcome limitations to data quality. Motivation of staff and recognition of best performance can motivate others and can create cooperation among staff.

保持各级医疗数据的良好质量是发展中国家面临的一项严峻挑战。本研究旨在评估 2019 年 4 月 7 日至 5 月 7 日期间迪雷达瓦市政府城市公共医疗机构中医疗数据质量的障碍。研究采用基于机构的定性探索方法，在 17 名特意挑选的关键信息提供者中进行了研究。深入访谈使用 ATLAS.ti 7.5.4 版软件进行归纳编码。通过对数据的明确内容进行语义分析，归纳分析确定了我们的主题。确定了具有不同障碍的几个关键主题和次主题，其中一些主题是互不排斥的。这些主题包括组织障碍：缺乏足够的健康管理信息系统和数据办事员、管理层承诺不力、缺乏培训后的跟进、工作负担过重、频繁的轮岗、缺乏对表现优秀者的激励、缺乏有针对性的反馈以及信息使用文化不佳。行为/个人障碍：管理人员和保健专业人员的技能存在差距，对每项指标及其定义缺乏足够的认识，教育能力不足，缺乏主人翁感，缺乏承诺，缺乏日常统计，缺乏数据价值。技术障碍：缺乏标准表格、数据录入格式多样且过多、手工收集数据、物资短缺、未能及时修复系统故障、电力和网络中断、卫生信息系统数字化延迟、缺乏培训后跟进以及监督不足。外部障碍：利益相关者之间合作不力，依赖非政府组织的软件程序，天气炎热。制定标准化的医疗管理信息系统实施计划、提供高级主管级别的培训、支持性监督和现场指导可能会非常有效地发现和解决数据质量瓶颈问题。医疗管理人员应了解数据质量的重要性，并承担起改进和维护数据质量的责任。仅针对供应的干预措施无法完全克服数据质量的局限性。对员工的激励和对最佳表现的表彰可以调动其他人的积极性，并在员工之间建立合作关系。

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引用次数: 0

Operational disruption in healthcare associated with software functionality issue due to software security patching: a case report 软件安全补丁导致的软件功能问题引发的医疗保健业务中断：案例报告

Q3 Medicine

Frontiers in digital health

Pub Date : 2024-03-14 DOI: 10.3389/fdgth.2024.1367431

M. S. R. Jabin

Despite many benefits, the extensive deployment of Health Information Technology (HIT) systems by healthcare organizations has encountered many challenges, particularly in the field of telemetry concerning patient monitoring and its operational workflow. These challenges can add more layers of complexity when an unplanned software security patching is performed, affecting patient monitoring and causing disruption in daily clinical operations. This study is a reflection on what happened associated with software security patching and why it happened through the lens of an incident report to develop potential preventive and corrective strategies using qualitative analyses—inductive and deductive approaches. There is a need for such analyses to identify the underlying mechanism behind such issues since very limited research has been conducted on the study of software patching. The incident was classified as a “software functionality” issue, and the consequence was an “incident with a noticeable consequence but no patient harm”, and the contributing factor was a software update, i.e., software security patching. This report describes how insufficient planning of software patching, lack of training for healthcare professionals, contingency planning on unplanned system disruption, and HIT system configuration can compromise healthcare quality and cause risks to patient safety. We propose 15 preventive and corrective strategies grouped under four key areas based on the system approach and social-technical aspects of the patching process. The key areas are (i) preparing, developing, and deploying patches; (ii) training the frontline operators; (iii) ensuring contingency planning; and (iv) establishing configuration and communication between systems. These strategies are expected to minimize the risk of HIT-related incidents, enhance software security patch management in healthcare organizations, and improve patient safety. However, further discussion should be continued about general HIT problems connected to software security patching.

尽管医疗机构广泛部署医疗信息技术（HIT）系统有许多好处，但也遇到了许多挑战，尤其是在有关病人监护及其操作工作流程的遥测领域。当计划外的软件安全补丁执行时，这些挑战可能会增加复杂性，影响患者监护并导致日常临床操作中断。本研究通过事件报告的视角，对与软件安全补丁相关的事件及其原因进行了反思，并采用定性分析--归纳和演绎的方法，制定了潜在的预防和纠正策略。由于对软件修补的研究非常有限，因此有必要进行此类分析，以确定此类问题背后的潜在机制。该事件被归类为 "软件功能 "问题，其后果是 "有明显后果但未对患者造成伤害的事件"，其促成因素是软件更新，即软件安全补丁。本报告介绍了软件补丁规划不足、医护人员缺乏培训、计划外系统中断的应急规划以及 HIT 系统配置如何影响医疗质量并给患者安全带来风险。我们根据补丁程序的系统方法和社会技术方面，提出了 15 项预防和纠正策略，分为四个关键领域。这些关键领域包括：(i) 准备、开发和部署补丁；(ii) 培训一线操作人员；(iii) 确保应急计划；(iv) 建立系统之间的配置和通信。这些策略有望最大限度地降低与 HIT 相关的事故风险，加强医疗机构的软件安全补丁管理，提高患者安全。不过，还应继续讨论与软件安全补丁相关的一般 HIT 问题。

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引用次数: 0

Supporting autistic communities through parent-led and child/young person-led digital social story interventions: an exploratory study 通过家长和儿童/青少年主导的数字社交故事干预措施支持自闭症社区：一项探索性研究

Q3 Medicine

Frontiers in digital health

Pub Date : 2024-03-13 DOI: 10.3389/fdgth.2024.1355795

L. Camilleri, Katie Maras, Mark Brosnan

Social Stories (SS) is a socially-valid intervention for autistic children and young people (CYP) which is used widely by professionals and parents. Research suggests that whilst parents are in an ideal position to deliver interventions for their autistic CYP, a lack of procedural integrity can result in a great deal of variability in parent-mediated intervention outcomes.This exploratory study investigated the extent to which SS can be effectively developed and delivered, through digital mediation, by parents with little to no researcher input (n = 17, sample 1) and the factors that impact effectiveness. Furthermore, the study also investigated the extent to which digitally-mediated SS can support autistic CYP to develop and deliver their own stories, thereby utilising the intervention as a means for self-support and self-management (n = 5, sample 2).The outcomes of the study indicate that digital mediation can effectively support parent-led SS intervention. Findings also indicate that receptive/expressive language skills of autistic CYP, their level of systemizing, as well as the practice of consulting with the autistic CYP whilst identifying goals and developing stories, are individual and procedural characteristics which positively influence the effectiveness of the parent-led intervention. The study also found that digitally-mediated SS can be utilised as a self-support tool by autistic CYP themselves.The results inform the developing literature on digital interventions and support tools that aim to engage with, and involve further, the autistic community in the setting and authoring of interventions and research.

社交故事（SS）是一种针对自闭症儿童和青少年（CYP）的社会有效干预措施，被专业人士和家长广泛使用。本探索性研究调查了在几乎没有研究人员参与的情况下，家长通过数字中介有效开发和实施社交故事的程度（n = 17，样本 1），以及影响效果的因素。此外，本研究还调查了以数字为媒介的社会服务在多大程度上可以支持自闭症儿童青少年开发和传播他们自己的故事，从而将干预作为自我支持和自我管理的一种手段（样本 2，n = 5）。研究结果表明，数字媒介可以有效支持家长主导的社会服务干预。研究结果还表明，自闭症儿童的接受/表达语言能力、他们的系统化水平，以及在确定目标和编写故事时与自闭症儿童进行协商的做法，都是对家长主导的干预效果产生积极影响的个人和程序特征。研究还发现，自闭症儿童青少年可以利用以数字为媒介的社会支持系统作为自我支持工具。研究结果为有关数字干预和支持工具的文献发展提供了信息，这些干预和支持工具旨在让自闭症社区参与并进一步参与干预和研究的制定和创作。

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引用次数: 0

Active transfer learning for audiogram estimation 听力图估算的主动迁移学习

Q3 Medicine

Frontiers in digital health

Pub Date : 2024-03-11 DOI: 10.3389/fdgth.2024.1267799

H. Twinomurinzi, Herman Myburgh, Dennis L. Barbour

Computational audiology (CA) has grown over the last few years with the improvement of computing power and the growth of machine learning (ML) models. There are today several audiogram databases which have been used to improve the accuracy of CA models as well as reduce testing time and diagnostic complexity. However, these CA models have mainly been trained on single populations. This study integrated contextual and prior knowledge from audiogram databases of multiple populations as informative priors to estimate audiograms more precisely using two mechanisms: (1) a mapping function drawn from feature-based homogeneous Transfer Learning (TL) also known as Domain Adaptation (DA) and (2) Active Learning (Uncertainty Sampling) using a stream-based query mechanism. Simulations of the Active Transfer Learning (ATL) model were tested against a traditional adaptive staircase method akin to the Hughson-Westlake (HW) method for the left ear at frequencies ω=0.25,0.5,1,2,4,8 kHz, resulting in accuracy and reliability improvements. ATL improved HW tests from a mean of 41.3 sound stimuli presentations and reliability of ±9.02 dB down to 25.3±1.04 dB. Integrating multiple databases also resulted in classifying the audiograms into 18 phenotypes, which means that with increasing data-driven CA, higher precision is achievable, and a possible re-conceptualisation of the notion of phenotype classifications might be required. The study contributes to CA in identifying an ATL mechanism to leverage existing audiogram databases and CA models across different population groups. Further studies can be done for other psychophysical phenomena using ATL.

过去几年来，随着计算能力的提高和机器学习（ML）模型的发展，计算听力学（CA）也在不断发展。如今，已有多个听力图数据库用于提高计算听力学模型的准确性，并减少测试时间和诊断复杂性。然而，这些 CA 模型主要是在单一人群中进行训练的。本研究整合了多人群听力图数据库中的上下文知识和先验知识作为信息先验，利用两种机制更精确地估计听力图：（1）从基于特征的同质迁移学习（TL）（也称为领域适应（DA））中提取的映射函数；（2）使用基于流的查询机制的主动学习（不确定性采样）。在频率ω=0.25,0.5,1,2,4,8 kHz时，对主动迁移学习（ATL）模型与传统的自适应阶梯方法（类似于左耳的休森-韦斯特莱克（HW）方法）进行了模拟测试，从而提高了准确性和可靠性。ATL 将 HW 测试从平均 41.3 次声音刺激呈现和 ±9.02 dB 的可靠性降低到 25.3±1.04 dB。通过整合多个数据库，还将听力图分为 18 种表型，这意味着随着数据驱动 CA 的增加，可以实现更高的精确度，可能需要对表型分类的概念进行重新构思。这项研究为听觉分类做出了贡献，它确定了一种 ATL 机制，以利用现有的听力图数据库和听觉分类模型，跨越不同的人群。还可以利用 ATL 对其他心理物理现象进行进一步研究。

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引用次数: 0

eHealth implementation in Europe: a scoping review on legal, ethical, financial, and technological aspects. 欧洲的电子保健实施情况：法律、伦理、财务和技术方面的范围审查。

Q3 Medicine

Frontiers in digital health

Pub Date : 2024-03-08 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1332707

Britt E Bente, Anne Van Dongen, Ruud Verdaasdonk, Lisette van Gemert-Pijnen

Background: The evolution of eHealth development has shifted from standalone tools to comprehensive digital health environments, fostering data exchange among diverse stakeholders and systems. Nevertheless, existing research and implementation frameworks have primarily emphasized technological and organizational aspects of eHealth implementation, overlooking the intricate legal, ethical, and financial considerations. It is essential to discover what legal, ethical, financial, and technological challenges should be considered to ensure successful and sustainable implementation of eHealth.

Objective: This review aims to provide insights into barriers and facilitators of legal, ethical, financial, and technological aspects for successful implementation of complex eHealth technologies, which impacts multiple levels and multiple stakeholders.

Methods: A scoping review was conducted by querying PubMed, Scopus, Web of Science, and ACM Digital Library (2018-2023) for studies describing the implementation process of eHealth technologies that facilitate data exchange. Studies solely reporting clinical outcomes or conducted outside Europe were excluded. Two independent reviewers selected the studies. A conceptual framework was constructed through axial and inductive coding, extracting data from literature on legal, ethical, financial, and technological aspects of eHealth implementation. This framework guided systematic extraction and interpretation.

Results: The search resulted in 7.308 studies that were screened for eligibility, of which 35 (0.48%) were included. Legal barriers revolve around data confidentiality and security, necessitating clear regulatory guidelines. Ethical barriers span consent, responsibility, liability, and validation complexities, necessitating robust frameworks. Financial barriers stem from inadequate funding, requiring (commercial) partnerships and business models. Technological issues include interoperability, integration, and malfunctioning, necessitating strategies for enhancing data reliability, improving accessibility, and aligning eHealth technology with existing systems for smoother integration.

Conclusions: This research highlights the multifaceted nature of eHealth implementation, encompassing legal, ethical, financial, and technological considerations. Collaborative stakeholder engagement is paramount for effective decision-making and aligns with the transition from standalone eHealth tools to integrated digital health environments. Identifying suitable stakeholders and recognizing their stakes and values enriches implementation strategies with expertise and guidance across all aspects. Future research should explore the timing of these considerations and practical solutions for regulatory compliance, funding, navigation of responsibility and liability, and business models for reimbursement strategies.

背景：电子医疗的发展已从独立的工具转变为全面的数字医疗环境，促进了不同利益相关者和系统之间的数据交换。然而，现有的研究和实施框架主要强调电子医疗实施的技术和组织方面，而忽略了错综复杂的法律、伦理和财务方面的考虑。有必要了解应考虑哪些法律、伦理、财务和技术挑战，以确保电子医疗的成功和可持续实施：本综述旨在深入探讨法律、伦理、财务和技术方面的障碍和促进因素，以便成功实施复杂的电子医疗技术，这将对多个层面和多个利益相关者产生影响：通过查询 PubMed、Scopus、Web of Science 和 ACM 数字图书馆（2018-2023 年），对描述促进数据交换的电子健康技术实施过程的研究进行了范围界定。仅报告临床结果或在欧洲以外进行的研究被排除在外。两位独立审稿人对研究进行了筛选。通过轴向编码和归纳编码，从有关电子医疗实施的法律、伦理、财务和技术方面的文献中提取数据，构建了一个概念框架。该框架为系统性提取和解释提供了指导：通过检索，筛选出 7308 项研究符合条件，其中 35 项（0.48%）被纳入。法律障碍围绕数据的保密性和安全性，需要明确的监管准则。伦理障碍涉及同意、责任、义务和验证的复杂性，因此需要强有力的框架。资金障碍源于资金不足，需要（商业）伙伴关系和业务模式。技术问题包括互操作性、集成和故障，因此需要制定战略来提高数据可靠性、改善可访问性，并使电子健康技术与现有系统保持一致，以实现更顺畅的集成：本研究强调了电子医疗实施的多面性，包括法律、道德、财务和技术方面的考虑。利益相关者的合作参与对于有效决策至关重要，并与从独立的电子医疗工具向集成的数字医疗环境过渡相一致。确定合适的利益相关者并认识到他们的利害关系和价值观，可以丰富实施策略，为其提供各方面的专业知识和指导。未来的研究应探讨这些考虑因素的时间安排，以及监管合规、资金、责任和义务的引导以及报销策略的商业模式等方面的实用解决方案。

{"title":"eHealth implementation in Europe: a scoping review on legal, ethical, financial, and technological aspects.","authors":"Britt E Bente, Anne Van Dongen, Ruud Verdaasdonk, Lisette van Gemert-Pijnen","doi":"10.3389/fdgth.2024.1332707","DOIUrl":"10.3389/fdgth.2024.1332707","url":null,"abstract":"Background: The evolution of eHealth development has shifted from standalone tools to comprehensive digital health environments, fostering data exchange among diverse stakeholders and systems. Nevertheless, existing research and implementation frameworks have primarily emphasized technological and organizational aspects of eHealth implementation, overlooking the intricate legal, ethical, and financial considerations. It is essential to discover what legal, ethical, financial, and technological challenges should be considered to ensure successful and sustainable implementation of eHealth.Objective: This review aims to provide insights into barriers and facilitators of legal, ethical, financial, and technological aspects for successful implementation of complex eHealth technologies, which impacts multiple levels and multiple stakeholders.Methods: A scoping review was conducted by querying PubMed, Scopus, Web of Science, and ACM Digital Library (2018-2023) for studies describing the implementation process of eHealth technologies that facilitate data exchange. Studies solely reporting clinical outcomes or conducted outside Europe were excluded. Two independent reviewers selected the studies. A conceptual framework was constructed through axial and inductive coding, extracting data from literature on legal, ethical, financial, and technological aspects of eHealth implementation. This framework guided systematic extraction and interpretation.Results: The search resulted in 7.308 studies that were screened for eligibility, of which 35 (0.48%) were included. Legal barriers revolve around data confidentiality and security, necessitating clear regulatory guidelines. Ethical barriers span consent, responsibility, liability, and validation complexities, necessitating robust frameworks. Financial barriers stem from inadequate funding, requiring (commercial) partnerships and business models. Technological issues include interoperability, integration, and malfunctioning, necessitating strategies for enhancing data reliability, improving accessibility, and aligning eHealth technology with existing systems for smoother integration.Conclusions: This research highlights the multifaceted nature of eHealth implementation, encompassing legal, ethical, financial, and technological considerations. Collaborative stakeholder engagement is paramount for effective decision-making and aligns with the transition from standalone eHealth tools to integrated digital health environments. Identifying suitable stakeholders and recognizing their stakes and values enriches implementation strategies with expertise and guidance across all aspects. Future research should explore the timing of these considerations and practical solutions for regulatory compliance, funding, navigation of responsibility and liability, and business models for reimbursement strategies.","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10957613/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140208311","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

Toward mechanistic medical digital twins: some use cases in immunology. 迈向机理医学数字双胞胎：免疫学中的一些用例。

Q3 Medicine

Frontiers in digital health

Pub Date : 2024-03-07 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1349595

Reinhard Laubenbacher, Fred Adler, Gary An, Filippo Castiglione, Stephen Eubank, Luis L Fonseca, James Glazier, Tomas Helikar, Marti Jett-Tilton, Denise Kirschner, Paul Macklin, Borna Mehrad, Beth Moore, Virginia Pasour, Ilya Shmulevich, Amber Smith, Isabel Voigt, Thomas E Yankeelov, Tjalf Ziemssen

A fundamental challenge for personalized medicine is to capture enough of the complexity of an individual patient to determine an optimal way to keep them healthy or restore their health. This will require personalized computational models of sufficient resolution and with enough mechanistic information to provide actionable information to the clinician. Such personalized models are increasingly referred to as medical digital twins. Digital twin technology for health applications is still in its infancy, and extensive research and development is required. This article focuses on several projects in different stages of development that can lead to specific-and practical-medical digital twins or digital twin modeling platforms. It emerged from a two-day forum on problems related to medical digital twins, particularly those involving an immune system component. Open access video recordings of the forum discussions are available.

个性化医疗面临的一个基本挑战是，如何充分捕捉个体患者的复杂性，以确定保持其健康或恢复其健康的最佳方法。这就要求个性化计算模型具有足够的分辨率和足够的机理信息，以便为临床医生提供可操作的信息。这种个性化模型越来越多地被称为医学数字孪生。用于医疗应用的数字孪生技术仍处于起步阶段，需要进行广泛的研究和开发。本文重点介绍几个处于不同开发阶段的项目，这些项目可以开发出具体实用的医疗数字孪生或数字孪生建模平台。本文是为期两天的医学数字孪生相关问题论坛的成果，尤其是那些涉及免疫系统的问题。论坛讨论的视频录像可公开获取。

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引用次数: 0

Enhancing patient outcomes: the role of clinical utility in guiding healthcare providers in curating radiology AI applications. 提高患者疗效：临床实用性在指导医疗服务提供者策划放射学人工智能应用中的作用。

Q3 Medicine

Frontiers in digital health

Pub Date : 2024-03-07 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1359383

Franziska Lobig, Jacob Graham, Apeksha Damania, Brian Sattin, Joana Reis, Prateek Bharadwaj

With advancements in artificial intelligence (AI) dominating the headlines, diagnostic imaging radiology is no exception to the accelerating role that AI is playing in today's technology landscape. The number of AI-driven radiology diagnostic imaging applications (digital diagnostics) that are both commercially available and in-development is rapidly expanding as are the potential benefits these tools can deliver for patients and providers alike. Healthcare providers seeking to harness the potential benefits of digital diagnostics may consider evaluating these tools and their corresponding use cases in a systematic and structured manner to ensure optimal capital deployment, resource utilization, and, ultimately, patient outcomes-or clinical utility. We propose several guiding themes when using clinical utility to curate digital diagnostics.

人工智能（AI）的发展占据了各大媒体的头条，放射诊断成像技术也不例外，人工智能在当今的技术领域正扮演着越来越重要的角色。人工智能驱动的放射诊断成像应用（数字诊断）的数量正在迅速增加，这些应用既有商业化的，也有正在开发中的，而这些工具能为患者和医疗服务提供者带来的潜在益处也在迅速扩大。医疗服务提供商在寻求利用数字诊断学的潜在优势时，可以考虑以系统化和结构化的方式评估这些工具及其相应的用例，以确保最佳的资本部署、资源利用，并最终实现患者的治疗效果或临床效用。在利用临床效用来策划数字诊断时，我们提出了几个指导性主题。

引用次数: 0

Smart hospital: achieving interoperability and raw data collection from medical devices in clinical routine. 智能医院：实现临床常规医疗设备的互操作性和原始数据收集。

Q3 Medicine

Frontiers in digital health

Pub Date : 2024-03-06 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1341475

Eimo Martens, Hans-Ulrich Haase, Giulio Mastella, Andreas Henkel, Christoph Spinner, Franziska Hahn, Congyu Zou, Augusto Fava Sanches, Julia Allescher, Daniel Heid, Elena Strauss, Melanie-Maria Maier, Mark Lachmann, Georg Schmidt, Dominik Westphal, Tobias Haufe, David Federle, Daniel Rueckert, Martin Boeker, Matthias Becker, Karl-Ludwig Laugwitz, Alexander Steger, Alexander Müller

Introduction: Today, modern technology is used to diagnose and treat cardiovascular disease. These medical devices provide exact measures and raw data such as imaging data or biosignals. So far, the Broad Integration of These Health Data into Hospital Information Technology Structures-Especially in Germany-is Lacking, and if data integration takes place, only non-Evaluable Findings are Usually Integrated into the Hospital Information Technology Structures. A Comprehensive Integration of raw Data and Structured Medical Information has not yet Been Established. The aim of this project was to design and implement an interoperable database (cardio-vascular-information-system, CVIS) for the automated integration of al medical device data (parameters and raw data) in cardio-vascular medicine.

Methods: The CVIS serves as a data integration and preparation system at the interface between the various devices and the hospital IT infrastructure. In our project, we were able to establish a database with integration of proprietary device interfaces, which could be integrated into the electronic health record (EHR) with various HL7 and web interfaces.

Results: In the period between 1.7.2020 and 30.6.2022, the data integrated into this database were evaluated. During this time, 114,858 patients were automatically included in the database and medical data of 50,295 of them were entered. For technical examinations, more than 4.5 million readings (an average of 28.5 per examination) and 684,696 image data and raw signals (28,935 ECG files, 655,761 structured reports, 91,113 x-ray objects, 559,648 ultrasound objects in 54 different examination types, 5,000 endoscopy objects) were integrated into the database. Over 10.2 million bidirectional HL7 messages (approximately 14,000/day) were successfully processed. 98,458 documents were transferred to the central document management system, 55,154 materials (average 7.77 per order) were recorded and stored in the database, 21,196 diagnoses and 50,353 services/OPS were recorded and transferred. On average, 3.3 examinations per patient were recorded; in addition, there are an average of 13 laboratory examinations.

Discussion: Fully automated data integration from medical devices including the raw data is feasible and already creates a comprehensive database for multimodal modern analysis approaches in a short time. This is the basis for national and international projects by extracting research data using FHIR.

简介如今，现代技术已被用于诊断和治疗心血管疾病。这些医疗设备可提供精确的测量数据和原始数据，如成像数据或生物信号。到目前为止，这些健康数据还没有被广泛整合到医院信息技术结构中（尤其是在德国），即使进行了数据整合，通常也只是将无价值的结果整合到医院信息技术结构中。原始数据和结构化医疗信息的全面整合尚未建立。本项目旨在设计和实施一个可互操作的数据库（心血管信息系统，CVIS），用于自动整合心血管医学中所有医疗设备数据（参数和原始数据）：方法：CVIS 是各种设备与医院 IT 基础设施之间的数据集成和准备系统。在我们的项目中，我们建立了一个集成了专有设备接口的数据库，该数据库可通过各种 HL7 和网络接口集成到电子病历（EHR）中：在 2020 年 7 月 1 日至 2022 年 6 月 30 日期间，我们对整合到该数据库中的数据进行了评估。在此期间，共有 114 858 名患者被自动纳入数据库，其中 50 295 人的医疗数据已被输入。在技术检查方面，超过 450 万个读数（平均每个检查 28.5 个读数）、684,696 个图像数据和原始信号（28,935 个心电图文件、655,761 个结构化报告、91,113 个 X 光对象、54 种不同检查类型中的 559,648 个超声波对象、5,000 个内窥镜检查对象）被纳入数据库。成功处理了 1020 多万条双向 HL7 信息（每天约 14000 条）。98,458 份文件被传送到中央文件管理系统，55,154 份材料（平均每份订单 7.77 份）被记录并储存在数据库中，21,196 项诊断和 50,353 项服务/OPS 被记录并传送。平均每个病人记录了 3.3 次检查；此外，平均还有 13 次实验室检查：讨论：医疗设备的全自动数据整合（包括原始数据）是可行的，并且已经在短时间内为多模式现代分析方法创建了一个全面的数据库。这是通过使用 FHIR 提取研究数据开展国内和国际项目的基础。

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引用次数: 0

Digital loneliness-changes of social recognition through AI companions. 数字孤独--通过人工智能伴侣改变社会认知。

Q3 Medicine

Frontiers in digital health

Pub Date : 2024-03-05 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1281037

Kerrin Artemis Jacobs

Inherent to the experience of loneliness is a significant change of meaningful relatedness that (usually negatively) affects a person's relationship to self and others. This paper goes beyond a purely subjective-phenomenological description of individual suffering by emphasizing loneliness as a symptomatic expression of distortions of social recognition relations. Where there is loneliness, a recognition relation has changed. Most societies face an increase in loneliness among all groups of their population, and this sheds light on the reproduction conditions of social integration and inclusion. These functions are essential lifeworldly components of social cohesion and wellbeing. This study asks whether "social" AI promotes these societal success goals of social integration of lonely people. The increasing tendency to regard AI Companions (AICs) as reproducers of adequate recognition is critically discussed with this review. My skepticism requires further justification, especially as a large portion of sociopolitical prevention efforts aim to fight an increase of loneliness primarily with digital strategies. I will argue that AICs rather reproduce than sustainably reduce the pathodynamics of loneliness: loneliness gets simply "digitized."

孤独感的内在体验是有意义的关系发生了重大变化，这种变化（通常是负面的）影响了一个人与自我和他人的关系。本文超越了对个人痛苦的纯主观现象学描述，强调孤独是社会认可关系扭曲的症状表现。哪里存在孤独，哪里的认可关系就发生了变化。大多数社会的所有人群都面临着孤独感增加的问题，这揭示了社会融合和包容的再生产条件。这些功能是社会凝聚力和福祉的基本生活世界组成部分。本研究提出的问题是，"社交 "人工智能是否能促进孤独者融入社会的这些社会成功目标。越来越多的人倾向于将人工智能伴侣（AIC）视为充分认可的再现者，本评论对此进行了批判性讨论。我的怀疑需要更多的理由，尤其是社会政治预防工作的很大一部分都旨在主要通过数字战略来对抗孤独感的增加。我将论证，"AIC "与其说是可持续地减少孤独的病理动力，不如说是在复制孤独：孤独被简单地 "数字化 "了。

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引用次数: 0

Unlocking the potential of telehealth in Africa for HIV: opportunities, challenges, and pathways to equitable healthcare delivery. 释放非洲远程保健在防治艾滋病毒方面的潜力：机遇、挑战和公平提供保健服务的途径。

Q3 Medicine

Frontiers in digital health

Pub Date : 2024-03-04 eCollection Date: 2024-01-01 DOI: 10.3389/fdgth.2024.1278223

Diego F Cuadros, Qian Huang, Thulile Mathenjwa, Dickman Gareta, Chayanika Devi, Godfrey Musuka

引用次数: 0