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J H van Bemmel

Publications and source records attributed to J H van Bemmel.

At least 19 recordsLinked to original sources
PubMed1992

Electronic communication between providers of primary and secondary care.

OBJECTIVE: To study the effects of the introduction of electronic data interchange between primary and secondary care providers on speed of communication, efficiency of data handling, and satisfaction of general practitioners with communication. DESIGN: Comparison of traditional paper based communication for laboratory reports and admission-discharge reports between hospital and general practitioners and electronic data interchange. SETTING: Twenty-seven general practitioners whose offices were equipped with a practice information system and two general hospitals. OUTCOME MEASURES: Paper based communication was evaluated by questionnaire responses from and interviews with care providers; electronic communication was evaluated by measuring time intervals between generation and delivery of messages and by assessing doctors' satisfaction with electronic data interchange by questionnaire. RESULTS: Via paper mail admission-discharge reports took a median of 2-4 days, and laboratory reports 2 days, to reach general practitioners. With electronic data interchange almost all admission-discharge reports were available to general practitioners within one hour of generation. When samples were analysed on the day of collection (as was the case for 174/542 samples in one hospital and 443/854 in the other) the laboratory reports were also available to the general practitioner the same day via electronic data interchange. Fifteen general practitioners (of the 24 who returned the questionnaire) reported that the use of electronic admission-discharge reports provided more accurate and complete information about the care delivered to their patients. Ten general practitioners reported that electronic laboratory reports lessened the work of processing the data. CONCLUSION: Electronic communication between primary and secondary care providers is a feasible option for improving communication.

Communication↗
PubMed1992

Improvement of automated electrocardiographic diagnosis by combination of computer interpretations of the electrocardiogram and vectorcardiogram.

In the international project "Common Standards for Quantitative Electrocardiography" (CSE), diagnostic results of different computer programs for the interpretation of the electrocardiogram (ECG) and of the vectorcardiogram (VCG) were combined, and it was shown that the "combined program" performs better than each program separately. Because the program MEANS (Modular ECG Analysis System) comprises 2 different classification programs--one for the ECG, the other for the VCG--this allowed investigation of whether the combined interpretations would yield a better diagnostic result than either one separately. This approach requires that a VCG always be recorded in addition to the ECG. To circumvent this complication, the VCG was reconstructed from the simultaneously recorded ECG leads. This reconstructed VCG was then interpreted by the VCG classification program, whereupon the diagnostic interpretations of the ECG and the reconstructed VCG were combined. For the validation, the CSE database of documented ECGs and VCGs (n = 1,220) was used. The combination of the ECG and VCG interpretations yielded a better diagnostic result than each interpretation program separately (total accuracy 74.2% (ECG + VCG) vs 69.8% (ECG) and 70.2% (VCG), p less than 0.001 in both cases). The results for the reconstructed VCG (total accuracy 70.5%) are comparable to those for the ECG and the VCG (p greater than 0.10 in both cases). The performance of the combined interpretations of ECG and reconstructed VCG (total accuracy 73.6%) is approximately the same as that of the combined ECG and VCG (p greater than 0.10). Thus, the performance of an ECG computer program can be improved by incorporating both ECG and VCG classificatory knowledge, using only the ECG itself.

Diagnosis, Computer-Assisted↗
PubMed1992

Variability in ECG computer interpretation. Analysis of individual complexes vs analysis of a representative complex.

Variability in the electrocardiogram (ECG) can be due to extrinsic noise or can be caused by intrinsic factors, such as changes in the volume conductor or in the heart itself. Computer programs for the interpretation of the ECG base their diagnostic classification on one set of measurements that is derived from a representative PQRST complex or that is computed by taking the median from the measurements for each complex in the recording. However, these methods may fail to do justice to the intrinsic variability that may be present in the ECG. An alternative method is proposed: derive a set of measurements from each complex in the recording, classify each individual complex separately, and then combine the individual classifications into one final classification. This procedure has been evaluated on a validated database (n = 1,220) using an ECG computer program. Total accuracy against the clinical evidence increased from 69.8% for the interpretations of the averaged complexes to 71.2% for the combined interpretations of the individual complexes (p < 0.001). The effect of beat-to-beat variation on the measurements and classifications is demonstrated and the influence of extrinsic and intrinsic variability is assessed.

Electrocardiography↗
PubMed1992

Combination of diagnostic classifications from ECG and VCG computer interpretations.

The Common Standards for Quantitative Electrocardiography (CSE) study showed that the weighted combined diagnostic classification of a group of experts or a set of electrocardiographic (ECG) programs is superior to the average expert or program, and sometimes even better than the best expert. For that reason the authors investigated whether the combination of classifications from the authors' programs for ECG and vectorcardiographic (VCG) interpretation would deliver better results than either one separately. The CSE diagnostic database (n = 1,220) was used for testing purposes. Since the combination of computer interpretations from the ECG and VCG requires a separate and preferably simultaneous recording of the VCG, the authors also examined the combined interpretation of the ECG with a simulated VCG reconstructed from the eight independent leads of the 12-lead ECG (the rVCG). Besides that, the authors investigated the combined interpretation from all single beats of the dominant waveform from the same ECG recording (sECG). The performance of all combinations, that is, the ECG + VCG, ECG + rVCG, and sECG proved to be significantly better (74.2%, 73.6%, and 71.2%, respectively) than that of the ECG or VCG separately (69.8% and 70.2%, respectively; p < 0.001 for all cases). However, the difference in performance between the sECG and the VCG was not significant.

Cardiology↗
PubMed1992

A standard communications protocol for computerized electrocardiography.

In an international collaborative project aimed at producing common standards for quantitative electrocardiography, a standard communications protocol (SCP-ECG) was developed for computerized electrocardiography. The protocol consisted of standards for the interchange, encoding, and storage of digital ECG data. The work was performed in three distinct, but closely related, work-packages and in close collaboration with representatives from 13 manufacturers of computerized electrocardiographs from all over the world. The objectives and results of SCP-ECG are briefly described in this paper.

Computer Communication Networks↗
PubMed1991

The diagnostic performance of computer programs for the interpretation of electrocardiograms.

BACKGROUND: Computer programs for the interpretation of electrocardiograms (ECGs) are now widely used. However, a systematic assessment of various computer programs for the interpretation of ECGs has not been performed. METHODS: We undertook a large international study to compare the performance of nine electrocardiographic computer programs with that of eight cardiologists in interpreting ECGs in 1220 clinically validated cases of various cardiac disorders. ECGs from the following groups were included in the sample: control patients (n = 382); patients with left ventricular hypertrophy (n = 183), right ventricular hypertrophy (n = 55), or biventricular hypertrophy (n = 53); patients with anterior myocardial infarction (n = 170), inferior myocardial infarction (n = 273), or combined myocardial infarction (n = 73); and patients with combined infarction and hypertrophy (n = 31). The interpretations of the computer programs and the cardiologists were compared with the clinical diagnoses made independently of the ECGs, and the computer interpretations were compared with those of the cardiologists. RESULTS: The percentage of ECGs correctly classified by the computer programs (median, 91.3 percent) was lower than that of the cardiologists (median, 96.0 percent; P less than 0.01). The median sensitivity of the computer programs was also significantly lower than that of the cardiologists in diagnosing left ventricular hypertrophy (56.6 percent vs. 63.9 percent, P less than 0.02), right ventricular hypertrophy (31.8 percent vs. 46.6 percent, P less than 0.01), anterior myocardial infarction (77.1 percent vs. 84.9 percent, P less than 0.001), and inferior myocardial infarction (58.8 percent vs. 71.7 percent, P less than 0.0001). The median total accuracy level (the percentage of correct classifications) was 6.6 percent lower for the computer programs (69.7 percent) than for the cardiologists (76.3 percent; P less than 0.001). However, the performance of the best programs nearly matched that of the most accurate cardiologists. CONCLUSIONS: Our study shows that some but not all computer programs for the interpretation of ECGs perform almost as well as cardiologists in identifying seven major cardiac disorders.

Cardiology↗
PubMed1991

Comparison of computer-aided and human review of general practitioners' management of hypertension.

Computer programs that automatically review decisions can help physicians provide better patient care. In the Netherlands, the ELIAS computer information system has replaced paper medical records in some general practices. We have written a computer program called 'HyperCritic' that audits general practitioners' management of patients with essential hypertension by taking patient-specific data from the ELIAS system. We investigated whether the computer-based medical records contain sufficient information to generate critiques, and compared the limitations of audit by hypercritic with those of review by a panel of eight physicians. Hypercritic and the physicians independently reviewed the medical records of 20 randomly selected patients with hypertension and commented on the decisions made at each of 243 patient visits. Of 468 comments on patient management, 260 were judged correct by six or more of the physicians; hypercritic also made 118 of these 260 comments. The main reasons why the program did not produce the other 142 comments were: insufficient data in the computer-based medical record; absence of sufficient medical consensus; and omissions in the database of hypercritic. Calculation of an "index of merit" ([sensitivity + specificity] - 1) for individual reviewers showed that hypercritic performed better (index of merit 0.62) in its limited domain than did physician reviewers (0.3-0.56). At least in hypertension management, automated review of computer-based medical records compares favourably with review by physicians. Further development of computer-aided clinical audit requires the introduction of computer-based medical records that capture the reasoning of physicians, and of widely accepted practice guidelines.

Adult↗
PubMed1991

DTL: a language to assist cardiologists in improving classification algorithms.

Heuristic classifiers, e.g., for diagnostic classification of the electrocardiogram, can be very complex. The development and refinement of such classifiers is cumbersome and time-consuming. Generally, it requires a computer expert to implement the cardiologist's diagnostic reasoning into computer language. The average cardiologist, however, is not able to verify whether his intentions have been properly realized and perform as he hoped for. But also for the initiated, it often remains obscure how a particular result was reached by a complex classification program. An environment is presented which solves these problems. The environment consists of a language, DTL (Decision Tree Language), that allows cardiologists to express their classification algorithms in a way that is familiar to them, and an interpreter and translator for that language. The considerations in the design of DTL are described and the structure and capabilities of the interpreter and translator are discussed.

Algorithms↗
PubMed1990

Stability of computer ECG amplitude measurements in the presence of noise. The CSE Working Party.

An important feature of an ECG analysis program is its ability to provide reliable measurements under various operating conditions, e.g., on noise-free and noisy ECGs. Therefore, within the European cooperative project "Common Standards For Quantitative Electrocardiography" (CSE), the accuracy and stability of ECG measurements obtained by several computer programs has been compared. To investigate the stability of measurements two sets of 10 ECGs with and without seven different high- and low-frequency types of noise--altogether 160 electrocardiograms and 160 vectorcardiograms--have been analyzed by eight electrocardiographic and five vectorcardiographic computer programs. The stability of measurement was tested with respect to results obtained for the noise-free recordings. In a previous paper, the influence of noise on wave boundary recognition has been reported. In the present paper, the effect of noise on amplitude measurements and on problems of waveform definitions within the QRS complex are described. The results indicate that programs analyzing an averaged beat exhibit less variability than programs which measure every complex or a selected beat. Comparability and stability of measurements could be improved if a standardized procedure for amplitude references were to be introduced. In addition, the stability of QRS waveform labelling could be improved if waveforms' minimum amplitude and duration were to be validated against the noise level which itself should be determined by a standardized procedure.

Analog-Digital Conversion↗
PubMed1990

Reconstruction of the Frank vectorcardiogram from standard electrocardiographic leads: diagnostic comparison of different methods.

Three methods for reconstructing the Frank VCG from the standard 12-lead ECG were studied. The first was based on multivariate regression, the second on a model of the cardio-electrical activity, and the third method used a quasi-orthogonal set of ECG leads. The methods were evaluated on a test set of 90 cases by a numerical distance measure and by the agreement in diagnostic classification of the original and reconstructed VCGs. The original and reconstructed VCGs were presented separately and in random order to three referees. Eighteen of the original VCGs were presented three times to estimate the intra-observer agreement. Kappa statistics were used to quantify the agreement between diagnostic classifications. Separately, one referee was simultaneously presented the original VCG and its three reconstructions for all cases. Each reconstruction VCG was classified as either diagnostically 'same' as the original, 'borderline' or 'different'. The performance of the regression method and the model-based method was comparable. Both methods were preferable to the quasi-orthogonal method. The kappa values for the preferred methods indicated a good to excellent diagnostic agreement between the original and reconstructed VCGs. Only one out of ninety VCGs that were reconstructed with the regression method was classified as 'different' compared with the original VCGs; three VCGs were classified as 'different' with the model-based method. It was also found that estimation of similarity by a distance measure could not replace diagnostic evaluation by skilled observers.

Electrocardiography↗
PubMed1990

Common standards for quantitative electrocardiography: goals and main results. CSE Working Party.

Computer processing of electrocardiograms (ECGs) has over the last 15 years increased rapidly. Still, there are at present no standards for computer ECG interpretation. Different techniques are used not only for measurement and interpretation, but also for transmission and storage of data. In order to fill these gaps, a large international project, sponsored by the European Commission, was launched in 1980 to develop "Common Standards for Quantitative Electrocardiography (CSE)". The main objective of the first CSE study was to reduce the wide variation in wave measurements currently obtained by ECG computer programs. The second study was started in 1985 and aimed at the assessment and improvement of diagnostic classification of ECG interpretation programs. To this end reference libraries of well documented ECGs have been developed and comprehensive reviewing schemes devised for the visual and computer analysis of ECGs. This task was performed by a board of cardiologists in a Delphi review process, and by 9 VCG and 10 standard 12-lead programs developed by university research groups and by industry. A third action was started in June 1989 to harmonize acquisition, encoding, interchange and storing of digital ECG data. The action thus performed have become internationally recognized milestones for the standardization of quantitative electrocardiography.

Algorithms↗
PubMed1990

Evaluation of ECG interpretation systems: signal analysis.

Performance analysis of biosignal processing systems which provide diagnostic statements requires particular care. Besides general accuracy requirements, psychological and legal implications for patient and physician have to be considered on both the development and the user sites. Cybernetics and control engineering have provided the basic methodology for performance analysis of systems: in technical systems often mathematically defined functions and signals can be fed into the system to be tested and its response and output provide the necessary performance characteristics after adequate mathematical analysis. For systems which process biosignals, as for example ECG analysis systems, instead of analytically given signals learning and test sets of data derived from patients have to be applied. The performance analysis is done on a statistical basis. In this paper construction and composition of learning and test data sets as well as methods for performance evaluation of the signal processing part of ECG programs are described. Specific reference is made to the European project Common Standards for Quantitative Electrocardiography (CSE) where ten ECG- and nine VCG-programs have been tested. The results of these tests provide reference data and standards for further program development as well as for independent system performance evaluation.

Electrocardiography↗
PubMed1990

Signal analysis for ECG interpretation.

In ECG interpretation usually two main areas are discerned: the signal analysis and the diagnostic classification. This article reviews the major developments in the first area. ECG signal analysis itself is subdivided into the stages data acquisition, data transformation, feature selection, and data reduction. These stages are consecutively reviewed, while in the data transformation stage digital filtering, detection, wave typing, beat selection, and boundary recognition are discussed.

Algorithms↗
PubMed1990

Classification methods for computerized interpretation of the electrocardiogram.

Two methods for diagnostic classification of the electrocardiogram are described: a heuristic one and a statistical one. In the heuristic approach, the cardiologist provides the knowledge to construct a classifier, usually a decision tree. In the statistical approach, probability densities of diagnostic features are estimated from a learning set of ECGs and multivariate techniques are used to attain diagnostic classification. The relative merits of both approaches with respect to criteria selection, comprehensibility, flexibility, combined diseases, and performance are described. Optimization of heuristic classifiers is discussed. It is concluded that heuristic classifiers are more comprehensible than statistical ones; encounter less difficulties in dealing with combined categories; are flexible in the sense that new categories may readily be added or that existing ones may be refined stepwise. Statistical classifiers, on the other hand, are more easily adapted to another operating environment and require less involvement of cardiologists. Further research is needed to establish differences in performance between both methods. In relation to performance testing the issue is raised whether the ECG should be classified using as much prior information as possible, or whether it should be classified on itself, explicitly discarding information other than age and sex, while only afterwards other information will be used to reach a final diagnosis. Consequences of taking one of both positions are discussed.

Algorithms↗
PubMed1990

Methodology of the modular ECG analysis system MEANS.

The methodology, used in the Modular ECG Analysis System (MEANS) is described. MEANS consists of modules for signal analysis and diagnostic classification. The basic structure of the modular interpretation system remained intact over a period of 20 years, while all modules underwent many changes as a function of experience and insight, and the continuously changing information technology. The article describes the advantages of a modular approach to decision-support systems, the most important ones being easier maintenance of the software package and separate optimization and testing of each module. The overall evaluation of MEANS was done in the CSE study. Evaluation results for modules and for the entire system are presented.

Diagnosis, Computer-Assisted↗
PubMed1990

Rationale for a community strategy in the field of information and communications technologies applied to health care.

The challenge for Europe in the field of information and communications technologies applied to health care is that of addressing positively the problem of the widening gap between the expectations of the citizens of the type of care that can be made available and the limited resources to provide that care. If the expectations of the population are to be fulfilled, it will be necessary to find innovative ways of delivering health services and to do it more efficiently than has yet been the case. Advanced information and communications technologies will be important tools for Member States to achieve the levels of efficiency required. Based on the results of the Community AIM Exploratory Action, further collaborative work is required at EEC level to create an Integrated Health Information Environment (IHE) allowing essentially for integration, modularity and security.

Europe↗