Sociotechnical Challenges and Progress in Using Social Media for Health

Social media tools that connect patients, caregivers, and health providers offer great potential for helping people access health advice, receive and give social support, manage or cope with chronic conditions, and make day-to-day health decisions. These systems have seen widespread adoption, but often fail to support the goals as fully as designers and users would like. Through Ackerman’s lens of the “sociotechnical gap” and computer supported cooperative work (CSCW) as a science of the artificial, we review contemporary sociotechnical challenges and progress for using social media to support health. These challenges include a tension between privacy and sharing, policy information credibility, accessibility, and tailoring in social spaces. Those studying, building, deploying, and using social media systems to further health goals will benefit from approaching this work by borrowing from Ackerman’s framing of CSCW. In particular, this requires acknowledgment that technical systems will not fully meet our social goals, and then adopting design and educational approaches that are appropriate to fill this gap, building less-nuanced systems as partial solutions and tools for advancing our understanding, and by working with the CSCW research community to develop and pursue key lines of inquiry.     

Giving patients granular control of personal health information: Using an ethics ‘Points to Consider’ to inform informatics system designers

ObjectiveThere are benefits and risks of giving patients more granular control of their personal health information in electronic health record (EHR) systems. When designing EHR systems and policies, informaticists and system developers must balance these benefits and risks. Ethical considerations should be an explicit part of this balancing. Our objective was to develop a structured ethics framework to accomplish this.MethodsWe reviewed existing literature on the ethical and policy issues, developed an ethics framework called a “Points to Consider” (P2C) document, and convened a national expert panel to review and critique the P2C.ResultsWe developed the P2C to aid informaticists designing an advanced query tool for an electronic health record (EHR) system in Indianapolis. The P2C consists of six questions (“Points”) that frame important ethical issues, apply accepted principles of bioethics and Fair Information Practices, comment on how questions might be answered, and address implications for patient care.DiscussionThe P2C is intended to clarify what is at stake when designers try to accommodate potentially competing ethical commitments and logistical realities. The P2C was developed to guide informaticists who were designing a query tool in an existing EHR that would permit patient granular control. While consideration of ethical issues is coming to the forefront of medical informatics design and development practices, more reflection is needed to facilitate optimal collaboration between designers and ethicists. This report contributes to that discussion.     

Emergent CSCW systems: the resolution and bandwidth of workplaces

In any collaborative work settings, people naturally develop physical tools and associated work processes that support the management of the interdependencies in information, materials, and social needs. Field studies of management of operating rooms pointed out that collaborative work is supported by an infrastructure that is composed of mostly non-computerized, physical components. The supporting infrastructure is jointly maintained and exploited, with constantly evolving patterns of usage, in response to complexity of coordination needs and the uncertain environment. To represent status and plans, users seem to invent structures based both on idiosyncratic preferences and on negotiated symbols. The fluidity and ease of restructuring workplaces to support collaborative work may be explained in part by the high resolution and bandwidth of workplaces: a large number of ways in which workers could structure their work and a high capacity to convey rich information and meanings quickly to collaborators. We argue that to support health care workers, designers of computer supported cooperative work (CSCW) systems should learn how the physical and perceptual properties of workplaces are exploited, and that CSCW systems should be designed to allow maximum freedom of restructuring and reconfiguring as part of workplaces to enhance bandwidth and resolution of representation and communication.     

Color-engineered rats and luminescent LacZ imaging: a new platform to visualize biological processes

The rat represents an excellent mammalian model for broadening medical knowledge, and a wealth of information on its physiology has been obtained from its use as an experimental organism. Furthermore, its ample body size allows various surgical manipulations that cannot be performed on a mouse. Many rat models mimic human diseases and have therefore been used in a variety of biomedical studies, including physiology, pharmacology, and transplantation. In an effort to create specifically designed rats for new biomedical research and the field of regenerative medicine, we develop an engineered rat system on the basis of transgenic technology and succeed in establishing unique rats that possess genetically encoded color probes: green fluorescent protein (GFP), DsRed2 (red liver), Cre/LoxP (red to green), and LacZ (blue and luminescence). In this work, we highlight their characteristics and describe recent applications for tissue engineering and regeneration. Coupled with recent progress in modern imaging systems, these transgenic rats are providing powerful tools for the elucidation of many cellular processes in biomedical science, and may lead to innovative medical treatments.     

Incorporating collaboratory concepts into informatics in support of translational interdisciplinary biomedical research

Due to its complex nature, modern biomedical research has become increasingly interdisciplinary and collaborative in nature. Although a necessity, interdisciplinary biomedical collaboration is difficult. There is, however, a growing body of literature on the study and fostering of collaboration in fields such as computer supported cooperative work (CSCW) and information science (IS). These studies of collaboration provide insight into how to potentially alleviate the difficulties of interdisciplinary collaborative research. We, therefore, undertook a cross cutting study of science and engineering collaboratories to identify emergent themes. We review many relevant collaboratory concepts: (a) general collaboratory concepts across many domains: communication, common workspace and coordination, and data sharing and management, (b) specific collaboratory concepts of particular biomedical relevance: data integration and analysis, security structure, metadata and data provenance, and interoperability and data standards, (c) environmental factors that support collaboratories: administrative and management structure, technical support, and available funding as critical environmental factors, and (d) future considerations for biomedical collaboration: appropriate training and long-term planning. In our opinion, the collaboratory concepts we discuss can guide planning and design of future collaborative infrastructure by biomedical informatics researchers to alleviate some of the difficulties of interdisciplinary biomedical collaboration.     

Query expansion with a medical ontology to improve a multimodal information retrieval system

Searching biomedical information in a large collection of medical data is a complex task. The use of tools and biomedical resources could ease the retrieval of the information desired. In this paper, we use the medical ontology MeSH to improve a Multimodal Information Retrieval System by expanding the user's query with medical terms. In order to accomplish our experiments, we have used the dataset provided by ImageCLEFmed task organizers for years 2005 and 2006. This dataset is composed of a multimodal collection (images and text) of clinical cases, a list of queries for each year, and a list of relevance judgments for each query to evaluate the results. The results from the experiments show that the use of a medical ontology to expand the queries greatly improves the results.     

The ImageCLEFmed Medical Image Retrieval Task Test Collection

A growing number of clinicians, educators, researchers, and others use digital images in their work and search for them via image retrieval systems. Yet, this area of information retrieval is much less understood and developed than searching for text-based content, such as biomedical literature and its derivations. The goal of the ImageCLEF medical image retrieval task (ImageCLEFmed) is to improve understanding and system capability in search for medical images. In this paper, we describe the development and use of a medical image test collection designed to facilitate research with image retrieval systems and their users. We also provide baseline results with the new collection and describe them in the context of past research with portions of the collection.     

Asynchronous communication among clinical researchers: a study for systems design

Group work is an essential part of modern health care. Although there have been advances in the technology of communication, these have not necessarily led to efficient and effective communication among collaborating health-care professionals. Instead, barriers such as varied organizational cultures, different training backgrounds, and varied time schedules can overwhelm technological solutions and impede efficient communication. We focus on one particular sort of collaboration, that of group work around a clinical trial protocol, where the collaboration is asynchronous and the participants are geographically distributed. In this work setting, we have applied a computer-supported cooperative work (CSCW) approach in two distinct ways. First, we used observational methods to uncover and understand a complex set of communication behaviors and needs. Second, we used participatory design and iterative prototyping to design a system that aims to improve communication and work flow among these collaborators. We found that these methods work well in tandem-our observational study helped better inform our design, and our prototyping cycles provided additional insight into the work. More specifically, we were able to identify a set of communication problems in the work that led us to specify a set of design desiderata for systems that support asynchronous collaboration around an evolving medical document.     

听觉引导助盲系统

盲人由于视觉缺失造成了生活上的诸多不便,因此人们一直在努力研究辅助装置来提高盲人生活质量。基于感觉替代的原理,设计听觉引导助盲系统为视觉障碍人士提供帮助,成为现今生物医学工程领域的研究热点。本文介绍了听觉代替视觉的基本原理和系统构架,综述了国内外听觉引导助盲系统的发展历史和研究进展。虽然系统的开发还存在很多技术难点,但相信在不久的将来听觉引导助盲系统的发展将会为盲人的生活带来福音。     

The contextual nature of medical information

Successful design of information systems in health care starts with a thorough understanding of the practices in which the systems are to function. In this paper, we discuss the nature of 'medical information' from a sociological perspective. We focus on the (im)possibilities of the utilization of primary health care data for secondary purposes such as research and administration. In much of the literature on EPRs, this secondary utilization is only seen to depend on the question whether the IT connections are in place. It is then simply a matter of selecting which information to transport and to where. In this article, we argue that this view of medical information is mistaken. Information should be conceptualized as always entangled with the context of its production. The disentangling of information from its production context is possible, but that entails work. We propose the following 'law of medical information': the further information has to be able to circulate (i.e. the more diverse contexts it has to be usable in), the more work is required to disentangle the information from the context of its production. The question that then becomes pertinent is; who has to do this work, and who reaps the benefits?     

Functional and dysfunctional characteristics of the prevailing model of clinical evaluation systems in North American medical schools.

To ensure that graduates are ready to move on to residency, medical schools need systems to monitor students' progress through clinical experiences. Clinical rotations occur in geographically separated settings in a variety of disciplines that use evaluators of varying levels of experience. That this complexity lends itself to error has been documented by the Association of American Medical Colleges' ongoing Clinical Evaluation Project, begun in 1979. This paper draws from that work and a 1987-1988 survey of 77% of the U.S. and Canadian deans for student affairs. This information is subjected to an analysis that emphasizes both common and unique characteristics of evaluation systems that are based on the four-stage model employed by most medical schools. Seventeen symptoms that can be signs of system errors are identified. It is recommended that schools having these symptoms review their clinical evaluation systems to ensure effective and efficient monitoring of clinical students.     

Applications of MEMS technologies in tissue engineering

The success of therapeutic strategies within the fields of regenerative medicine, including tissue engineering, biomaterials engineering, and cell and tissue transplantation science, relies on researchers' understanding of the complex cellular microenvironments that occur within functional tissue. Microfabricated biomedical platforms provide tools for researchers to study cellular response to various stimuli with micro- and nanoscale spatial control. Initial studies utilizing relatively passive means of microenvironmental control have provided the fundamental knowledge required to begin to design microculture platforms that closely mimic these biological systems. In this review, we discuss second-generation cell and tissue culture platforms that utilize active components, borrowed from work in the development of microelectromechanical systems (MEMS). These microsystems offer the unprecedented opportunity to fabricate culture platforms designed to match tissue-specific growth parameters. In addition, the adoption of MEMS components opens up the door for future integration with the burgeoning field of microanalytical systems, providing analytical platforms that retain the sensitivity and resolution required within low-volume, microfluidic culture technologies.     

Cooperation of the Russian Academy of Medical Sciences with the World Health Organization

The paper presents a brief review of successful cooperation of the Russian Academy of Medical Sciences (RAMS) with the World Health Organization (WHO) in developing biomedical research and promoting the scientific bases of public health. This cooperation is effected in different forms. The work of 30 WHO collaborating centers on the basis of 18 RAMS Research Institutions plays the leading part in this cooperation. The paper contains specific data on the activities of these centers in the field of medical research, scientific publications, education, and training of medical staff for Russia and other countries. The financial support given by the WHO to its collaborating centers is now very limited, but scientific information, medicaments, and equipment which can be received by the centers from this Organization are very valuable.     

Temporal reasoning with medical data--a review with emphasis on medical natural language processing

Temporal information is crucial in electronic medical records and biomedical information systems. Processing temporal information in medical narrative data is a very challenging area. It lies at the intersection of temporal representation and reasoning (TRR) in artificial intelligence and medical natural language processing (MLP). Some fundamental concepts and important issues in relation to TRR have previously been discussed, mainly in the context of processing structured data in biomedical informatics; however, it is important that these concepts be re-examined in the context of processing narrative data using MLP. Theoretical and methodological TRR studies in biomedical informatics can be classified into three main categories: category 1 applies theories and models from temporal reasoning in AI; category 2 defines frameworks that meet needs from clinical applications; category 3 resolves issues such as temporal granularity and uncertainty. Currently, most MLP systems are not designed with a formal representation of time, and their ability to reason about temporal relations among medical events is limited. Previous work in processing time with clinical narrative data includes processing time in clinical reports, modeling textual temporal expressions in clinical databases, processing time in clinical guidelines, and building time standards for data exchange and integration. In addition to common problems in MLP, there are challenges specific to TRR in medical text, which occur at each level of linguistic structure and analysis. Despite advances in temporal reasoning in biomedical informatics, processing time in medical text deserves more attention. Besides the need for more research in temporal granularity, fuzzy time, temporal contradiction, intermittent events and uncertainty, broad areas for future research include enhancing functions of current MLP systems on processing temporal information, incorporating medical knowledge into temporal reasoning systems, resolving coreference, integrating narrative data with structured data and evaluating these systems.     

Biomedical text mining and its applications in cancer research

Cancer is a malignant disease that has caused millions of human deaths. Its study has a long history of well over 100 years. There have been an enormous number of publications on cancer research. This integrated but unstructured biomedical text is of great value for cancer diagnostics, treatment, and prevention. The immense body and rapid growth of biomedical text on cancer has led to the appearance of a large number of text mining techniques aimed at extracting novel knowledge from scientific text. Biomedical text mining on cancer research is computationally automatic and high-throughput in nature. However, it is error-prone due to the complexity of natural language processing. In this review, we introduce the basic concepts underlying text mining and examine some frequently used algorithms, tools, and data sets, as well as assessing how much these algorithms have been utilized. We then discuss the current state-of-the-art text mining applications in cancer research and we also provide some resources for cancer text mining. With the development of systems biology, researchers tend to understand complex biomedical systems from a systems biology viewpoint. Thus, the full utilization of text mining to facilitate cancer systems biology research is fast becoming a major concern. To address this issue, we describe the general workflow of text mining in cancer systems biology and each phase of the workflow. We hope that this review can (i) provide a useful overview of the current work of this field; (ii) help researchers to choose text mining tools and datasets; and (iii) highlight how to apply text mining to assist cancer systems biology research.     

Computers in imaging and health care: Now and in the future

Early picture archiving and communication systems (PACS) were characterized by the use of very expensive hardware devices, cumbersome display stations, duplication of database content, lack of interfaces to other clinical information systems, and immaturity in their understanding of the folder manager concepts and workflow reengineering. They were implemented historically at large academic medical centers by biomedical engineers and imaging informaticists. PACS were nonstandard, home-grown projects with mixed clinical acceptance. However, they clearly showed the great potential for PACS and filmless medical imaging. Filmless radiology is a reality today. The advent of efficient softcopy display of images provides a means for dealing with the ever-increasing number of studies and number of images per study. Computer power has increased, and archival storage cost has decreased to the extent that the economics of PACS is justifiable with respect to film. Network bandwidths have increased to allow large studies of many megabytes to arrive at display stations within seconds of examination completion. PACS vendors have recognized the need for efficient workflow and have built systems with intelligence in the management of patient data. Close integration with the hospital information system (HIS)-radiology information system (RIS) is critical for system functionality. Successful implementation of PACS requires integration or interoperation with hospital and radiology information systems. Besides the economic advantages, secure rapid access to all clinical information on patients, including imaging studies, anytime and anywhere, enhances the quality of patient care, although it is difficult to quantify. Medical image management systems are maturing, providing access outside of the radiology department to images and clinical information throughout the hospital or the enterprise via the Internet. Small and medium-sized community hospitals, private practices, and outpatient centers in rural areas will begin realizing the benefits of PACS already realized by the large tertiary care academic medical centers and research institutions. Hand-held devices and the Worldwide Web are going to change the way people communicate and do business. The impact on health care will be huge, including radiology. Computer-aided diagnosis, decision support tools, virtual imaging, and guidance systems will transform our practice as value-added applications utilizing the technologies pushed by PACS development efforts. Outcomes data and the electronic medical record (EMR) will drive our interactions with referring physicians and we expect the radiologist to become the informaticist, a new version of the medical management consultant.     

Evaluating informatics applications--clinical decision support systems literature review.

This paper reviews clinical decision support systems (CDSS) literature, with a focus on evaluation. The literature indicates a general consensus that clinical decision support systems are thought to have the potential to improve care. Evidence is more equivocal for guidelines and for systems to aid physicians with diagnosis. There also is general consensus that a variety of systems are little used despite demonstrated or potential benefits. In the evaluation literature, the main emphasis is on how clinical performance changes. Most studies use an experimental or randomized controlled clinical trials design (RCT) to assess system performance or to focus on changes in clinical performance that could affect patient care. Few studies involve field tests of a CDSS and almost none use a naturalistic design in routine clinical settings with real patients. In addition, there is little theoretical discussion, although papers are permeated by a rationalist perspective that excludes contextual issues related to how and why systems are used. The studies mostly concern physicians rather than other clinicians. Further, CDSS evaluation studies appear to be insulated from evaluations of other informatics applications. Consequently, there is a lack of information useful for understanding why CDSSs may or may not be effective, resulting in making less informed decisions about these technologies and, by extension, other medical informatics applications.     

Can multilinguality improve Biomedical Word Sense Disambiguation?

Ambiguity in the biomedical domain represents a major issue when performing Natural Language Processing tasks over the huge amount of available information in the field. For this reason, Word Sense Disambiguation is critical for achieving accurate systems able to tackle complex tasks such as information extraction, summarization or document classification. In this work we explore whether multilinguality can help to solve the problem of ambiguity, and the conditions required for a system to improve the results obtained by monolingual approaches. Also, we analyze the best ways to generate those useful multilingual resources, and study different languages and sources of knowledge. The proposed system, based on co-occurrence graphs containing biomedical concepts and textual information, is evaluated on a test dataset frequently used in biomedicine. We can conclude that multilingual resources are able to provide a clear improvement of more than 7% compared to monolingual approaches, for graphs built from a small number of documents. Also, empirical results show that automatically translated resources are a useful source of information for this particular task.