Biomedical subjects

G Surján

Publications and source records attributed to G Surján.

12 recordsLinked to original sources

PubMed2001

Indexing of medical diagnoses by word affinity method.

Automated coding of medical diagnoses is still an unsolved problem. Our goal in recent work was to find efficient, cheap and easy to implement method to assist the work of human encoders in hospitals. The proposed method is based on a vector-space model especially adapted to deal with short expressions, like clinical diagnoses. Using a set of coded diagnoses the co-occurrence of codes and words is more or less characteristic. The method describes these characteristics mathematically, by introduction of the so-called word adhesion. Two human encoders were asked to code the same set of 92 clinical diagnoses. Their results were compared to the ranked list of codes, produced by the computer. The results were better where the two human encoders agreed, and the overall results demonstrate the feasibility of the approach.

Abstracting and Indexing↗

PubMed2000

Typing of diseases in the Hungarian minimal basic data set for hospital treatment episodes.

For reimbursement and epidemiological statistics the coded diagnoses should be classified in types like principal diagnosis, complication, co-morbidity etc. Computer assisted semi-automatic coding systems usually does not pay attention to this problem. After the description of pertaining national regulation, we present a logical framework of an algorithm, which minimise the clerical work for physicians and presumably will satisfy the need of epidemiology and reimbursement. The algorithm makes difference between diagnosis and disease, various diagnostic statement types, and uses causal chains among conditions expressed by diagnoses.

Algorithms↗

PubMed1999

Questions on validity of International Classification of Diseases-coded diagnoses.

International Classification of Diseases (ICD) codes are used for indexing medical diagnoses for various purposes and in various contexts. According to the literature and our personal experience, the validity of the coded information is unsatisfactory in general, however the 'correctness' is purpose and environment dependent. For detecting potential error sources, this paper gives a general framework of the coding process. The key elements of this framework are: (1) the formulation of the established diagnoses in medical language; (2) the induction from diagnoses to diseases; (3) indexing the diseases to ICD categories; (4) labelling of the coded entries (e.g. principal disease, complications, etc.). Each step is a potential source of errors. The most typical types of error are: (1) overlooking of diagnoses; (2) incorrect or skipped induction; (3) indexing errors; (4) violation of ICD rules and external regulations. The main reasons of the errors are the physician's errors in the primary documentation, the insufficient knowledge of the encoders (different steps of the coding process require different kind of knowledge), the internal inconsistency of the ICD, and some psychological factors. Computer systems can facilitate the coding process, but attention has to be paid to the entire coding process, not only to the indexing phase.

Abstracting and Indexing↗

PubMed1999

Maintenance of self-consistency of coding tables by statistical analysis of word co-occurrences.

The author presents a method for maintaining the internal consistency of coding tables. The method was tested on a table used for assisting the daily work of indexing clinical cases to International Classification of Diseases. 300 item were tested selected randomly form a corpus of 3082 clinical diagnoses. The method discovered potential consistency problems in 39 cases, out of which 10 were false positive.

Data Interpretation, Statistical↗

PubMed1997

TSMI: a CEN/TC251 standard for time specific problems in healthcare informatics and telematics.

Time is the most important variable in healthcare, and standards are needed about how to represent information with explicit references to time. In this paper, the European Prestandard 'TSMI: time standards for healthcare specific problems' (CEN/TC251 preENV 12381) is presented which aims to be the first contribution to this harmonisation process, focusing on 'representation' and 'explicit reference' of temporal information in healthcare. The prestandard is mainly composed of two parts. First, the basic building blocks for modelling time-related information are introduced, and a formal representation scheme proposed. In a second part, conformance rules and principles for Healthcare Data and Information as well as for Healthcare Information Systems, are covered.

Artificial Intelligence↗

PubMed1997

Quality of healthcare related software applications--setting up an accreditation system in Hungary.

Meeting expectations of high quality health care, the safe and secure operation of medical information systems is a "must". However for healthcare software nationwide quality control systems are not widely used. A quality control project of health care applications in Hungary has been launched in 1996 by the Hungarian Society of Healthcare Informatics (MEIT) and Medico-Biological Section of Johann Neumann Society of Computing (NJSZT) by establishing a joint Healthcare Informatics Applications Accreditation Board (Board ESAB). The Board developed an evaluation methodology and a legal procedure to test health care software application modules. The evaluation method is based on international standards as ISO-9126 and on emerging European standards of CEN/TC 251. First rounds of accreditation already proved that there is a need among providers and users for the accreditation process. The authors hope that establishing an accreditation system will lead to a more balanced health care software market where users have an opportunity to inform themselves by the opinion of independent experts on the product they intend to purchase.

Accreditation↗

PubMed1997

On different roles of natural language information in medicine.

In this paper the authors analyze the main different function types of language in medical environment in different communicative situations and descriptive tasks. These functions are categorized as knowledge transfer, documentation, directive function, expression of emotions. The computer representation of the information have to be different according to the different tasks. The paper highlights the most important differences and concludes that further research is necessary in the details.

Communication↗

PubMed1995

[Method for the determination of the functional degree of esophageal stricture and the effectiveness of dilatation].

Based on their experiences of 494 oesophagus dilatation in 98 patients, authors developed a stadium system for defining the severity of dysphagia caused by oesophagus stenosis of stricture. This system is usable for follow-up the course of the disease, for the establishing the necessity of the dilatation, and for the comparison of results achieved by different dilatation methods, as well. The method is based on simple, well-defined clinical parameters, special skills or instrumentations not required, and fits the clinical experiences of many years of the authors. For this reasons it is useful both general practitioners and for the specialists performing the esophagus dilatation, as well.

Adult↗

PubMed1995

Third generation electronic medical record knowledge based perspectives.

There is a need to develop better electronic medical records. One possible solution is to put more and more 'routine' medical knowledge into systems handling medical records. In this paper, we analyze the current state-of-the-art of knowledge-based medical record handling; we mainly consider the work of Rector et al. [1]. We offer a more detailed 'four level' knowledge level model compared to the 'two level' model of Rector. The EMR of the future might be approached with a top-down method, using the above mentioned 'four level' model.

Artificial Intelligence↗

PubMedDate not supplied

Towards a quantitative approach of medical information. Part 1. Measures of a multidimensional medical information space.

Despite the importance of quantitative analysis of medical information, it is a rare subject in informatics literature. To stimulate more interest the authors propose a multidimensional medical information space, in which measures can be defined to compare different medical information objects or knowledge areas. To describe the measures, classical information theory, the general database theory of Sundgren and the Blois model of medical thinking are used. A space model of (at least) three dimensions is offered, where information objects might have a normalized length, a total depth (measuring embedded knowledge levels) and a complexity width.

Computer-Assisted Instruction↗

PubMedDate not supplied

Towards a quantitative approach of medical information. Part 2. Comparative measurement of medical information objects.

One of the key problems in medical knowledge representation is that we usually have no idea about the largeness of the knowledge to be represented. Underestimation of this largeness may occur frequently. Considering this situation, the authors have applied a method of measuring or estimating the largeness of a certain medical knowledge area modelled in a theoretical information space. The method is tested on two sets of terms, the OMED terminology of digestive endoscopy and on the second and third version of the SNOMED nomenclature. The assessment of largeness of a knowledge area does not seem possible by a single measure. The 'volume', 'density' and 'complexity' must be addressed separately. In the present study different medical knowledge-representation systems are compared according to their volume. Possible ways to estimate their complexity and density are mentioned.

Decision Making, Computer-Assisted↗

PubMedDate not supplied

Theoretical considerations on medical concept representation.

Concepts are seen as building elements of more compositional information objects in medicine. Consequently, representation of medical concepts plays a critical role in any information system. The authors present some of the key problems which need solution, such as definition of medical domain, analysis of internal structure, different subsets of medical concepts, and the problem of the 'elementary' concepts. As a result of these considerations we can conclude that the domain of medical concepts can hardly be delimited and consists of different subsets. These subsets need different representation methods according to their different nature. Some of these subsets have a hierarchic structure. In those one can find sometimes multiple hierarchies. We suggest avoiding multiple hierarchies in concept systems by the introduction of new dimensions.

Decision Support Techniques↗