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Biomedical subjects

A Hasman

Publications and source records attributed to A Hasman.

At least 55 records · Page 3Linked to original sources
PubMed2001

Design of a consumer health record for supporting the patient-centered management of chronic diseases.

This paper describes and discusses the design and usage of a shareable consumer health record system to investigate whether these systems can assist in the management of chronic diseases. This web-based system that can be used both by care providers and patients contains medical and patient information, provides access to websites that contain quality information, provides guideline-based advice, allows discussion between patients and allows us to interrogate both patients and care providers on a regular basis in order to get a good impression of the utility of such a consumer record for both chronic patients and the physicians and nurses. A health record system that was developed for the area of Diabetes is presented as an example.

Chronic Disease↗
PubMed2000

Reduction of noise in medullary renograms from dynamic MR images.

Dynamic magnetic resonance images of the kidney can be used to acquire separate renograms of the cortex and medulla. A high-quality cortical renogram can be determined directly from a region of interest (ROI) placed in the cortex. Due to partial volume effects, part of the signal from a ROI placed in the medulla is caused by cortical tissue. By subtracting a fraction of the cortical signal from the cortico-medullary signal, a purer medullary renogram can be obtained. A side effect of this subtraction is an increase in noise level. The noise level increases with larger partial volume fractions. Using a matched image filter, it is possible to exclude those areas from the ROI that have a high partial volume content, thus reducing the amount of cortical signal that has to be separated from the medullary signal. Noise reductions of up to 50% have been achieved in the medullary renogram, with an average reduction of 23%.

Contrast Media↗
PubMed2000

MR renography: an algorithm for calculation and correction of cortical volume averaging in medullary renographs.

We evaluated a mathematical algorithm for the generation of medullary signal from raw dynamic magnetic resonance (MR) data. Five healthy volunteers were studied. MR examination consisted of a run of 100 T1-weighted coronal scans (gradient echo; TR/TE 11/3.4 msec, flip angle 60 degrees; slice thickness 6 mm; temporal resolution 2 seconds). Gadolinium-diethylene triamine pentaacetic acid (DTPA; 0. 05 mmol/kg) was injected with an injector pump (5 ml/sec). Medullary MR renographs (MRRs) were calculated for regions of interest with strong and moderate cortical volume averaging (CVA). A reference medullary MRR, devoid of CVA, was obtained. Percentual signal differences between calculated and reference medullary MRRs were estimated for each consecutive scan. Run averaged values of these differences were calculated. Mean values, after subtraction of the resting state signal, were +0.2% (SD 9.7%) and +0.7% (SD 9.0%) for areas with strong and moderate CVA, respectively. We conclude that with this algorithm reliable extraction of medullary MRRs is feasible, providing a unique tool for clinical evaluation of medullary disease. J. Magn. Reson. Imaging 2000;12:453-459.

Adult↗
PubMed2000

Supporting the classification of pathology reports: comparing two information retrieval methods.

In this contribution two methods from the domain of information retrieval are compared. The goal of the retrieval is to select from a library of pathology reports those ones that are most similar to a given report. The SNOMED codes that accompany these reports are presented to the pathologist who has to code the given report with the aim to improve the quality of coding. The reports were represented either as a vector of words or as a vector of N-grams. Both 4-, 5- and 6-grams were used. The similarity of the reports was determined by comparing the SNOMED terms that were added to the reports. It could be concluded that the word-based method was consistently better than the N-gram method.

Databases, Factual↗
PubMed2000

Editorial

Explore the source record for details and available documents.

Journal Article↗
PubMed2000

An experimental electronic patient record for stroke patients. Part 1: situation analysis.

In this article the paper record and its position in work practices is discussed, and is related to the situation at an inpatient clinic for which an electronic patient record (EPR) is in development. In addition reported research on innovations is discussed. An analysis of 42 clinical paper records gave insight into existing problems with paper records. The current work practices were analysed based on two periods of observations in the ward and eight in-depth interviews with questions about their daily work, communication in the ward and the role of the paper record in communication. The results indicate that several problems described in the literature were recognised only for a part of the medical and nursing records. One probable cause of insufficient communication between health care workers appeared to be the internal organisation of the paper records. The fact that the experimental EPR system will be small-scaled, introduces specific problems regarding communication with other departments that still work with paper records. Nevertheless, we conclude that also an electronic patient record designed for a specific setting has the potential to improve record keeping and communication between health care workers.

Decision Support Systems, Clinical↗
PubMed2000

An experimental electronic patient record for stroke patients. Part 2: system description.

This article presents an electronic patient record (EPR) for stroke patients. At the neurology department of the Maastricht University Hospital, coordination and communication of the multidisciplinary team for stroke patients is intended to be supported by an EPR. Existing, structured, paper nursing and medical records served as a starting point for the development of the EPR. In close cooperation with future users, the database structure, and data entry and data retrieval aspects of the user interface were adapted to the domain of stroke. The result is a combined electronic medical and nursing record that has potential to improve record keeping and to truly support daily routines. The challenges encountered in the development process were maintaining continuous user involvement and conflicting points of view regarding the relevance of clinical data. Conclusively, we state that intensive user participation improved the EPR, coupling with the existing hospital information system and other systems will be advantageous and the fact that the paper records were structured in advance will smooth the unavoidable changes in work patterns.

Decision Support Systems, Clinical↗
PubMed2000

A test ordering system with automated reminders for primary care based on practice guidelines.

In this article we describe a real-time automated reminder system that has been developed to change Family Physicians' (FP) test ordering behavior. The system focuses on the appropriateness of test requests. We aim at using the system as a substitute for written feedback by human experts. The reminder system consists of a knowledge base, an order entry system and modules to provide passive and active support in the form of reminders to FPs. The system generates critical comments about the rationality of the test requests at the moment the FP orders a test that is not in line with national or regional guidelines. For the first validation of the knowledge base we compared the comments of a human expert to the comments of the reminder system on three random samples of test requests. The overall agreement in the subsequent validation rounds was 46, 60 and 69%. The corrections made in the knowledge base after each validation round resulted in a reminder system with 149 reminders concerning various medical problems. Due to the corrections in the knowledge base the reminder system reacts better over the subsequent validation rounds.

Diagnostic Tests, Routine↗
PubMed2000

Development of the Nursing Minimum Data Set for the Netherlands (NMDSN): identification of categories and items.

Development of the Nursing Minimum Data Set for the Netherlands (NMDSN): identification of categories and items Rationale Currently, there is no systematic collection of nursing care data in the Netherlands, while pressure is growing from the profession, policy-makers and society to justify the contribution of nursing and its costs. A nursing minimum data set can provide data to demonstrate nursing's contribution to health care as it can be used to describe the diversity of different patient populations and the variability of nursing activities, and to calculate the associated nursing workload. Objective To identify categories and items for inclusion in the Nursing Minimum Data Set for the Netherlands. Design A multimethod, exploratory approach was used. This included interviews, document analysis, consensus rounds, seeking validation in the literature, and drawing up lists of most frequently occurring patient problems, interventions and outcomes of care. Eight hospitals, with a total of 16 wards, participated in the study. Results Relevant categories and items emerged after analysis and grouping of the material and included: five hospital-related items, six patient demographics items, seven medical condition items, 10 nursing process items, 24 patient problems, 32 nursing interventions, four outcomes of nursing care, and three complexity of care items. Almost every item could be located in the existing documentation systems, the lists of patient problems, outcomes and interventions, or in the literature. Conclusion A set of categories and items of nursing data has been identified. The content validity of this set is partly supported by its consistency with the literature, findings from practice and the judgement of potential users. Nursing outcomes need further development. The data set will be tested in practice to find out whether the categories and items are useful, and whether they can be minimized.

Attitude of Health Personnel↗
PubMed2000

Problem-based education and health informatics.

In this contribution the traditional approach to education is presented and compared with the problem-based approach. Trends in the healthcare system indicate that education in health informatics and training in ICT becomes mandatory for students and healthcare professionals. These trends are presented. In addition the role of ICT in education and training is discussed. Finally some educational programs are presented.

Education↗
PubMed2000

Thoughts about curricula in health informatics.

In this contribution it is argued that it is difficult to talk of medical informatics education since the groups that need education in this field are not very homogeneous. Also these groups overlap. WG 1 of IMIA is in the process of producing recommendations for curricula in medical informatics. The target groups are defined by their career type, which is categorised using three axes: discipline, stage of career and level of expertise. An example is given of the knowledge requirements for medical students.

Career Choice↗
PubMed2000

The user in the design process of an EPR.

To optimise the development and implementation process of an electronic patient record, attitudes toward computers in health care and satisfaction with paper records of nurses and physicians of a department in an academic hospital were determined. For this purpose participants received two questionnaires. These results were supplemented with eight semi-structured in-depth interviews. Users who considered themselves as experienced computer users had more positive attitudes. Inexperienced users were more satisfied with the nursing paper record, while no significant differences existed for the paper medical record.

Attitude to Computers↗
PubMed2000

Comparing assessment of appropriateness of diagnostic tests between a human expert and an automated reminder system.

This paper describes the validation of the GRIF automated reminder system. The reminder system has been developed to influence diagnostic test ordering of General Practitioners (GPs). It generates critical comments on the basis of accepted guidelines. A retrospective random selection of 253 request forms has been taken. We compared the comments of a human expert to the comments of the reminder system. A panel of two independent reviewers judged the requested tests based on the strict interpretation of the guidelines. The sensitivity, specificity and 'predictive values' of the comments of the reminder system and the human expert were calculated using the judgement of the two reviewers as 'gold standard'.

Artificial Intelligence↗
PubMed1999

Validating a decision support system for anti-epileptic drug treatment. Part I: initiating anti-epileptic drug treatment.

In this contribution the validation of a prototype decision support system that implements a model of expertise for initiating anti-epileptic drug treatment is described. Since domain experts were of the opinion that prescribing was a rather straightforward process we used only one expert neurologist for knowledge elicitation. To determine the correctness of the system we intended to compare the contents of the system's prescriptions with the majority decision of three neurologists. Because of a large variation in prescribing a majority decision could not be obtained in many cases. Even a Delphi procedure did not yield a majority decision in a large number of cases. Therefore a consensus meeting was organised to discuss cases where discrepancies remained. In the process the participating neurologists formulated prescription guidelines. These guidelines were used as a reference to determine the correctness of the prescriptions of both the system and of the neurologists. The acceptability of all prescriptions for each case was rated by the two neurologists who did not write a prescription for that case. From both comparisons it could be concluded that the system was at least as good in prescribing as individual neurologists.

Adolescent↗
PubMed1999

Validating a decision support system for anti-epileptic drug treatment. Part II: adjusting anti-epileptic drug treatment.

A model of expertise for monitoring antiepileptic drug treatment was implemented in a decision support system. We validated the advice of the system regarding treatment decisions at first follow-up with 265 paper cases based on patient records. The reference for comparison is based on the opinions of neurologists. We found considerable variation among the decisions of five neurologists. It could be shown that the system agreed with (groups of) neurologists at least as often as individual neurologists did. The correctness of the system was consistently higher than that of each of the neurologists, when the majority decision of the remaining neurologists constituted the standard.

Anticonvulsants↗
PubMed1999

A strategy for developing practice guidelines for the ICU using automated knowledge acquisition techniques.

OBJECTIVES: To implement practice guideline entry tools in a reminder system in order to provide decision support to health care workers in clinical care and emergency care environments. To design a knowledge acquisition environment that enables physicians to formulate, update, and verify guidelines without the assistance of a knowledge engineer. METHODS: We developed a knowledge acquisition environment for the Intensive Care Unit (ICU) consisting of 1) a graphical knowledge acquisition tool, 2) tools that perform logical and semantic tests on proposed guidelines, 3) a Patient Data Management System (PDMS) containing clinical patient data, and 4) an expert system that reminds ICU health care workers of inconsistencies between a treatment plan and implemented guidelines. Physicians enter the guidelines using the knowledge acquisition tool, after which consistency and correctness tests are performed on the guidelines. The guidelines are then transferred to the knowledge base of the reminder system and validated by applying the new guidelines to a large stored data set of previous patients. If the new guidelines are approved, they are exported to the reminder system that is used in daily practice. RESULTS: ICU physicians used the knowledge acquisition tool to enter 58 guidelines into the reminder system's knowledge base. These guidelines were tested on a data set consisting of 803 previously admitted patients. As a result, 27 guidelines fired at least once, generating 406 reminders in total. Of the 406 generated reminders, 356 (88%) were issued correctly and 50 (12%) were false alarms. The reminders that were issued correctly involved 3 situations: 1) the database contained inconsistent or incomplete information, 2) the actions or decisions of the health care workers were not the most appropriate ones, and 3) there was a potential risk involved. All false alarms were caused by the fact that the corresponding guidelines were not specific enough to handle certain exceptions. As a result of this analysis, the guidelines could be improved in such a way as to eliminate all false alarms. CONCLUSIONS: These first results demonstrate that this bottom-up knowledge acquisition strategy, implemented by the automated knowledge acquisition tools, enables medical specialists to improve the quality of computer support in an ICU without assistance of a knowledge engineer.

Artificial Intelligence↗