Brief communication: Louisiana Clinical Data Research Network: establishing an infrastructure for efficient conduct of clinical research

The state of Louisiana, like the nation as a whole, is facing the salient challenge of improving population health and efficiency of healthcare delivery. Research to inform innovations in healthcare will best enhance this effort if it is timely, efficient, and patient-centered. The Louisiana Clinical Data Research Network (LACDRN) will increase the capacity to conduct robust comparative effectiveness research by building a health information technology infrastructure that provides access to comprehensive clinical data for more than 1 million patients statewide. To ensure that network-based research best serves its end-users, the project will actively engage patients and providers as key informants and decision-makers in the implementation of LACDRN. The network''s patient-centered research agenda will prioritize patients’ and clinicians’ needs and aim to support evidence-based decisions on the healthcare they receive and provide, to optimize patient outcomes and quality of life.     

Brief communication: CAPriCORN: Chicago Area Patient-Centered Outcomes Research Network

The Chicago Area Patient-Centered Outcomes Research Network (CAPriCORN) represents an unprecedented collaboration across diverse healthcare institutions including private, county, and state hospitals and health systems, a consortium of Federally Qualified Health Centers, and two Department of Veterans Affairs hospitals. CAPriCORN builds on the strengths of our institutions to develop a cross-cutting infrastructure for sustainable and patient-centered comparative effectiveness research in Chicago. Unique aspects include collaboration with the University HealthSystem Consortium to aggregate data across sites, a centralized communication center to integrate patient recruitment with the data infrastructure, and a centralized institutional review board to ensure a strong and efficient human subject protection program. With coordination by the Chicago Community Trust and the Illinois Medical District Commission, CAPriCORN will model how healthcare institutions can overcome barriers of data integration, marketplace competition, and care fragmentation to develop, test, and implement strategies to improve care for diverse populations and reduce health disparities.     

Brief communication: The Greater Plains Collaborative: a PCORnet Clinical Research Data Network

The Greater Plains Collaborative (GPC) is composed of 10 leading medical centers repurposing the research programs and informatics infrastructures developed through Clinical and Translational Science Award initiatives. Partners are the University of Kansas Medical Center, Children''s Mercy Hospital, University of Iowa Healthcare, the University of Wisconsin-Madison, the Medical College of Wisconsin and Marshfield Clinic, the University of Minnesota Academic Health Center, the University of Nebraska Medical Center, the University of Texas Health Sciences Center at San Antonio, and the University of Texas Southwestern Medical Center. The GPC network brings together a diverse population of 10 million people across 1300 miles covering seven states with a combined area of 679 159 square miles. Using input from community members, breast cancer was selected as a focus for cohort building activities. In addition to a high-prevalence disorder, we also selected a rare disease, amyotrophic lateral sclerosis.     

Brief communication: The ADVANCE network: accelerating data value across a national community health center network

The ADVANCE (Accelerating Data Value Across a National Community Health Center Network) clinical data research network (CDRN) is led by the OCHIN Community Health Information Network in partnership with Health Choice Network and Fenway Health. The ADVANCE CDRN will ‘horizontally’ integrate outpatient electronic health record data for over one million federally qualified health center patients, and ‘vertically’ integrate hospital, health plan, and community data for these patients, often under-represented in research studies. Patient investigators, community investigators, and academic investigators with diverse expertise will work together to meet project goals related to data integration, patient engagement and recruitment, and the development of streamlined regulatory policies. By enhancing the data and research infrastructure of participating organizations, the ADVANCE CDRN will serve as a ‘community laboratory’ for including disadvantaged and vulnerable patients in patient-centered outcomes research that is aligned with the priorities of patients, clinics, and communities in our network.     

Why common carrier and network neutrality principles apply to the Nationwide Health Information Network (NWHIN)

The Office of the National Coordinator will be defining the architecture of the Nationwide Health Information Network (NWHIN) together with the proposed HealtheWay public/private partnership as a development and funding strategy. There are a number of open questions—for example, what is the best way to realize the benefits of health information exchange? How valuable are regional health information organizations in comparison with a more direct approach? What is the role of the carriers in delivering this service? The NWHIN is to exist for the public good, and thus shares many traits of the common law notion of ‘common carriage’ or ‘public calling,’ the modern term for which is network neutrality. Recent policy debates in Congress and resulting potential regulation have implications for key stakeholders within healthcare that use or provide services, and for those who exchange information. To date, there has been little policy debate or discussion about the implications of a neutral NWHIN. This paper frames the discussion for future policy debate in healthcare by providing a brief education and summary of the modern version of common carriage, of the key stakeholder positions in healthcare, and of the potential implications of the network neutrality debate within healthcare.     

The OneFlorida Data Trust: a centralized,translational research data infrastructure of statewide scope

The OneFlorida Data Trust is a centralized research patient data repository created and managed by the OneFlorida Clinical Research Consortium (“OneFlorida”). It comprises structured electronic health record (EHR), administrative claims, tumor registry, death, and other data on 17.2 million individuals who received healthcare in Florida between January 2012 and the present. Ten healthcare systems in Miami, Orlando, Tampa, Jacksonville, Tallahassee, Gainesville, and rural areas of Florida contribute EHR data, covering the major metropolitan regions in Florida. Deduplication of patients is accomplished via privacy-preserving entity resolution (precision 0.97–0.99, recall 0.75), thereby linking patients’ EHR, claims, and death data. Another unique feature is the establishment of mother-baby relationships via Florida vital statistics data. Research usage has been significant, including major studies launched in the National Patient-Centered Clinical Research Network (“PCORnet”), where OneFlorida is 1 of 9 clinical research networks. The Data Trust’s robust, centralized, statewide data are a valuable and relatively unique research resource.     

用例驱动的临床检验信息互联互通相关标准规范研究

介绍我国区域临床检验信息互联互通相关标准规范研究所采用的用例驱动的方式,阐述检验信息互操作需求的用例撰写,以及用例在后续标准规范研究中的应用,包括信息标准、信息安全、系统架构等方面。     

美国网络健康信息服务的主体、业务与启示

通过对美国网络健尿信息服务开展情况的网络调研,对Alexa排名前50的健康信息网站的主体分布、业务配置进行分析,发现美国网络健康信息服务主体性质多样,并且业务开展广泛,对比我国网络信息服务的现状,其不同主体的业务配置根据用户的不同一般都有各自的特点,且有更多新型的服务业务出现的趋势.由此,为我国更好的开展网络健康信息服务提出要建立网络健康信息服务多元主体协作机制;提升网络健康信息资源的质量水平;扩展网络健康信息服务的业务范围三点要求.     

Brief communication: Changing the research landscape: the New York City Clinical Data Research Network

The New York City Clinical Data Research Network (NYC-CDRN), funded by the Patient-Centered Outcomes Research Institute (PCORI), brings together 22 organizations including seven independent health systems to enable patient-centered clinical research, support a national network, and facilitate learning healthcare systems. The NYC-CDRN includes a robust, collaborative governance and organizational infrastructure, which takes advantage of its participants’ experience, expertise, and history of collaboration. The technical design will employ an information model to document and manage the collection and transformation of clinical data, local institutional staging areas to transform and validate data, a centralized data processing facility to aggregate and share data, and use of common standards and tools. We strive to ensure that our project is patient-centered; nurtures collaboration among all stakeholders; develops scalable solutions facilitating growth and connections; chooses simple, elegant solutions wherever possible; and explores ways to streamline the administrative and regulatory approval process across sites.     

医疗大数据研究现状及其临床应用

介绍医疗大数据的内涵及其对医学研究的影响，指出医疗领域大数据研究的必要性，总结现阶段医疗大数据的研究现状，提出医疗大数据研究中的若干问题。分析医疗大数据如何应用于临床医学，包括临床诊断和临床药效分析等方面。     

临床药物试验数据交换平台中集成方法应用研究

通过对数据集成方法的比较分析,针对临床药物试验系统,结合中国医学科学院阜外心血管病医院实践,提出一种可扩展、集成效率高、成本低廉的数据集成方法。介绍系统的集成结构和工作原理,并指出其在临床药物试验中的重要作用和价值。     

区域卫生信息交换数据集的构建方法研究

为实现区域医疗卫生信息的共享,向社会和本区域公众提供优质高效的医疗卫生信息服务,构建区域卫生信息交换标准成为基础且又重要的任务。讨论如何在区域卫生信息交换的环境下构建区域卫生信息交换数据集。对构建交换数据集的交换功能进行需求分析,重点讨论业务建模与信息建模及数据的规范化管理,并提出在信息交换构建过程中所涉及到的关键问题处理。     

军队干休所卫生信息管理与网络医疗服务系统研究与应用

建立干休所卫生信息管理与网络医疗服务系统,满足老干部“两高期”情况下出现的医疗保健新需求,提高医疗服务质量、效率,为卫生机关科学决策提供依据。     

中医临床护理信息数据元标准构建研究

简述数据元的概念及其模型,阐述开展中医临床护理信息数据元标准研究的重要性,以中医护理记录单中的特色操作为例,探讨如何构建中医临床护理信息数据元,提出护理记录信息数据元目录及相应的值域代码表,为构建中医临床护理信息数据元标准提供示范案例。     

国外临床数据挖掘研究热点的文献计量学分析

为了解近年国外临床数据挖掘领域的研究热点,以Web of Science收录的文献为研究对象,采用文献计量学方法对“最新高被引文献-施引文献”引文网络进行聚类和分析,总结出国外临床数据挖掘的研究热点,以期对我国相关领域研究有所借鉴。     

Brief communication: Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS): Architecture

We describe the architecture of the Patient Centered Outcomes Research Institute (PCORI) funded Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS, http://www.SCILHS.org) clinical data research network, which leverages the $48 billion dollar federal investment in health information technology (IT) to enable a queryable semantic data model across 10 health systems covering more than 8 million patients, plugging universally into the point of care, generating evidence and discovery, and thereby enabling clinician and patient participation in research during the patient encounter. Central to the success of SCILHS is development of innovative ‘apps’ to improve PCOR research methods and capacitate point of care functions such as consent, enrollment, randomization, and outreach for patient-reported outcomes. SCILHS adapts and extends an existing national research network formed on an advanced IT infrastructure built with open source, free, modular components.     

也论知情同意理论

通过描述知情同意理论的本质、要素和在新形势下的内涵,探讨了在公共卫生实践活动中怎样有效地贯彻实施知情同意原则,并比较了在公共卫生伦理学、临床伦理学、生物医学研究伦理学的不同情境下,知情同意的异同。     

Data governance requirements for distributed clinical research networks: triangulating perspectives of diverse stakeholders

There is currently limited information on best practices for the development of governance requirements for distributed research networks (DRNs), an emerging model that promotes clinical data reuse and improves timeliness of comparative effectiveness research. Much of the existing information is based on a single type of stakeholder such as researchers or administrators. This paper reports on a triangulated approach to developing DRN data governance requirements based on a combination of policy analysis with experts, interviews with institutional leaders, and patient focus groups. This approach is illustrated with an example from the Scalable National Network for Effectiveness Research, which resulted in 91 requirements. These requirements were analyzed against the Fair Information Practice Principles (FIPPs) and Health Insurance Portability and Accountability Act (HIPAA) protected versus non-protected health information. The requirements addressed all FIPPs, showing how a DRN''s technical infrastructure is able to fulfill HIPAA regulations, protect privacy, and provide a trustworthy platform for research.     

Professional and geographical network effects on healthcare information exchange growth: does proximity really matter?

Background and objective

We postulate that professional proximity due to common patients and geographical proximity among practice locations are significant factors influencing the adoption of health information exchange (HIE) services by healthcare providers. The objective of this study is to investigate the direct and indirect network effects of these drivers on HIE diffusion.

Design

Multi-dimensional scaling and clustering are first used to create different clusters of physicians based on their professional and geographical proximities. Extending the Bass diffusion model to capture direct and indirect network effects among groups, the growth of HIE among these clusters is modeled and studied. The network effects among the clusters are investigated using adoption data over a 3-year period for an HIE based in Western New York.

Measurement

HIE adoption parameters—external sources of influence as well as direct and indirect network coefficients—are estimated by the extended version of the Bass diffusion model.

Results

Direct network effects caused by common patients among physicians are much more influential on HIE adoption as compared with previously investigated social contagion and external factors. Professional proximity due to common patients does influence adoption decisions; geographical proximity is also influential, but its effect is more on rural than urban physicians.

Conclusions

Flow of patients among different groups of physicians is a powerful factor in HIE adoption. Rather than merely following the market trend, physicians appear to be influenced by other physicians with whom they interact with and have common patients.     

Clinical research data warehouse governance for distributed research networks in the USA: a systematic review of the literature

Objective

To review the published, peer-reviewed literature on clinical research data warehouse governance in distributed research networks (DRNs).

Materials and methods

Medline, PubMed, EMBASE, CINAHL, and INSPEC were searched for relevant documents published through July 31, 2013 using a systematic approach. Only documents relating to DRNs in the USA were included. Documents were analyzed using a classification framework consisting of 10 facets to identify themes.

Results

6641 documents were retrieved. After screening for duplicates and relevance, 38 were included in the final review. A peer-reviewed literature on data warehouse governance is emerging, but is still sparse. Peer-reviewed publications on UK research network governance were more prevalent, although not reviewed for this analysis. All 10 classification facets were used, with some documents falling into two or more classifications. No document addressed costs associated with governance.

Discussion

Even though DRNs are emerging as vehicles for research and public health surveillance, understanding of DRN data governance policies and procedures is limited. This is expected to change as more DRN projects disseminate their governance approaches as publicly available toolkits and peer-reviewed publications.

Conclusions

While peer-reviewed, US-based DRN data warehouse governance publications have increased, DRN developers and administrators are encouraged to publish information about these programs.