bluuebunny/crossref_metadata_2025_split huggingface dataset:
CSI-ISC
Authors: Wolff A. C. , Kutscha U. , Wetter T. , Knaup P. , Garde S. 
Published: March 2018

Summary

Objectives:
The introduction of information system components (ISCs) usually leads to a change in existing processes, e.g. processes of patient care. These processes might become even more complex and variable than before. An early participation of end users and a better understanding of human factors during design and introduction of ISCs are key factors for a successful introduction of ISCs in health care. Nonetheless no specialized methods have been developed until now to systematically support the integration of ISCs in existing processes of patient care while taking into account these requirements. In this paper, therefore, we introduce a procedure model to implement Concepts for Smooth Integration of ISCs (CSI-ISC).

Methods:
Established theories from economics and social sciences have been applied in our model, among them the stress-strain-concept, the contrastive task analysis (KABA), and the phase model for the management of information systems.

Results:
CSI-ISC is based on the fact that while introducing new information system components, users experience additional workload. One essential aim during the introduction process therefore should be to systematically identify, prioritize and ameliorate workloads that are being imposed on human beings by information technology in health care. To support this, CSI-ISC consists of a static part (workload framework) and a dynamic part (guideline for the introduction of information system components into existing processes of patient care).

Conclusions:
The application of CSI-ISC offers the potential to minimize additional workload caused by information system components systematically. CSI-ISC rationalizes decisions and supports the integration of the information system component into existing processes of patient care.
Investigation on the Improvement of Prediction by Bootstrap Model Averaging
Authors: Augustin N. H. , Sauerbrei W. , Holländer N. 
Published: March 2018

Summary

Objectives:
We illustrate a recently proposed two-step bootstrap model averaging (bootstrap MA) approach to cope with model selection uncertainty. The predictive performance is investigated in an example and in a simulation study. Results are compared to those derived from other model selection methods.

Methods:
In the framework of the linear regression model we use the two-step bootstrap MA, which consists of a screening step to eliminate covariates thought to have no influence on the response, and a model-averaging step. We also apply the full model, variable selection using backward elimination based on Akaike’s Information Criterion (AIC), the Bayes Information Criterion (BIC) and the bagging approach. The predictive performance is measured by the mean squared error (MSE) and the coverage of confidence intervals for the true response.

Results:
We obtained similar results for all approaches in the example. In the simulation the MSE was reduced by all approaches in comparison to the full model. The smallest values are obtained for bootstrap MA. Only the bootstrap MA and the full model correctly estimated the nominal coverage. The backward elimination procedures led to substantial underestimation and bagging to an overestimation of the true coverage. The screening step of bootstrap MA eliminates most of the unimportant factors.

Conclusion:
The new bootstrap MA approach shows promising results for predictive performance. It increases practical usefulness by eliminating unimportant factors in the screening step.
Same Systems, Different Outcomes
Authors: Berg M. , Aarts J. 
Published: March 2018

Summary

Objectives:
To compare the outcome of the implementation of computerized physician order entry (CPOE) systems in two Dutch hospitals.

Methods:
Qualitative research methods, including interviews in both hospitals, observations of system in use, observations of staff meetings and document analysis were used to understand the implementation of CPOE. The transcribed texts and implementation documents were analyzed for relevant concepts.The transcripts and field notes were analyzed using a heuristic success and failure model with medical work as the primary focus.

Results:
Occasions that determined the outcome of the implementation were classified according to factors that may influence the success or failure of implementing systems.

Conclusions:
The themes and patterns that emerged from the data helped validate the concept of medical work as the primary focus of our analysis model; in addition the concept of a support base necessary to accept changes in medical work that result from introducing CPOE may help to understand the different implementation outcomes.
Pre-operative Dynamic Interactive Exploration of Complex Articular Fractures Using a Novel 3D Navigation Tool
Authors: Teistler M. , Bott O. J. , Stuermer K. M. , Pretschner D. P. , Dresing K. , Marschollek M. 
Published: March 2018

Summary

Objectives:
Trauma surgeons possess specific anticipative pathoanatomical and procedural domain knowledge that can be used for information extraction from original CT image data. This knowledge so far remains unused in clinical workflow and surgeons do not take an active part in the process of image generation and processing. The objectives of our work are to propose and employ a strategy to directly involve surgeons in a dynamic image exploration process and to exemplarily assess the clinical use of this appoach for pre-operative diagnosis of complex articular fractures.

Methods:
We used an interactive 3D navigation tool with a novel human-computer interface for the exploration of articular fractures of two selected anatomical structures. The system offers dynamic interaction with a virtual 3D reconstruction model and the possibility to create on-the-fly oblique multiplanar reformations by tracking hand movements. Three expert surgeons performed exemplary explorations and rated the use of the method for preoperative diagnosis in informal interviews.

Results:
The approach and the system were well received by the three surgeons. The dynamic interaction was rated to be helpful in understanding fracture morphology. Two examples – a radius and a calcaneal fracture – are presented.

Conclusions:
Surgeons with their specific domain knowledge should be involved in the process of image processing. The benefit of using oblique multiplanar reformations for pre-operative planning in articular fractures appears to be substantial and they should therefore be included in radiological and surgical textbooks. Further evaluation is necessary to assess the use of interactive exploration systems in routine diagnosis.
Practical Considerations on the Use of Extreme Sib-pairs for Obesity
Authors: Barth N. , Coners H. , Mayer H. , Hebebrand J. , Ziegler A. 
Published: March 2018

Summary

Objectives:
The extreme sib-pair approach has been shown to be a powerful strategy to identify susceptibility loci linked to quantitative traits. The body mass index is the usually assessed trait in genetic studies on human obesity. Environmental factors clearly play an important role for this trait. We hypothesized that the low weight of most sibs who were seemingly discordant to the obese index proband was influenced by other environmental and/or genetic factors like restrained eating or psychiatric disorders.

Methods:
A screening questionnaire was sent to parents of all consecutively admitted patients three weeks prior to referral of index probands for inpatient treatment of obesity. The first 320 families were further investigated. Twenty-seven seemingly extremely discordant sib-pairs (ED) were identified and examined in detail.

Results:
The low weight of most sibs who were seemingly discordant to the obese index proband was influenced by factors like restrained eating or psychiatric disorders. Only 20% of the interviewed ED could be considered as genuine ED.

Conclusion:
We conclude that extensive medical evaluation is necessary if the aim is to guarantee genuine ED in family studies for human obesity. Non-paternity deserves specific attention in ED studies.
Computed Critiquing Integrated into Daily Clinical Practice Affects Physicians’ Behavior
Authors: Kuilboer M. M. , Mosseveld M. , van der Does E. , de Jongste J. C. , Overbeek S. E. , Ponsioen B. , van der Lei J. , van Wijk M. A. M. 
Published: March 2018

Summary

Objective:
We developed AsthmaCritic, a non-inquisitive critiquing system integrated with the general practitioners’ electronic medical records. The system is based on the guidelines for asthma and chronic obstructive pulmonary disease (COPD) as issued by the Dutch College of General Practitioners. This paper assesses the effect of AsthmaCritic on monitoring and treatment of asthma and COPD by Dutch general practitioners in daily practice.

Methods:
A randomized clinical trial in 32 practices (40 Dutch general practitioners) using electronic patient records. An intervention group was given the use of AsthmaCritic, a control group continued working in the usual manner. Both groups had the disposal of the asthma and COPD guidelines routinely distributed by the Dutch College of General Practitioners. We measured the average number of contacts, FEV1 (forced ex-piratory volume), and peak-flow measurements per asthma/COPD patient per practice; and, the average number of antihistamine, cromoglycate, deptropine, and oral bronchodilator prescriptions per asthma/COPD patient per practice.

Results:
The number of contacts increased in the age group of 12-39 years. The number of FEV1, peak-flow measurements, and the ratio of coded measurements increased, whereas the number of cromoglycate prescriptions decreased in the age group of 12-39 years.

Conclusions:
Our study shows that the guideline-based critiquing system AsthmaCritic changed the manner in which the physicians monitored their patients and, to a lesser extent, their treatment behavior. In addition, the physicians changed their data-recording habits.
A Rational Request Behavior: The Development of Prediction Instruments regarding Thyroid Function Tests in Primary Care
Authors: Pop P. , Hasman A. , Schouten H. J. A. , Dupuits F. M. H. M. 
Published: March 2018

Abstract:A prospective study was performed to encourage a rational thyroid-stimulating hormone (TSH) test request behavior of physicians, using prediction instruments. The latter give direct feedback about request adequacy on the basis of pretest probabilities of hyperthyroidism using patients’ signs and symptoms. For instrument design, stepwise logistic regression was used on diagnostic data acquired through questionnaires, answered by 80 physicians and 668 patients for whom physicians requested a TSH test. Instruments were designed for clinical and subclinical hyperthyroidism and for clinical hyperthyroidism alone. Use of the instrument for clinical or subclinical hyperthyroidism on the selected group, at a 5% probability threshold, can result in a 37% reduction of unnecessary TSH test requests. With the instrument for clinical hyperthyroidism at a 5% probability threshold, the number of unnecessary test requests can be reduced by 57%. Therefore, it can be concluded that the instruments can determine TSH test request adequacy and encourage a rational TSH test request behavior of physicians at low pretest probability thresholds.
Functional Requirements for a HIS-RIS-PACS-Interface Design, Including Integration of “Old” Modalities
Authors: Nissen-Meyer S. , Pistitsch C. , Fink U. , Reiser M. , Adelhard K. 
Published: March 2018

Abstract:Radiology, Information Systems (RIS) and Picture Archiving Systems (PACS), have the potential for immense rationalization of operations in radiology and hence for the improvement of health care, as well as the return of investments. These systems must, however, be carefully designed such that they support routine work rather than being an additional burden to radiology staff. Analyses show that comprehensive communication of patient demographic and clinical data between RIS, PACS and Hospital Information Systems (HIS) are necessary prerequisites to achieve cost effectiveness. Based on analyses of radiology operations in a large university primary care hospital, functional requirements and data structures for designing HIS/RIS/PACS interfaces are presented. These concern communication of past examinations, associated written reports and images, appointment scheduling, requests of new examinations, digitizing old analog X-ray films, access from RIS/PACS to other clinical data, and transfer of new radiology reports and relevant images. Consistency of all redundant data stored in the three systems is essential. A pragmatic, safe and inexpensive method of electronically integrating “old” modalities not fully ”PACS capable“ in the HIS/RIS/PACS world is presented.
A Review of Database Management Systems Suitable for Neuroimaging
Authors: Diallo B. , Travere J.-M. , Mazoyer B. 
Published: March 2018

AbstractThis study comprises a technical assessment of Database Management Systems (DBMS), which may be of use in the analysis of data obtained from human brain mapping procedures. Due to the large expansion of the neuroimaging field, the use of specialized database software to store and process neuroimages and their attached components is inevitable. The advent of multiple software products, a wealth of technical terms and a wide variety of other applications make the choice of a suitable program sometimes difficult. Through the inclusion of some basic and pertinent criteria (e.g., performance, ease of opening, standardization and portability), we present a descriptive comparison of 12 DBMSs currently available in the commercial and public domain. We have compared and tested three main architecture models which are currently available and assessed their potential applications for imaging purposes: relational, object-oriented, and hybrid. The findings of our study demonstrated that the Illustra&#8482; software was the best suited for a neuroimaging environment because of its intrinsic ability to handle complex and large objects, such as 3D volumes or geometric structures.
A Multistate Kalman Filter for Neonatal Clotting Time Prediction and Early Detection of Coagulation Disturbances
Authors: van der Velde J. , Geven W. B. , Festen C. , Verbeek A. L. M. , de Haan A. F. J. 
Published: March 2018

AbstractThe multistate Kalman filter was applied to develop a heparin dose proposal system and to detect coagulation disturbances during neonatal extracorporeal membrane oxygenation (ECMO). A system containing this filter was based on the activated clotting time (ACT) values and the heparin doses administered every hour during ECMO. If the ACT value can be predicted accurately from the previous heparin dose, a heparin dose proposal can be given to achieve or maintain the required ACT level. The analysis was done on 6,356 ACT level measurements in 44 ECMO neonates. The multistate Kalman filter technique showed an unbiased prediction of ACT, with a standard deviation of 23 seconds. Two out of three cases of disseminated intravascular coagulation (DIC) were detected. ACT values were predicted sufficiently accurately by the multistate Kalman filter technique to justify a prospective study on the performance of the heparin dose proposal system and its ability to detect DIC.
A Generic Model of Clinical Practice
Authors: Dietz J. L. G. , Hasman A. , de Vries Robbé P. F. , Tange H. J. 
Published: March 2018

Summary
Objectives: Many shared-care projects feel the need for electronic patient-record (EPR) systems. In absence of practical experiences from paper record keeping, a theoretical model is the only reference for the design of these systems. In this article, we review existing models of individual clinical practice and integrate their useful elements. We then present a generic model of clinical practice that is applicable to both individual and collaborative clinical practice.
Methods: We followed the principles of the conversation-for-action theory and the DEMO method. According to these principles, information can only be generated by a conversation between two actors. An actor is a role that can be played by one or more human subjects, so the model does not distinguish between inter-individual and intra-individual conversations.
Results: Clinical practice has been divided into four actors: service provider, problem solver, coordinator, and worker. Each actor represents a level of clinical responsibility. Any information in the patient record is the result of a conversation between two of these actors. Connecting different conversations to one another can create a process view with meta-information about the rationale of clinical practice. Such process view can be implemented as an extension to the EPR.
Conclusions: The model has the potential to cover all professional activities, but needs to be further validated. The model can serve as a theoretical basis for the design of EPR-systems for shared care, but a successful EPR-system needs more than just a theoretical model.
Entering the Black Box of Neural Networks
Authors: Gerber B. S. , Tape T. G. , Wigton R. S. , Heckerling P. S. 
Published: March 2018

Summary
Objectives: Artificial neural networks have proved to be accurate predictive instruments in several medical domains, but have been criticized for failing to specify the information upon which their predictions are based. We used methods of relevance analysis and sensitivity analysis to determine the most important predictor variables for a validated neural network for community-acquired pneumonia.
Methods: We studied a feed-forward, back-propagation neural network trained to predict pneumonia among patients presenting to an emergency department with fever or respiratory complaints. We used the methods of full retraining, weight elimination, constant substitution, linear substitution, and data permutation to identify a consensus set of important demographic, symptom, sign, and comorbidity predictors that influenced network output for pneumonia. We compared predictors identified by these methods to those identified by a weight propagation analysis based on the matrices of the network, and by logistic regression.
Results: Predictors identified by these methods were clinically plausible, and were concordant with those identified by weight analysis, and by logistic regression using the same data. The methods were highly correlated in network error, and led to variable sets with errors below bootstrap 95% confidence intervals for networks with similar numbers of inputs. Scores for variable relevance tended to be higher with methods that precluded network retraining (weight elimination) or that permuted variable values (data permutation), compared with methods that permitted retraining (full retraining) or that approximated its effects (constant and linear substitution).
Conclusion: Methods of relevance analysis and sensitivity analysis are useful for identifying important predictor variables used by artificial neural networks.
The Index as a New Concept towards an Integrated Framework for the Electronic Patient Record
Authors: Clercq De 
Published: March 2018

Summary
Objective: To overcome some classical limitations of the POMR (Problem-Oriented Medical Record), including the management of divergent opinions between health professionals, in order to construct a common patient record across multiple disciplines in hospital settings and professional networks.
Methods: Using a complex clinical case, we improved a POMR model previously used by GPs in order to translate it into a hospital setting. The enhanced model has been assessed through use in various ongoing clinical cases and through extended discussion with professional end-users (physicians, nurses, general practitioners, and social workers).
Results: The Index concept (flexible structural link) is proposed as a major improvement in the construction of a POMR in a shared care environment.
Conclusions: The Index introduces interesting new perspectives. Following its implementation in the Belgian pilot site in the CORINES project, further studies remain to be carried out in order to develop a cost/benefit assessment.
Discrete Event Simulation in the Health Policy and Management Program
Authors: Groothuis S. , Merode van 
Published: March 2018

Abstract:Students in Health Policy and Management at the Faculty of Health Sciences of Maastricht University must learn to analyze and design workflow processes in health care. To attain this, a discrete event simulation training, using MedModel™ is used. This paper describes the training in two consecutive years. In both years the training was evaluated systematically. The evaluation results demonstrate that the simulation training increased the students’ knowledge about analyzing and designing workflow processes in healthcare. Students considered the training as a very important part of their program.
High Speed Digital Circuits for Medical Communication; the MINCS-UH Project
Authors: Takahashi T. , Kiuchi T. 
Published: March 2018

Abstract:In Japan, a high speed, bidirectional digital satellite communication system called Medical Information Network by Communications Satellite for University Hospitals is currently available in 30 national universities, and many programs, including clinical conferences, lectures and tutorials, have been broadcasted. Its characteristics are: (1) a state-of-the-art digital high-definition television system, (2) excellent security protection using digital encryption (3) bidirectional communications using two satellite circuits simultaneously, and (4) easy operability. High-quality motion images, and security protection mechanisms are essential for use in clinical medicine.
A Data Mining System for Infection Control Surveillance
Authors: Brossette S. E. , Sprague A. P. , Jones W. T. , Moser S. A. 
Published: March 2018

Abstract:Nosocomial infections and antimicrobial resistance are problems of enormous magnitude that impact the morbidity and mortality of hospitalized patients as well as their cost of care. The Data Mining Surveillance System (DMSS) uses novel data mining techniques to discover unsuspected, useful patterns of nosocomial infections and antimicrobial resistance from the analysis of hospital laboratory data. This report details a mature version of DMSS as well as an experiment in which DMSS was used to analyze all inpatient culture data, collected over 15 months at the University of Alabama at Birmingham Hospital.
Robust Outcome Prediction for Intensive-Care Patients
Authors: Sebastiani P. , Dybowski R. , Ramoni M. 
Published: March 2018

AbstractMissing data are a major plague of medical databases in general, and of Intensive Care Unit databases in particular. The time pressure of work in an Intensive Care Unit pushes the physicians to omit randomly or selectively record data. These different omission strategies give rise to different patterns of missing data and the recommended approach of completing the database using median imputation and fitting a logistic regression model can lead to significant biases. This paper applies a new classification method, called robust Bayes classifier, which does not rely on any particular assumption about the pattern of missing data and compares it to the median imputation approach using a database of 324 Intensive Care Unit patients.