医疗健康大数据发展现状研究

通过介绍国内外医疗健康大数据发展计划、学术组织、标准化组织、研究领域、研究项目和开放数据资源等相关主题,反映了医疗健康大数据的发展现状与动态,可为医疗健康大数据应用和研究提供参考。     

我国医疗服务数据中心发展现状

医疗服务数据中心能够通过对医疗数据的采集、存储、维护和分析,在评价和提升患者安全、助力医疗质量管理、为患者就医提供导向、推动生物银行的建设发展等方面发挥着非常重要的作用。尽管相比发达国家,我国的国家医疗服务数据中心的建设起步较晚,但已在指导医疗服务和服务医疗管理方面取得了一定的成绩。     

医疗数据开放方法及策略研究

医疗数据开放可为患者、医技人员和医学科研人员等提供所需医疗信息。医疗数据开放有助于提升数据价值,改善信息透明度。文章介绍了国内外医疗数据开放研究和应用现状,在辨析共享数据、公开数据和开放数据三者区别与联系的基础上,阐述了医疗数据开放的方法,并对如何开放医疗数据提出相关对策与建议。     

九江市区域医疗联合体建设的实践与思考

介绍了九江市区域医疗联合体建设的基本情况、联合模式、主要做法以及主要成效,分析了医疗联合体运行过程中存在的一些共性问题。可借鉴国内医疗联合体建设的成功经验,进一步完善运作模式,推动医疗联合体健康发展。     

基于全过程医疗质量管理思想的临床数据存储库设计

全过程医疗质量管理是指医院对患者诊疗全流程的每个环节、每个处置都处于受控的状态,把影响医疗质量的问题降到最低,以取得最佳的医疗效果。全过程医疗质量管理除了对终末质量（大约占质控点的20%）进行控制外,重点是对过程中质量（大约占质控点的80%）进行控制,如何把全过程医疗质量管理与IT技术更好的结合起来,利用临床数据存储库（Clinical Data Repository,CDR）的建立来实现对医疗质量的实时管控,已成为当前医院信息化建设工作的主要任务。     

2022年数字健康发展态势

生物技术、数字技术等新兴技术的快速发展，为面向人民生命健康的融合创新提供了源动力，“数字健康”应运而生。近年来，随着居民收入的增加、消费结构的升级、人口老龄化及城镇化的加速发展，数字健康的应用场景不断丰富，发展空间不断拓展。2022年，国内外数字健康科技与产业均取得了新发展，包括政策的推动、前沿技术的突破以及产品的上市等。本文从政策、科技以及产业的创新链角度总结了数字健康的最新进展，并对数字健康的发展趋势进行展望。     

居民健康卡服务体系跨机构协同建设探讨

居民健康卡服务体系的建设横跨金融行业和医疗行业、卫生管理部门和医院、制卡机构和发卡机构,在省卫生厅的直接管理下开展。文章遵循部颁居民健康卡标准体系,对居民健康卡的制作、发行、业务受理和管理等4个环节进行了统一规划,研究了制卡机构、发卡机构、业务受理机构和管理机构如何分工建设居民健康卡服务体系,以实现居民健康卡跨地区、跨医疗机构就诊一卡通。     

构建医疗质量决策平台 促进精细化管理

信息技术为医院全面质量管理提供了巨大支持。本文通过建立医疗质量决策平台对医院终末质量管理进行提升。利用来自各环节医疗活动的数据,通过融合、加工、分析,获得医疗质量相关指标,并通过图形化报表工具进行展现,为医疗质量控制和精细化管理提供了决策依据。     

新医改背景下医疗设备信息化管理存在的问题及解决对策探究

医疗设备是医院的重要资产,可在一定程度上反映医院的诊断能力以及现代化程度。新医改政策出台后,各地均大力推进医药卫生信息化建设,随着医疗设备种类的增加,给医院设备管理带来一定的困难,医疗设备信息化管理已成为医院不可或缺的一部分。我国的医疗设备信息化管理起步较晚,尚处于初级研究阶段,从而导致现阶段医疗设备信息化管理问题较多。本文简短叙述了医疗设备信息化管理现状,以及当前医疗设备信息化管理所存在的问题,并对所描述问题提出针对性的解决方案。     

再论医院整体医疗管理的理论基础与组织运作

整体医疗管理是在整体论和医学整体观启发下产生的医院医疗管理新理论。医院整体医疗管理弥补了传统医院医疗管理模式的不足,对促进医院服务由医疗救治模式向院前、院内、院后全程化,预防、医疗、保健、康复一体化的健康服务模式转化具有重要意义。文章论述了实行医院整体医疗管理的必要性,讨论了其思想基础、变革目标以及基本运作模式。     

Fatal collision? Are wireless headsets a risk in treating patients?

Wireless-enabled headsets that connect to the internet can provide remote transcribing of patient examination notes. Audio and video can be captured and transmitted by wireless signals sent from the computer screen in the frame of the glasses. But using wireless glass-type devices can expose the user to a specific absorption rates (SAR) of 1.11–1.46 W/kg of radiofrequency radiation. That RF intensity is as high as or higher than RF emissions of some cell phones. Prolonged use of cell phones used ipsilaterally at the head has been associated with statistically significant increased risk of glioma and acoustic neuroma. Using wireless glasses for extended periods to teach, to perform surgery, or conduct patient exams will expose the medical professional to similar RF exposures which may impair brain performance, cognition and judgment, concentration and attention and increase the risk for brain tumors. The quality of medical care may be compromised by extended use of wireless-embedded devices in health care settings. Both medical professionals and their patients should know the risks of such devices and have a choice about allowing their use during patient exams. Transmission of sensitive patient data over wireless networks may increase the risk of hacking and security breaches leading to losses of private patient medical and financial data that are strictly protected under HIPPA health information privacy laws.     

Conceptual Privacy Framework for Health Information on Wearable Device

Wearable health tech provides doctors with the ability to remotely supervise their patients'' wellness. It also makes it much easier to authorize someone else to take appropriate actions to ensure the person''s wellness than ever before. Information Technology may soon change the way medicine is practiced, improving the performance, while reducing the price of healthcare. We analyzed the secrecy demands of wearable devices, including Smartphone, smart watch and their computing techniques, that can soon change the way healthcare is provided. However, before this is adopted in practice, all devices must be equipped with sufficient privacy capabilities related to healthcare service. In this paper, we formulated a new improved conceptual framework for wearable healthcare systems. This framework consists of ten principles and nine checklists, capable of providing complete privacy protection package to wearable device owners. We constructed this framework based on the analysis of existing mobile technology, the results of which are combined with the existing security standards. The approach also incorporates the market share percentage level of every app and its respective OS. This framework is evaluated based on the stringent CIA and HIPAA principles for information security. This evaluation is followed by testing the capability to revoke rights of subjects to access objects and ability to determine the set of available permissions for a particular subject for all models Finally, as the last step, we examine the complexity of the required initial setup.     

Data assimilation and multisource decision-making in systems biology based on unobtrusive Internet-of-Things devices

Biological and medical diagnoses depend on high-quality measurements. A wearable device based on Internet of Things (IoT) must be unobtrusive to the human body to encourage users to accept continuous monitoring. However, unobtrusive IoT devices are usually of low quality and unreliable because of the limitation of technology progress that has slowed down at high peak. Therefore, advanced inference techniques must be developed to address the limitations of IoT devices. This review proposes that IoT technology in biological and medical applications should be based on a new data assimilation process that fuses multiple data scales from several sources to provide diagnoses. Moreover, the required technologies are ready to support the desired disease diagnosis levels, such as hypothesis test, multiple evidence fusion, machine learning, data assimilation, and systems biology. Furthermore, cross-disciplinary integration has emerged with advancements in IoT. For example, the multiscale modeling of systems biology from proteins and cells to organs integrates current developments in biology, medicine, mathematics, engineering, artificial intelligence, and semiconductor technologies. Based on the monitoring objectives of IoT devices, researchers have gradually developed ambulant, wearable, noninvasive, unobtrusive, low-cost, and pervasive monitoring devices with data assimilation methods that can overcome the limitations of devices in terms of quality measurement. In the future, the novel features of data assimilation in systems biology and ubiquitous sensory development can describe patients’ physical conditions based on few but long-term measurements.     

Ensemble clustering for step data via binning

This paper considers the clustering problem of physical step count data recorded on wearable devices. Clustering step data give an insight into an individual's activity status and further provide the groundwork for health‐related policies. However, classical methods, such as K‐means clustering and hierarchical clustering, are not suitable for step count data that are typically high‐dimensional and zero‐inflated. This paper presents a new clustering method for step data based on a novel combination of ensemble clustering and binning. We first construct multiple sets of binned data by changing the size and starting position of the bin, and then merge the clustering results from the binned data using a voting method. The advantage of binning, as a critical component, is that it substantially reduces the dimension of the original data while preserving the essential characteristics of the data. As a result, combining clustering results from multiple binned data can provide an improved clustering result that reflects both local and global structures of the data. Simulation studies and real data analysis were carried out to evaluate the empirical performance of the proposed method and demonstrate its general utility.     

Security and privacy qualities of medical devices: an analysis of FDA postmarket surveillance

Background

Medical devices increasingly depend on computing functions such as wireless communication and Internet connectivity for software-based control of therapies and network-based transmission of patients’ stored medical information. These computing capabilities introduce security and privacy risks, yet little is known about the prevalence of such risks within the clinical setting.

Methods

We used three comprehensive, publicly available databases maintained by the Food and Drug Administration (FDA) to evaluate recalls and adverse events related to security and privacy risks of medical devices.

Results

Review of weekly enforcement reports identified 1,845 recalls; 605 (32.8%) of these included computers, 35 (1.9%) stored patient data, and 31 (1.7%) were capable of wireless communication. Searches of databases specific to recalls and adverse events identified only one event with a specific connection to security or privacy. Software-related recalls were relatively common, and most (81.8%) mentioned the possibility of upgrades, though only half of these provided specific instructions for the update mechanism.

Conclusions

Our review of recalls and adverse events from federal government databases reveals sharp inconsistencies with databases at individual providers with respect to security and privacy risks. Recalls related to software may increase security risks because of unprotected update and correction mechanisms. To detect signals of security and privacy problems that adversely affect public health, federal postmarket surveillance strategies should rethink how to effectively and efficiently collect data on security and privacy problems in devices that increasingly depend on computing systems susceptible to malware.     

我国现行医疗卫生政策的相关问题分析

医疗卫生是构建和谐社会的重要因素之一,也是关乎百姓切身利益的重大问题之一,近年来,医疗体制的不断改革,医疗卫生的相关政策的不断出台,已经大大地改善了我国广大人民群众的“看病难,看病贵”等问题,增加了医保的覆盖人群,减轻了城市低收入人群及农村的医疗负担,但是,我们仍面临着巨大的挑战,新的问题也不断涌现,医疗卫生政策不适应现在的医疗需求发展、经济发展不均衡、不同层次群众的医疗需求有差异等,都是医疗卫生改革中面临的问题,医疗改革的不断推进势在必行。我国的医疗保障制度覆盖率已经达到95％,但是,现行的医疗保障制度的还不能从根本上解决人民群众的“就医难,治病贵”的问题,其他医疗保险不能与现行的医疗保障制度相适应,从而,影响了我国整体的医疗水平的提高。     

我国省级层面分级诊疗文件比较分析

通过访问各省（区、市）卫生计生委的官方网站,获取有关分级诊疗政策的文件,在获取国家卫计委和万方、知网的相关分级诊疗文献的基础上,对各省（区、市）2016年2月28日以前的分级诊疗文件进行分析研究,通过对比各省分级诊疗文件的基本情况和实施措施等具体内容,分析不同省份在分级诊疗文件内容设定中存在的问题,从而为未来的分级诊疗决策和实践提供经验。     

手术医疗收费结构比例分析及对策探讨

目的 通过分析手术医疗收费结构比例,找出医疗收费结构中的缺陷。方法 对639例手术医疗收费情况进行数据处理,分析不同类别手术费用间价格的差异性。结果 在手术及麻醉医疗消费中,药品、耗材的费用在医疗消费中所占比例较大,医务人员的劳动价值在费用中未合理体现。结论 医疗费用的合理管控需要采取科学有效的措施作为保障,医务人员劳动价值需要公平合理的体现在医疗费用中。     

Gyroscopic corrections improve wearable sensor data prior to measuring dynamic sway in the gait of people with Multiple Sclerosis

Accelerometers are incorporated into many consumer devices providing new ways to monitor gait, mobility, and fall risk. However, many health benefits have not been realised because of issues with data quality that results from gravitational ‘cross-talk’ when the wearable device is tilted. Here we present an adaptive filter designed to improve the quality of accelerometer data prior to measuring dynamic pelvic sway patterns during a six minute walk test in people with and without Multiple Sclerosis (MS). Optical motion capture was used as the gold standard. Improved wearable device accuracy (≤4.4% NRMSE) was achieved using gyroscopic corrections and scaling filter thresholds by step frequency. The people with MS presented significantly greater pelvis sway range to compensate for their lower limb weaknesses and joint contractures. The visualisation of asymmetric pelvic sway in people with MS illustrates the potential to better understand their mobility impairments for reducing fall risk.     

Defaming Rover: Error-Based Latent Rhetoric in the Medical Literature on Dog Bites

This article examines the accuracy and rhetoric of reports by human health care professionals concerning dog bite injuries published in the peer-reviewed medical literature, with respect to nonclinical issues, such as dog behavior. A qualitative content analysis examined 156 publications between 1966 and 2015 identified by terms such as “dog bite” or “dangerous dogs.” The analysis revealed misinformation about human–canine interactions, the significance of breed and breed characteristics, and the frequency of dog bite–related injuries. Misinformation included clear-cut factual errors, misinterpretations, omissions, emotionally loaded language, and exaggerations based on misunderstood or inaccurate statistics or reliance on the interpretation by third parties of other authors’ meaning. These errors clustered within one or more rhetorical devices including generalization, catastrophization, demonization, and negative differentiation. By constructing the issue as a social problem, these distortions and errors, and the rhetorical devices supporting them, mischaracterize dogs and overstate the actual risk of dog bites.