Image standards in Tissue-Based Diagnosis (Diagnostic Surgical Pathology)

© 2008 Kayser et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Issues of the adoption of HIT related standards at the decision-making stage of six tertiary healthcare organisations in Saudi Arabia

Due to interoperability barriers between clinical information systems, healthcare organisations are facing potential limitations with regard to acquiring the benefits such systems offer; in particular, in terms of reducing the cost of medical services. However, to achieve the level of interoperability required to reduce these problems, a high degree of consensus is required regarding health data standards. Although such standards essentially constitute a solution to the interoperability barriers mentioned above, the level of adoption of these standards remains frustratingly low. One reason for this is that health data standards are an authoritative field in which marketplace mechanisms do not work owing to the fact that health data standards developed for a particular market cannot, in general, be applied in other markets without modification. Many countries have launched national initiatives to develop and promote national health data standards but, although certain authors have mapped the landscape of the standardisation process for health data in some countries, these studies have failed to explain why the healthcare organisations seem unwilling to adopt those standards. In addressing this gap in the literature, a conceptual model of the adoption process of HIT related standards at the decision-making stage in healthcare organisations is proposed in this research. This model was based on two predominant theories regarding IT related standards in the IS field: Rogers paradigm (1995) and the economics of standards theory. In addition, the twenty one constructs of this model resulted from a comprehensive set of factors derived from the related literature; these were then grouped in accordance with the Technology-Organisation Environment (TOE), a well-known taxonomy within innovation adoption studies in the IS field. Moving from a conceptual to an empirical position, an interpretive, exploratory, multiple-case study methodology was conducted in Saudi Arabia to examine the proposed model. The empirical qualitative evidence gained necessitated some revision to be made to the proposed model. One factor was abandoned, four were modified and eight new factors were added. This consistent empirical model makes a novel contribution at two levels. First, with regard to the body of knowledge in the IS area, this model offers an in-depth understanding of the adoption process of HIT related standards which the literature still lacks. It also examines the applicability of IS theories in a new area which allows others to relate their experiences to those reported. Secondly, this model can be used by decision makers in the healthcare sector, particularly those in developing countries, as a guideline while planning for the adoption of health data standards

The adoption of ICT in Malaysian public hospitals: the interoperability of electronic health records and health information systems

There have been a number of researches that investigated ICT adoption in Malaysian healthcare. With the small number of hospitals that adopt ICT in their daily clinical and administrative operations, the possibility to enable data exchange across 131 public hospitals in Malaysia is still a long journey. In addition to those studies, this research was framed under six objectives, which aim to critically review existing literature on the subject matter, identify barriers of ICT adoption in Malaysia, understand the administrative context during the pre and post-ICT adoption, and recommend possible solutions to the Ministry of Health of Malaysia (MoHM) in its efforts to implement interoperable electronic health records (EHR) and health information systems (HTIS). Specifically, this research aimed to identify the factors that had significant impacts to the processes of implementing interoperable EHR and HTIS by the MoHM. Furthermore, it also aimed to propose relevant actors who should involve in the implementation phases. These factors and actors were used to develop a model for implementing interoperable EHR and HTIS in Malaysia. To gather the needed data, series of interviews were conducted with three groups of participants. They were ICT administrators of MoHM, ICT and medical record administrators of three hospitals, and physicians of three hospitals. To ensure the interview feedback was representing the context of EHR and HTIS implementation in Malaysia, two hospital categories were selected, which included the hospitals with HTIS and non-HTIS hospitals. The government documents were then used to triangulate the feedback to ensure dependability, credibility, transferability and conformity of the findings. Two techniques were used to analyse the data, which were thematic analysis and theme matching. These two techniques were modified from its original method, known as pattern matching. The originality of this research was presented in the findings and methods to transform them into solutions and provide recommendation to the MoHM. In general, the results showed that the technological factors contributed less to the success of the implementation of interoperable EHR and HTIS compared to the managerial and administrative factors. Four main practical and social contributions were identified from this research, which included synchronisation of managerial elements, political determination and change management transformation, optimisation of use of existing legacy system (Patient Management System) and finally the roles of actors. Nevertheless, the findings of this research would be more dependable and transferable if more participants had been willing to participate especially among the physicians and those who managed the ICT adoptions under the MoHM

Sistemas interativos e distribuídos para telemedicina

doutoramento Ciências da ComputaçãoDurante as últimas décadas, as organizações de saúde têm vindo a adotar continuadamente as tecnologias de informação para melhorar o funcionamento dos seus serviços. Recentemente, em parte devido à crise financeira, algumas reformas no sector de saúde incentivaram o aparecimento de novas soluções de telemedicina para otimizar a utilização de recursos humanos e de equipamentos. Algumas tecnologias como a computação em nuvem, a computação móvel e os sistemas Web, têm sido importantes para o sucesso destas novas aplicações de telemedicina. As funcionalidades emergentes de computação distribuída facilitam a ligação de comunidades médicas, promovem serviços de telemedicina e a colaboração em tempo real. Também são evidentes algumas vantagens que os dispositivos móveis podem introduzir, tais como facilitar o trabalho remoto a qualquer hora e em qualquer lugar. Por outro lado, muitas funcionalidades que se tornaram comuns nas redes sociais, tais como a partilha de dados, a troca de mensagens, os fóruns de discussão e a videoconferência, têm o potencial para promover a colaboração no sector da saúde. Esta tese teve como objetivo principal investigar soluções computacionais mais ágeis que permitam promover a partilha de dados clínicos e facilitar a criação de fluxos de trabalho colaborativos em radiologia. Através da exploração das atuais tecnologias Web e de computação móvel, concebemos uma solução ubíqua para a visualização de imagens médicas e desenvolvemos um sistema colaborativo para a área de radiologia, baseado na tecnologia da computação em nuvem. Neste percurso, foram investigadas metodologias de mineração de texto, de representação semântica e de recuperação de informação baseada no conteúdo da imagem. Para garantir a privacidade dos pacientes e agilizar o processo de partilha de dados em ambientes colaborativos, propomos ainda uma metodologia que usa aprendizagem automática para anonimizar as imagens médicasDuring the last decades, healthcare organizations have been increasingly relying on information technologies to improve their services. At the same time, the optimization of resources, both professionals and equipment, have promoted the emergence of telemedicine solutions. Some technologies including cloud computing, mobile computing, web systems and distributed computing can be used to facilitate the creation of medical communities, and the promotion of telemedicine services and real-time collaboration. On the other hand, many features that have become commonplace in social networks, such as data sharing, message exchange, discussion forums, and a videoconference, have also the potential to foster collaboration in the health sector. The main objective of this research work was to investigate computational solutions that allow us to promote the sharing of clinical data and to facilitate the creation of collaborative workflows in radiology. By exploring computing and mobile computing technologies, we have designed a solution for medical imaging visualization, and developed a collaborative system for radiology, based on cloud computing technology. To extract more information from data, we investigated several methodologies such as text mining, semantic representation, content-based information retrieval. Finally, to ensure patient privacy and to streamline the data sharing in collaborative environments, we propose a machine learning methodology to anonymize medical images

Structured patient information management for efficient treatment and healthcare quality assurance in oncology

Die Behandlung von Patienten mit Tumoren im Kopf-Hals-Bereich gestaltet sich als komplexer und herausfordernder Prozess sowohl für den Patienten als auch für die behandelnden Ärzte und Chirurgen. Zur Gewährleistung der bestmöglichen individuellen Therapie werden vor Beginn der Behandlung zahlreiche diagnostische Verfahren durchgeführt. Hierzu zählen unter anderem medizinische bildgebende Verfahren wie z.B. Computertomographie (CT) oder Magnetresonanztomographie (MRT) sowie die Entnahme von tumorverdächtigem Gewebe während einer Panendoskopie zur exakten Bestimmung der Tumorart (Histologie, Grading, TNM-Klassifikation nach UICC, genaue Lokalisation des Primärtumors, der lokoregionären Metastasen und ggf. Fernmetastasen). Die gewonnenen Informationen bilden anschließend die Grundlage für die Entscheidung über die durchzuführende Therapie und stehen in unterschiedlichen klinischen Informationssystemen sowie auf Papierakten zur Verfügung. Leider werden die Daten im klinischen Alltag häufig nur unstrukturiert und schwer auffindbar präsentiert, da die führenden Informationssysteme nur unzureichend in den klinischen Arbeitsprozess integriert und untereinander schlecht vernetzt sind. Die präzise und erschöpfende Darstellung der jeweiligen individuellen Situation und die darauf aufbauende Therapieentscheidung sind aber entscheidend für die Prognose des Patienten, da der erste, gut geplante \"Schuss\" entscheidend für den weiteren Verlauf ist und nicht mehr korrigiert werden kann. In dieser Arbeit werden neue Konzepte zur Verbesserung des Informationsmanagements im Bereich der Kopf-Hals-Tumorbehandlung entwickelt, als prototypische Software implementiert und im klinischen Alltag in verschiedenen Studien wissenschaftlich evaluiert. Die Erlangung eines tiefgreifenden Verständnisses über die klinischen Abläufe sowie über beteiligte Informationssysteme und Datenflüsse stellte den ersten Teil der Arbeit dar. Aufbauend auf den Erkenntnissen wurde ein klinisches Informationssystem oncoflow entwickelt. Oncoflow importiert vollautomatisch relevante Patientendaten von verschiedenen klinischen Informationssystemen, restrukturiert die Daten und unterstützt Ärzte und Chirurgen im gesamten Therapieprozess. Das System wurde anschließend in unterschiedlichen Studien evaluiert und der klinische Nutzen in Bezug auf effizientere Arbeitsabläufe und eine verbesserte Informationsqualität gezeigt. Im folgenden Teil der Arbeit wurden Machine Learning Methoden genutzt um von Daten in der elektronischen Patientenakte auf den aktuellen Prozessschritt im Therapieprozess zu schließen. Der letzte Teil der Arbeit zeigt Möglichkeiten zur Erweiterung des Systems zur Nutzung in weiteren klinischen Fachdisziplinen auf

Relevance criteria for medical images applied by health care professionals : A grounded theory study.

This thesis studies relevance criteria for medical images' applied by health care professionals. The study also looks at the image information needs and image resources used by health care professionals, together with the image seeking behaviour of health care professionals from different disciplines. The work is a qualitative study that uses the Straussian version of grounded theory. The population of the study included health care professionals from different health and biomedical departments who worked in Sheffield Teaching Hospitals NHS Foundation Trust. In total twenty-nine health care professionals participated in this study and fifteen relevance criteria were identified from the data collected using semi-structured interviews and think-aloud protocols. The work forms part of the medical image retrieval track of ImageCLEF (ImageCLEFMed), and investigated the use of relevance criteria applied to search statements. Analysis indicates that some of the criteria identified by participants could be included in new topics used for future versions of the track. The findings of the study showed that health care professionals paid more attention to the visual attributes of medical images when selecting images and that they applied topical relevancy as the most frequent and most important criterion. The study found that health care professionals looked for medical images mainly for educational and research purposes and judged the relevancy of medical images based on their pictorial information needs and the image resources they used. We identified the difficulties that health care professionals faced when searching medical images in different image resources. Other findings also highlighted the need for, and the value of, looking at narrower subject communities within health and biomedical sciences for better understanding of relevance judgment and image seeking behaviour of the health care professionals