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Biomedical subjects

J Brender

Publications and source records attributed to J Brender.

At least 19 recordsLinked to original sources
PubMed2000

Research needs and priorities in health informatics.

A Delphi study was accomplished on the topic "what is needed to implement the information society within healthcare? and which research topics should be given higher priority than other topics to achieve the desired evolution?", involving 29 international experts. The study comprised of four phases, (I) a brainstorming phase based on a open question; (II) an evaluation phase for mutual commenting; (III) a feedback phase allowing corrections/extensions; and (IV) a phase collecting the ratings of individual issues within a questionnaire synthesised from the previous phases. A total of 110 research items and 58 supplementary barriers were raised, divided into 14 topics grouped according to homogeneity. The emphasised research topics are business process re-engineering, the electronic patient record and connected inter-operating systems, (support for) evidence-based medicine and clinical guidelines, and education. Issues inherent to the healthcare domain often are the kernel of the research recommended. Similarly, methods and 'people'-issues are strongly emphasised among the research issues in general and among those for which the experts' joint opinion was rated as statistically significant. In contrast, only a minority of the research issues emphasised was related to technical issues.

Delphi Technique↗
PubMed1999

Methodology for constructive assessment of IT-based systems in an organisational context.

Even if painted in black and white, there is no doubt that the assumptions for the application of traditional approaches for user requirements specification are more or less unfulfilled. This indicates a need for evolutionary system development combined with constructive assessment throughout the life-cycle of an IT-based solution. A methodology for constructive technology assessment is presented, which 1) covers the entire system life-cycle; 2) has users from the application domain of the future system, or their representatives, as the target users of the assessment methodology; 3) enables constructive assessment during the development of an IT-based solution; 4) is applicable independently of the system development approach; and 5) provides users of the IT-based solution with information enabling them to decide whether or not to take the system into real-life clinical usage.

Computer Systems↗
PubMed1999

Research needs and priorities in health informatics--early results of a Delphi study.

A four-phased Delphi study has been performed on the topic of "research needs and priorities to implement the Information Society within Healthcare". This contribution presents the outcome of the first three phases. The biggest surprises are that 'Telemedicine' is relatively lower ranked than expected, and that 'Business Process Re-engineering' is the highest ranking topic, as judged from the number of issues and barriers raised by the expert panel.

Delphi Technique↗
PubMed1998

Computer-aided test selection and result validation-opportunities and pitfalls.

Dynamic test scheduling is concerned with pre-analytical preprocessing of the individual samples within a clinical laboratory production by means of decision algorithms. The purpose of such scheduling is to provide maximal information with minimal data production (to avoid data pollution and/or to increase cost-efficiency). Our experience shows that there is a practical limit to the extent of exploitation of the principle of dynamic test scheduling, unless it is automated in one way or the other. This paper analyses some issues of concern related to the profession of clinical biochemistry, when implementing such dynamic test scheduling within a Laboratory Information System (and/or an advanced analytical workstation). The challenge is related to 1) generation of appropriately validated decision models, and 2) mastering consequences of analytical imprecision and bias.

Algorithms↗
PubMed1997

Cognitive evaluation: how to assess the usability of information technology in healthcare.

As the adoption of information technology has increased, so too has the demands that these systems become more adapted to the physicians and nurses environments, to make access and management of information easier. The developers of information systems in Healthcare must use quality management techniques to ensure that their product will satisfy given requirements. This underlines the importance of the preliminary phase where Users Requirements are elicited. Some methodologies, such as KAVAS (E.M.S. Van Gennip, F. Grémy, Med. Inform. 18, 1993, 179) chose to use a continuous assessment protocol as a key strategy for quality management. At each stage of the conception and development of a prototype, the assessment checks that it conforms to the expectation of the users' requirements. The methodology of evaluation is then seen as a dynamic process which is able to improve the design and development of a dedicated system. The purpose of this paper is to demonstrate the necessity to include a cognitive evaluation phase in the process of evaluation by: (1) evaluating the integration (usability) of the I.T. in the activity of the users; and (2) understanding the motives underlying their management of information. This will help the necessary integration of information management in the workload of the healthcare professionals and the compatibility of the prototypes with the daily activity of the users.

Cognition↗
PubMed1997

Assessment of IT-based solutions in healthcare: trends in today's practice and justification of tomorrow's approach.

State-of-the-Art with respect to assessment of IT-based solutions in Healthcare is discussed with a user-oriented perspective on system development and assessment. Based on this and other basic conditions reported in the literature, requirements for a methodology for user-driven, formative assessment during the entire life-cycle of the IT-based system are synthesised.

Artificial Intelligence↗
PubMed1996

User requirements on the future laboratory information systems.

Today numerous information technology solutions exist for the clinical laboratory which operate either as stand-alone functionalities or with ad hoc integration solutions. The OpenLabs (A2028) AIM Project puts emphasis on the design and specification of a framework for the interoperability of existing systems and new advanced services, and consequently concentrates on the issue of integration. The purpose of the OpenLabs open architecture is to serve as a functional solution to this integration. A basic principle for this open architecture is that each of the advanced services shall be able to function individually or in any combination with an existing Laboratory Information System (LIS), and that it shall enable new modular functionalities to be incorporated in a 'plug-and-play' fashion. The synthesis of the main user needs and requirements implies that the future IT solutions: (a) must be highly flexible and maximally customizable--by the users themselves; (b) are based on the concept of open systems, both technically and functionally, which enables modular functionalities from different vendors to co-operate forming a global LIS functionality; (c) are future viable and able to incorporate already installed IT functionalities; (d) support management of failure prevention, of repair, of success, and of change. The establishment of an open architecture implies that a market will develop for modular, scaleable, and cost-effective LIS features without today's dependence on individual manufacturers and hardware/software platforms.

Clinical Laboratory Information Systems↗
PubMed1996

Specifying an open clinical laboratory information system.

This paper presents an overview of the architectural infrastructure in which existing laboratory information systems can be made to interoperate with additional modules offering a range of advanced clinical laboratory functionalities. The infrastructure is based on an open distributed computing platform, and its specification is described using the open distributed processing reference model.

Clinical Laboratory Information Systems↗
PubMed1995

Framework for quality assessment of knowledge.

One of the key issues in the development (and subsequent application) of medical knowledge-be it in terms of a KBS or otherwise-is the assessment of its quality. We present a framework for how to manage and make measurable the quality of the semantic as well as pragmatic aspects of the knowledge embedded in classification models during the development of such models.

Artificial Intelligence↗
PubMed1994

KAVAS-2: Knowledge Acquisition, Visualization and Assessment System.

The objective of KAVAS-2 is the development of a tool, named KAVIAR, with which domain experts can make their knowledge explicit. It contains components for (computer assisted) knowledge elicitation and for machine learning. A key issue in KAVAS is the assessment of the quality of the classification and domain models built. Various quality measures are available and implemented in KAVIAR to assess the quality of models, specifically those developed from data bases by machine learning techniques.

Computer Simulation↗
PubMed1994

On the quality of neural net classifiers.

This paper describes several concepts and metrics that may be used to assess various aspects of the quality of neural net classifiers. Each concept describes a property that may be taken into account by both designers and users of neural net classifiers when assessing their utility. Besides metrics for assessment of the correctness of classifiers we also introduce metrics that address certain aspects of the misclassifications. We show the applicability of the introduced quality concepts for selection among several neural net classifiers in the domain of thyroid disorders.

Humans↗
PubMed1994

A methodology for evaluation of knowledge-based systems in medicine.

Evaluation is critical to the development and successful integration of knowledge-based systems into their application environment. This is of particular importance in the medical domain--not only for reasons of safety and correctness, but also to reinforce the users' confidence in these systems. In this paper we describe an iterative, four-phased development evaluation cycle covering the following areas: (i) early prototype development, (ii) validity of the system, (iii) functionality of the system, and (iv) impact of the system.

Artificial Intelligence↗
PubMed1993

Problem-oriented management of laboratory work through dynamic test scheduling.

This paper gives an overview of problems inherent in dynamic test scheduling together with some model solutions. Dynamic test schedules are decision tree-like protocols for cost-efficient management of analytical production in a clinical laboratory. The present analysis is based on previous practical experience and concludes that it is not feasible to introduce dynamic test scheduling on a large scale without computer-based support, because of the increase in complexity of the laboratory work processes. Further, our experience is that it is extremely complex to incorporate the dynamic test scheduling functionality into an existing Laboratory Information System (LIS). The approach pursued in the OpenLabs (A2028) AIM Project for implementing dynamic test scheduling is to provide the necessary functionality as a stand-alone module interconnected with a LIS in an open systems solution.

Clinical Laboratory Information Systems↗