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PubMedDate not supplied

[Design criteria for a computerized clinical database].

The techniques of data management constitute a principal field in medical informatics, both for systems oriented to sole information retrieval, and basic-systems for more sophisticated applications. The operative utility of a data base depends on a careful planning based on foreseen requirements, and on the observance of some methodological rules. Such as, a precised preliminary study for the selection of clinical data to include in the data base, the choice of better tools and methodologies for the data collection and the right programming of software for the management of the archives. The knowledge of these problems allows, in many cases, the programming of computerized data base to use efficiently in the management of clinical information and in the planning of research. These problems, which do not depend on the hardware used, are commonly found in these applications. However, they have to be solved either for the use of large data base in hospital, which run on mainframe, or for the archives of the department, which can be built by every clinician on his own personal computer.

Humans↗
PubMed1999

Intelligent visualization and exploration of time-oriented clinical data.

Physicians and other care providers often need to quickly browse and interpret large numbers of time-oriented clinical data. Reducing the information overload involving such tasks is a major goal for medical information systems. We describe a conceptual architecture and software implementation specific to the task of interpretation, summarization, visualization, explanation, and interactive exploration of time-oriented clinical data and the multiple levels of meaningful concepts that can be derived from these data. We build on our work on abstraction of time-oriented clinical data using a knowledge base, acquired from expert physicians, of temporal properties of the data. The core module of the new framework is called KNAVE (Knowledge-based Navigation of Abstractions for Visualization and Explanation). Health care providers can manipulate the display though several visualization and exploration operators. These operators have semantics that are domain independent but that are customized automatically for the application by access to the domain-specific knowledge base. The display, which reflects data and derived interpretations in the patient's database, changes when the user explores key relations (e.g., the dependency hierarchy) in the knowledge base of the relevant clinical domain. Preliminary assessment of the initial prototype with several clinical users has been encouraging. The KNAVE methodology has broad ramifications for reducing the load that large numbers of time-oriented clinical data put on care providers.

Artificial Intelligence↗
PubMed1990

Reference standards for software evaluation.

The field of automated ECG analysis was one of the earliest topics in Medical Informatics and may be regarded as a model both for computer-assisted medical diagnosis and for evaluating medical diagnostic programs. The CSE project has set reference standards of two kinds: In a broad sense, a standard how to perform a comprehensive evaluation study, in a narrow sense, standards as specific references for evaluating computer ECG programs. The evaluation methodology used within the CSE project is described as a basis for presentation of results which are published elsewhere in this issue.

Diagnosis, Computer-Assisted↗
PubMed2005

Informatics infrastructure of CAD system.

A computer aided diagnosis (CAD) system requires several components which influence its effectiveness. An image processing methodology is responsible for the analysis, database structure archives and distributes the patient demographics, clinical information, and image data. A graphical user interface is applied in order to enter the data and present it to the user. By designing dynamic Web pages a remote access to the entire is granted. The computer aided diagnosis system includes three layers, which might be installed on various platforms. Elements of the application software are designed independently. Integration of all components is another issue discussed in the presented paper. Implementation of a computer aided diagnosis system improves and accelerates the analysis by giving to the user objective measurement tools. It also standardizes the decision-making process and solves the problem of replicability. Finally, it permits a set of images and features to be collected and recognized as a medical standard and be applied in education and research.

Diagnosis, Computer-Assisted↗
PubMed2006

Individualization, globalization and health--about sustainable information technologies and the aim of medical informatics.

This paper discusses aspects of information technologies for health care, in particular on transinstitutional health information systems (HIS) and on health-enabling technologies, with some consequences for the aim of medical informatics. It is argued that with the extended range of health information systems and the perspective of having adequate transinstitutional HIS architectures, a substantial contribution can be made to better patient-centered care, with possibilities ranging from regional, national to even global care. It is also argued that in applying health-enabling technologies, using ubiquitous, pervasive computing environments and ambient intelligence approaches, we can expect that in addition care will become more specific and tailored for the individual, and that we can achieve better personalized care. In developing health care systems towards transinstitutional HIS and health-enabling technologies, the aim of medical informatics, to contribute to the progress of the sciences and to high-quality, efficient, and affordable health care that does justice to the individual and to society, may be extended to also contributing to self-determined and self-sufficient (autonomous) life. Reference is made and examples are given from the Yearbook of Medical Informatics of the International Medical Informatics Association (IMIA) and from the work of Professor Jochen Moehr.

Decision Trees↗
PubMedDate not supplied

An operational model for patient-centered informatics.

There are no multidisciplinary operational models to guide nursing informaticists and clinical system users in the design and implementation of computer-supported multidisciplinary care. The Patient-Centered Informatics Model is offered as just such a pragmatic guide. It fuses earlier work with new concepts and allows a visual depiction of crucial elements-influencing factors such as regulations and healthcare delivery models, system attributes such as healthcare delivery methods, knowledge base and supporting technology and categories of results of application processing. The model can help users and executives organize their thinking about the design, implementation, and evaluation of clinical systems in complex settings.

Computer Simulation↗
PubMed1995

[Contribution of computers and telepathology in cancerologic pathology].

The histologic or cytologic diagnosis of a tumoral lesion may be sometimes very difficult to do even for a senior pathologist. Nevertheless, it is necessary to recognize a malignant process with reliability and security. The usual way to solve some difficult problems is firstly to search documentations in books or atlas and then to discuss the slides in common. Sometimes it is necessary to dispatch the original documents to a national or international expert. Now computers are used in any private or public department of Pathology. Some new informatics developments allow to send good digitized pictures to an expert and to discuss with him. It is also possible to elaborate a data base of digitized images which can be edited on CD-Rom. We describe the development and the use of these technics in France and elsewhere. It seems that they could have an increasing role for quality assurance in tumoral pathology.

Cancer Care Facilities↗
PubMed2005

Mapping cognitive work: the way out of healthcare IT system failures.

The failure of automation to improve clinical performance is likely rooted in the design concepts on which IT systems are based. Current systems provide clinicians with specific direction about how to care for individual patients. This is much like the specific, detailed, complicated, and narrow trip route driving directions that can be obtained from various web sites. Daily healthcare work rarely has the certainty that makes such directions useful. Rather than directions, useful healthcare automation is likely to have characteristics of a map. Clinicians could use its depictions of available routes, obstacles, and distances between the current and goal locations in order to choose routes and to track progress toward goals. Such representations are likely to be quite different than those currently incorporated in healthcare automation. We demonstrate the concept of creating maps and using constraints as the basis for the design of healthcare automation.

Cognition↗
PubMed2006

A user-centred deployment process for ICT in health care teams--experiences from the OLD@HOME project.

OBJECTIVE: To present a user-centred method for introducing ICT in health care organisations, taking factors that influence acceptance into account. METHODS: User centred methods are used in combination with previous research regarding factors that affect user acceptance, in order to facilitate users' acceptance of new ICT tools. RESULTS: A method is presented that supports the introduction of ICT in team work. The method consists of three major steps; (1) the start-up seminar, (2) end user education and (3) continuous follow-up during the deployment phase. Important results of the start-up seminar are documentation of the users' expectations, and an agreement of ground rules that supports both the social norm factor and the users' perceived behavioural control. Education and follow-up also improve perceived behavioural control, and by involving super users perceived usefulness and ease of use can be improved through subjective norm. CONCLUSION: Key factors in the deployment process are; user participation, end user experience and education, and continuous follow-up of the process.

Computer Literacy↗
PubMed2002

Cognitive engineering in interface design.

Today, many medical information systems are not satisfactory to their users. To ensure ultimate acceptance of health care information systems asks for systems that map on health care workers' tasks and on their cognitive processes in performing these tasks. The development of human-oriented computer interfaces requires insight in users' information needs and information processing in view of the tasks that will be computer-supported. Cognitive engineering aims at understanding the fundamental principles behind human activities that are relevant in designing a system that supports these activities. The application of cognitive engineering methods may therefore contribute to computer systems that fit better in health care working practices. We used cognitive engineering methods in designing a user interface for a physicians' workstation to support them in preparing their patient screening. The information needs and information search strategies of 4 physicians were revealed by systematic analyses of verbal protocols and video's while they successively worked through 10 paper-based patient records in preparing their patient visits. The results of these analyses were used as input for the design of a conceptual higher-order model that represents both the information needs and information search strategy of these physicians. Based on this higher-order conceptual model, we developed paper-mock ups and a first prototype of the user interface. The physicians will evaluate this prototype in the next phase of the project.

Cognition↗
PubMed1999

A JAVA implementation of a medical knowledge base for decision support.

Distributed decision support is a challenging issue requiring the implementation of advanced computer science techniques together with tools of development which offer ease of communication and efficiency of searching and control performance. This paper presents a JAVA implementation of a knowledge base model called ARISTOTELES which may be used in order to support the development of the medical knowledge base by clinicians in diverse specialised areas of interest. The advantages that are evident by the application of such a cognitive model are ease of knowledge acquisition, modular construction of the knowledge base and greater acceptance from clinicians.

Artificial Intelligence↗
PubMed2005

The use of receiver operating characteristic curves in biomedical informatics.

Receiver operating characteristic (ROC) curves are frequently used in biomedical informatics research to evaluate classification and prediction models for decision support, diagnosis, and prognosis. ROC analysis investigates the accuracy of a model's ability to separate positive from negative cases (such as predicting the presence or absence of disease), and the results are independent of the prevalence of positive cases in the study population. It is especially useful in evaluating predictive models or other tests that produce output values over a continuous range, since it captures the trade-off between sensitivity and specificity over that range. There are many ways to conduct an ROC analysis. The best approach depends on the experiment; an inappropriate approach can easily lead to incorrect conclusions. In this article, we review the basic concepts of ROC analysis, illustrate their use with sample calculations, make recommendations drawn from the literature, and list readily available software.

Biomedical Engineering↗