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An academic department of health informatics: a vision for the 21st century.

The purpose of this article is to share the vision of an academic health science center in creating a centralized academic and service Department of Health Informatics. To do this, we will present background on the institution, a brief discussion of informatics (including medical and health informatics), and then look in-depth at the Department of Health Informatics, including its mission, goals, organizational structure and operations.

Computer User Training↗

Critical dimensions in medical informatics.

A typology of medical informatics applications is proposed around three dimensions: the dimension of care, the dimension of information and knowledge, and the aspects of the computerized society. These dimension can help both to evaluate application or research papers in the field or to derive long term goals for the discipline. In the first dimension medical informatics appears more as a technology driven by external forces such as the general progress of medicine or the integration of economical constraints in the choice of optimal procedures. It is argued that barriers to overcome as well as challenges for future research mainly remain in the two last dimensions.

Artificial Intelligence↗

Informatics in the service of health, a look to the future.

The paper attempts a balanced look at the directions of health informatics required in the future. In a high level review of impediments to health and health care a number of issues are identified that may be amenable to improvement by contributions from health informatics. Attention is drawn to the improvement of the collection and dissemination of knowledge in addition to the analysis of morbid conditions as a focus for health informatics. On this basis a review of the current state of health information systems is undertaken. The importance of adaptable user interfaces for end users and systems personnel, privacy and confidentiality protection, and linkage among clinical support systems and knowledge repositories is stressed. These improvements hinge on advancements in medical concept representation. Canadian contributions to these developments, particularly the instigation of Evidence Based Medicine (EBM) are briefly reviewed.

Canada↗

Realtime textured 3D-models for medical applications.

Realistic visualisation becomes more and more important in medicine. Whenever a patient individual 3D-model was generated the aim is to visualise the model as realistic as possible. We use 3D-models in our diagnostic and therapeutic tools for intraoperative visualisation of e.g. CT-scans. Most medical tools uses surface-rendering or volume-rendering for virtual visualisation. The coloration of a visualised model is normally done by using a convenient colour for each surface resp. volume. Our approach for 3D-models generated from motion in image series (e.g. videoendoscopes) is to add textures to the 3D-model. The main problem is, to handle the huge amount of videoimage-data (20Mb/sec.) and render the model in realtime.

Computer Simulation↗

A linear programming approach to limited angle 3D reconstruction from DSA projections.

OBJECTIVES: We investigate the feasibility of binary-valued 3D tomographic reconstruction using only a small number of projections acquired over a limited range of angles. METHODS: Regularization of this strongly ill-posed problem is achieved by (i) confining the reconstruction to binary vessel/non-vessel decisions, and (ii) by minimizing a global functional involving a smoothness prior. RESULTS: Our approach successfully reconstructs volumetric vessel structures from three projections taken within 90 degrees. The percentage of reconstructed voxels differing from ground truth is below 1%. CONCLUSION: We demonstrate that for particular applications--like Digital Subtraction Angiography--3D reconstructions are possible where conventional methods must fail, due to a severely limited imaging geometry. This could play an important role for dose reduction and 3D reconstruction using non-conventional technical setups.

Angiography, Digital Subtraction↗

Objective evaluation of three-dimensional image registration algorithms--tools for optimization and evaluation.

OBJECTIVE: The registration of medical volume data sets plays an important role when different images or modalities are used during computer-assisted surgical procedures. Nevertheless, it is often questionable how robust and accurate the underlying algorithms really are. Therefore, the goal is to foster the establishment of methods for an objective evaluation. METHOD: To reliably calculate the accuracy of registration algorithms, a reference transformation must be known. Due to the unknown perfect registration for real clinical data, the simulation of realistic data and successive affine transformations are employed. The simulation is based on models of the respective imaging modality where the dominant physical effects are taken into account. This gives the user full control over all simulation and transformation parameters. Finally, suitable quality measures are applied which allow a systematic evaluation of image registration accuracy by comparing the known theoretical result and the transformation calculated by the algorithm under investigation. RESULTS: During the development of a new registration algorithm, the presented method proved to be a very valuable tool for optimization and evaluation of registration accuracy, since it allows objective numerical comparison of the calculated results. CONCLUSIONS: The presented method can be used during the development of algorithms for optimization and for quantitative comparison of different registration schemes. The respective software tool can automatically generate and transform simulated but realistic data. Employing suitable numerical quality measures, an objective evaluation of registration results can be easily obtained. Still, the validity of the relatively simple models has to be verified to draw reliable conclusions with respect to real data.

Algorithms↗

Modeling a medical environment: an ontology for integrated medical informatics design.

Modern medical environments have seen an increase in technological complexity and pressures of handling more patients with fewer resources, resulting in higher demands on medical practitioners. Medical informatics designers will have to focus on the problem of organizing medical information more effectively to enable practitioners to cope with these challenges. This article addresses this research problem for the particular area of medical problem solving in patient care. First, we describe a traditional modeling approach for medical reasoning used as a basis for developing some decision support systems. We argue these models may be faithful to what is known about biomedical knowledge, but they have limitations for human problem solving, especially in unanticipated situations. Second, we present an ontological framework, known as the abstraction hierarchy (Rasmussen, IEEE Trans. Man. Cybernetics 15 (1985) 234-243), for integrating patient representations that are faithful to existing biomedical knowledge and that are consistent with what is known about human problem solving. Through an example of a critical event in the operating room, we reveal how this framework can support medical problem solving in unanticipated situations. Third, we show how to use these representations as a frame of reference for mapping medical roles, responsibilities, sensors, and controls in an operating room context. Finally, we provide some insight for medical informatics designers in using this framework to design novel training programs and human-computer displays.

Decision Support Techniques↗

A methodology for web-enabling a computer-based patient record with contributions from cognitive science.

Cognitive science is a rich source of insight for creative use of new Web technologies by medical informatics workers. I outline a project to Web-enable an existing computer-based patient record (CPR) in the context of ideas from philosophy, linguistics, artificial intelligence, and cognitive psychology. Web prototypes play an important role (a) because Web technology lends itself to rapid prototype development, and (b) because prototypes help team members bridge among disparate medical, computing, and business ontologies. Six Web-enabled CPR prototypes were created and ranked. User scenarios were generated using a user communication matrix. Resulting prototypes were compared according to the degree to which they satisfied medical, computing, and business constraints. In a different organization, or at different time, candidate prototypes and their ranking might have been different. However, prototype generation and comparison are fundamentally influenced by factors usefully understood in a cognitive science framework.

Cognitive Science↗

Combining medical informatics and bioinformatics toward tools for personalized medicine.

OBJECTIVES: Key bioinformatics and medical informatics research areas need to be identified to advance knowledge and understanding of disease risk factors and molecular disease pathology in the 21 st century toward new diagnoses, prognoses, and treatments. METHODS: Three high-impact informatics areas are identified: predictive medicine (to identify significant correlations within clinical data using statistical and artificial intelligence methods), along with pathway informatics and cellular simulations (that combine biological knowledge with advanced informatics to elucidate molecular disease pathology). RESULTS: Initial predictive models have been developed for a pilot study in Huntington's disease. An initial bioinformatics platform has been developed for the reconstruction and analysis of pathways, and work has begun on pathway simulation. CONCLUSIONS: A bioinformatics research program has been established at GE Global Research Center as an important technology toward next generation medical diagnostics. We anticipate that 21 st century medical research will be a combination of informatics tools with traditional biology wet lab research, and that this will translate to increased use of informatics techniques in the clinic.

Biomedical Research↗

Clinical informatics: 2000 and beyond.

Healthcare has begun to flounder in the mounting flood of data available from automated monitoring equipment, microprocessor controlled life-support equipment, such as ventilators, ever more sophisticated laboratory tests, and the myriad of minor technological wonders that every hospital and clinic seem to collect. It is no longer enough to merely display the data in a large spreadsheet or on a complex, colorful time-sequence graph. The next generation of healthcare information systems must help the clinician to assimilate the myriad of data and to make fast and effective decisions. The following is a list of features that the next generation of computer systems will have to include if they are to have a significant impact on the quality of patient care: data acquisition, data storage, information display, data processing, and decision support. By automating or streamlining repetitive or complex tasks, correlating and presenting complex and potentially confusing data, and tracking patient outcomes, the computer can augment clinicians' skills to improve patient care.

Computer Systems↗

Computerized management of respiratory care.

Respiratory care as an organized discipline is only about 45 years old, and the management of this dynamic allied health profession has usually been characterized by a demand-for-service mentality. As pressure continues to control costs, those departments that maximize quality patient care cost-effectively with thoroughly documented outcomes are in a better position to compete for future resources. The practice of respiratory care is changing as is the practice of medical care in general. Accountability for resource consumption and the quality of the product delivered are essential elements in the delivery of respiratory modalities. We have developed and implemented a comprehensive patient-data-based approach to the management of respiratory care. The essential elements of this approach are (1) relative-value-unit procedure base; (2) individual, shift, and department productivity that is attached to the annual performance review process; (3) management reporting on a 24-hour basis, with biweekly review at the management level; (4) development and implementation of a comprehensive patient-data-documentation system that permits automatic patient billing and 100% data review for quality-assurance documentation; (5) the development of a medical alerting system that alerts the Medical Director and Respiratory Care staff to potentially harmful events that, if untreated, may result in increased morbidity or mortality; and (6) the development of concurrent and retrospective tools for patient-outcomes research. These functions are supported by an active Medical Informatics Department that is nationally recognized in medical computing and logic application.

Cost-Benefit Analysis↗

Exploring the portability of informatics capabilities from a clinical application to a bioscience application.

This report describes XDesc (eXperiment Description), a pilot project that serves as a case study exploring the degree to which an informatics capability developed in a clinical application can be ported for use in the biosciences. In particular, XDesc uses the Entity-Attribute-Value database implementation (including a great deal of metadata-based functionality) developed in TrialDB, a clinical research database, for use in describing the samples used in microarray experiments stored in the Yale Microarray Database (YMD). XDesc was linked successfully to both TrialDB and YMD, and was used to describe the data in three different microarray research projects involving Drosophila. In the process, a number of new desirable capabilities were identified in the bioscience domain. These were implemented on a pilot basis in XDesc, and subsequently "folded back" into TrialDB itself, enhancing its capabilities for dealing with clinical data. This case study provides a concrete example of how informatics research and development in clinical and bioscience domains has the potential for synergy and for cross-fertilization.

Clinical Medicine↗

IMED: the development of a consortium.

The California Consortium for Informatics in Medical Education and Development began in 1990 upon the recommendation of the academic deans of eight California medical schools. It provides one model of how consortia can promote the development, evaluation, dissemination, and utilization of technology-based medical education.

California↗

A review of medical education and medical informatics.

Physicians have considerable difficulty collecting and interpreting information from patients, dealing with the uncertainties associated with diagnosing and treating their patients, communicating precisely with one another, keeping up to date, and applying recommended procedures when indicated. Some of the advances in information technology may help physicians to manage information more effectively through more accessible, validated clinical indexes, data bases of diagnostic test characteristics, computerized audits of clinical activities with feedback, expert systems, on-line access to the medical literature, and other tools of medical informatics. Medical educators can catalyze this process by facilitating the introduction of information technology into academic clinical settings so that students can learn its use first-hand and by promoting the evolution of this and other aspects of medical informatics, a new discipline dedicated to the solution of information problems in health care. The potential roles for computer-aided instruction and centralized computer laboratories in medical schools are much less clear.

Canada↗

Education in medical informatics in The Netherlands: a nationwide policy and the Erasmus curriculum.

The curricula of all Medical Faculties still bear the characteristics of an era in which the physician was not educated in managing medical information systems, using communication networks, and processing knowledge. In attempting to formulate the prerequisites for developing and adjusting future curricula, we discuss the evolution of medical information technology during the past 25 years and give examples to illustrate that, by extrapolating current trends, future developments in information technology, medicine and education can be predicted. A plea is made for a strong interaction between scientific developments in medical informatics and academic education. In addition, a model based on our experience in medical informatics education of over 15 years, is pointed out. Furthermore, a nationwide policy on medical informatics in The Netherlands, is discussed. Our treatise is concluded by presenting the outline of the curriculum in medical informatics at the Erasmus University in Rotterdam. Educational recommendations conclude the paper.

Computers↗

Improving the classification of multiple disorders with problem decomposition.

Differential diagnosis of multiple disorders is a challenging problem in clinical medicine. According to the divide-and-conquer principle, this problem can be handled more effectively through decomposing it into a number of simpler sub-problems, each solved separately. We demonstrate the advantages of this approach using abductive network classifiers on the 6-class standard dermatology dataset. Three problem decomposition scenarios are investigated, including class decomposition and two hierarchical approaches based on clinical practice and class separability properties. Two-stage classification schemes based on hierarchical decomposition boost the classification accuracy from 91% for the single-classifier monolithic approach to 99%, matching the theoretical upper limit reported in the literature for the accuracy of classifying the dataset. Such models are also simpler, achieving up to 47% reduction in the number of input variables required, thus reducing the cost and improving the convenience of performing the medical diagnostic tests required. Automatic selection of only relevant inputs by the simpler abductive network models synthesized provides greater insight into the diagnosis problem and the diagnostic value of various disease markers. The problem decomposition approach helps plan more efficient diagnostic tests and provides improved support for the decision-making process. Findings are compared with established guidelines of clinical practice, results of data analysis, and outcomes of previous informatics-based studies on the dataset.

Algorithms↗

Learning just-in-time in medical informatics.

Just-in-time learning (JITL) methodology has been applied to many areas of knowledge acquisition and dissemination. The paradigm is a challenge to the traditional classroom course-oriented approach with the aim to shorten the learning time, increasing the efficiency of the learning process, improve availability and save money. The information technology tools and platforms have been heavily involved to develop and deliver JITL. This paper discusses the main characteristics of JITL with regard to its implementation to teaching Medical Informatics.

Audiovisual Aids↗