Digital Pathology and Virtual Microscopy Integration in E-Health Records

In anatomic pathology, digital pathology integrates information management systems to manage both digital images and text-based information. Digital pathology allows information sharing for diagnosis, biomedical research and education. Virtual microscopy resulting in digital slides is an outreaching technology in anatomic pathology. Limiting factors in the expansion of virtual microscopy are formidable storage dimension, scanning speed, quality of image and cultural change. Anatomic pathology data and images should be an important part of the patient electronic health records as well as of clinical datawarehouses, epidemiological or biomedical research databases, and platforms dedicated to translational medicine. Integrating anatomic pathology to the “healthcare enterprise” can only be achieved using existing and emerging medical informatics standards like Digital Imaging and Communications in Medicine (DICOM®1), Health Level Seven (HL7®), and Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT®), following the recommendations of Integrating the Healthcare Enterprise (IHE®).

Dynamic Business Processes and Virtual Communities in Wireless eHealth Environments

Computer Supported Collaborative Work (CSCW) related applications tend to be a trend for most successful businesses, organizations and domains nowadays, as is the Healthcare sector. Healthcare specialists often work in remote areas facing many problems and challenges driven mainly from the limitations and constraints of the mobile and wireless technologies in relation to the tasks at hand. Due to the sensitive area of healthcare provision, this chapter discusses that additional features need to be incorporated in current CSCW systems, like the dynamic creation of medical virtual teams, dynamic workflows and the automatic triggered events upon time expiration, in order to be more effective and efficient. In this respect and having in mind the new Web 2.0 characteristics, a set of new features applied in our proposed CSCW system, DITIS, is analyzed in an attempt to encapsulate all the needs of eHealth applications. Furthermore, an extensive evaluation of the system is presented, supporting the need for such enhancements since a significant increase in communication, coordination and collaboration has been shown among the subjects.

Academic Family Health Teams Collaborative Lessons from the Far Flung North

Working collaboratively, in widely distributed settings, poses unique challenges. The Academic Family Health Team, affiliated with the Northern Ontario School of Medicine, has had to adopt a wide variety of information sharing practices and collaborative software tools, in order to function effectively in such roles as clinicians, educators and researchers. Based on an ongoing action research model, this chapter describes approaches taken and lessons learned while developing the informatics infrastructure to support interprofessional practice. The author describes how common procedures and software tools can benefit from a Web 2.0 approach, comparing commercial and open-source aspects of possible solutions. Ubiquitous data access for point of care decision making is supported by integrating web services, mobile devices and multi-stream communications. Resource discovery is enabled by integrating information streams into the medical record, into wireless device interfaces and via clinical dashboards. Effective team collaboration is highly enhanced through such infrastructure support.

A Semantic Model to Address Health Questions to Professionals in Healthcare Social Networks

Internet social networks offer a wide variety of possibilities, including communication between users, sharing information, and the creation of virtual communities on many different subjects. One of these subjects is healthcare, where different social networks are now appearing and covering different objectives. In this chapter, a social network is described, where users can formulate healthcare questions that are automatically classified under concepts of a medical ontology and assigned to experts of each topic. These questions are then answered by healthcare expert physicians. This chapter includes a semantic classifying method that provides the automatic classification of questions by means of a medical ontology, based on the tags used to annotate them, and the previously classified questions. The chapter includes an ontological model that represents the questions, the assigned tags, the answers, the physicians, and the medical concepts.

Personal Health Records Status-Quo and Future Perspectives

Consumers, industry, and government have recently focused attention on the potential of personal health records to empower patients in the health care process, improve patient-provider relationships, facilitate patient access to health information, and improve the quality of health care. A Personal Health Record (PHR) is a private and secure digital record that is created, managed, and owned by an individual, and contains the owner’s relevant health information. The benefits of PHRs have not yet been widely realized due to several significant challenges in their adoption, including the need for privacy, security, and interoperability, and the lack of accepted standards. Although many players in the healthcare arena are beginning to offer partial solutions, none have adequately addressed the full range of challenges. The adoption of PHRs can be significantly accelerated by the development of Open Source software that enables an individual to collect, create, organize, and manage his or her own private and secure PHR, using a standardized format and controlled vocabulary.

Semantic Interoperability Issue of Standardizing Medical Vocabularies

Semantic interoperability is the key to achieving global interoperability in healthcare information technology. The benefits are tremendous – the sharing of clinical data for multiple uses including patient care, research, reimbursement, audit and analyses, education, health surveillance, and many other uses. Patient safety, higher quality healthcare, more effective and efficient healthcare, increased outcomes, and potentially improved performance, higher quality of life and longer lifetimes are potential results. Decision support and the immediate linking of knowledge to the care process become easier. Semantic interoperability is a worthy goal. There are many barriers to achieving semantic interoperability. Key among these is the resolution of the many issues relating to the terminologies used in defining, describing and documenting health care. Each of these controlled terminologies has a reason for being and a following. The terminologies conflict and overlap; the granularity is not sufficiently rich for direct clinical use; there are gaps that prevent an exhaustive set; there are major variances in cost and accessibility; and no one appears eager or willing to make the ultimate decisions required to solve the problem. This chapter defines and describes the purpose and characteristics of the major terminologies in use in healthcare today. Terminology sets are compared in purpose, form and content. Finally, a proposed solution is presented based on a global master metadictionary of data elements with a rich set of attributes including names that may come from existing controlled terminologies, precise definitions to remove ambiguity in use, and complete value sets of possible values. The focus is on data elements because data elements are the basic unit of data interchange.

Feature Evaluation and Classification for Content-Based Medical Image Retrieval System

Image retrieval in general and content-based image retrieval (CBIR) in particular are well-known research fields in information management. A large number of methods have been proposed and investigated in both areas but satisfactory general solution has not still been developed. The aim of this research is to develop highly flexible web-based system for storage, organization and retrieval of medical images. The system besides text and metadata retrieval also supports querying by image to find visually similar images to presented query. Several algorithms and techniques were implemented in the system to support content-based retrieval. For efficient and reliable search machine learning techniques were included in the system.

Electronic Environments for Integrated Care Management Case of Depression Treatment

This chapter provides a basic overview of care process management and active patient engagement principles. It builds upon these principles to describe in more detail the way information and communication technology can provide support for them. It later discusses their impact on quality and cost-efficiency of care. The authors specify care models suitable for ICT support, specific process support characteristics related to health care, standards and communication devices that are being used. The chapter also provides a description of development and implementation of such an environment to support treatment of patients with depression.

Managing E-Health in the Age of Web 2.0 The Impact on E-Health Evaluation

The use of Web 2.0 internet tools for healthcare is noted for its great potential to address a wide range of healthcare issues or improve overall delivery. However, there have been various criticisms of Web 2.0, including in its application to healthcare where it has been described as more marketing and hype than a real departure from previous medical internet or eHealth trends. Authors have noted that there is scant evidence demonstrating it as a cost efficient mechanism to improve outcomes for patients. Moreover, the investments in Web 2.0 for health, or the wider concept of eHealth, are becoming increasingly significant. Hence given the uncertainty surrounding its value, this chapter aims to critically examine the issues associated with emerging use of Web 2.0 for health. The authors look at how it not only distinguishes itself from previous eHealth trends but also how it enhances them, examining the impact on eHealth investment and management from a policy perspective, and how research can aid this management.

Semantic Web Architecture to Provide E-Health Content and Services

This chapter is aimed at introducing the Semantic Web, the related common languages, and the Semantic Web Services Architecture as a hope for future information services architecture on the Web. In particular, the chapter will focus on the current and prospective (or practical and potential) contributions of the Semantic Web technologies in providing e-Health content and services to its potential users worldwide. To stay health-focused and to illustrate the potentials of the health related services, a real-life journey of a health consumer seeking health information services has been used as the context throughout this chapter. This consumer’s journey will help the readers to comprehend the superior aspects of the Semantic Web technologies as an emerging upgrade to the current physical architecture.