Thesis (Ph. D.)--University of Missouri--Columbia, 2002. / "May 2002." Typescript. Vita. Includes bibliographical references (leaves 104-114).

Thesis (M. Sc.)--University of Alberta, 1997. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M. Sc.)--University of Alberta, 1997. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--University of Missouri-Columbia, 2005. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Vita. "July 2005." Includes bibliographical references.

Thesis (Ph. D.)--University of Missouri--Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 104-114).

Diss. (sammanfattning) Stockholm : Karolinska institutet, 2007. / Härtill 4 uppsatser.

Les Technologies de l’Information en Santé (TIS) sont de plus en plus utilisées pour améliorer la qualité des soins et la sécurité du patient. Cependant, certains problèmes d’utilisabilité peuvent amenuiser leur impact et peuvent même induire de nouveaux problèmes dont la mise en danger du patient. Pour éviter ces effets négatifs, il est notamment nécessaire d’améliorer l’utilisabilité des TIS ce qui requiert l’application de connaissances d’utilisabilité éprouvées. Les connaissances en utilisabilité appliquée aux TIS sont rares, éparpillées à travers diverses supports et peu utilisables. Par ailleurs, leur couverture en termes de problèmes d’utilisabilité est peu connue. Ce travail a deux objectifs: (i) participer à l’amélioration de l’accumulation de la connaissance en utilisabilité pour les TIS, (ii) fournir une connaissance structurée sur l’utilisabilité des TIS et dont la couverture est établie. Le domaine d’application est celui des systèmes d’alerte médicamenteux.Méthode. Deux analyses indépendantes de la littérature ont été menées : d’un côté, identifier et organiser les problèmes d’utilisabilité des systèmes d’alerte médicamenteux ainsi que leurs conséquences ; de l’autre, identifier et synthétiser les principes d’utilisabilité spécifiques à ces systèmes. Les résultats de ces analyses ont été croisés afin de connaitre la couverture desdits principes en termes de problèmes d’utilisabilité.Résultats. La revue systématique a identifié 13 types de problèmes d’utilisabilité dans les systèmes d’alerte médicamenteux. Les conséquences de ces problèmes sur le clinicien et son système de travail sont variées et ont un grand pouvoir de nuisance (e.g., fatigue, erreur d’interprétation). Au total, 63 principes d’utilisabilité permettent de rendre compte de tous les problèmes d’utilisabilité identifiés. Ils sont organisés en 6 thèmes : améliorer le ratio signal-bruit, être en adéquation avec l’activité des cliniciens, supporter le travail collaboratif, afficher les informations pertinentes, rendre le système transparent et fournir des outils utiles. Le croisement des deux ensembles de données révèle une bonne correspondance entre les principes d’utilisabilité énoncés et les problèmes d’utilisabilité réellement observés.Discussion. Une liste structurée des principes d’utilisabilité illustrés par des exemples réels de leur violation a été développée à partir de ce travail. Cette liste peut aider les concepteurs et les experts en Facteurs Humains à comprendre et à appliquer les principes d’utilisabilité durant la conception et l’évaluation de systèmes d’alerte médicamenteux. L’utilisabilité appliquée aux TIS est une discipline relativement récente qui souffre d’un déficit de structuration et de capitalisation de ses connaissances. Ce travail montre qu’il est possible d’accumuler et de structurer les données d’utilisabilité des TIS. Ce travail pourrait être poursuivi en développant une base de connaissance en utilisabilité appliquée aux TIS afin de tendre vers une « utilisabilité fondée sur les preuves ». / Health Information Technology (HIT) is increasingly implemented to improve healthcare quality and patient safety. However, some usability issues may reduce their impact and even induce new problems (including patient safety issues). To avoid those negative outcomes, amongst other actions, HIT usability must be improved. This action requires applying validated usability knowledge. However, usability knowledge applied to HIT is scattered across several sources, is not structured and is hardly usable. Moreover, its coverage regarding related usability flaws is not known. This work has two aims: (i) to participate in improving the accumulation of usability knowledge for HIT and (ii) to provide synthetic structured easy-to-use HIT usability knowledge with a clear coverage. Those aims are applied to medication alerting systems.Method.Two independent analyses of the literature have been performed. On the one hand, usability flaws and their consequences for the clinicians and the work system have been searched and organized; on the other hand, existing usability design principles specific to medication alerting systems have been synthesized. Results of both analyses have been matched together. Results.A systematic review identified 13 types of usability flaws in medication alerting systems. Consequences on the clinicians and the work system are varied: they greatly impede the clinicians and negatively impact the work system (e.g., alert fatigue, alert misinterpretation). Sixty-three usability design principles dedicated to medication alerting systems are identified. They represent six themes: improve the signal-to-noise ratio, fit clinicians’ workflow, support collaborative work, display relevant information, make the system transparent and provide useful tools. The matching between usability flaws and principles is quite good.Discussion.As a result of this work, a list of usability design principles illustrated by actual instances of their violation has been developed. It may help designers and Human Factors experts understand and apply usability design principles when designing and evaluating medication alerting systems. Usability applied to HIT is a recent research field that suffers from a deficit of structured knowledge. This work shows that it is possible to accumulate and structure usability knowledge. It could be carried on by developing a usability knowledge base dedicated to HIT in order to strive towards “evidence-based usability”.

Diss. (sammanfattning) Stockholm : Karolinska institutet, 2009. / Härtill 4 uppsatser.

As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approach to optimize a decision-fusion technique to combine heterogeneous information, such as from different modalities, feature categories, or institutions. For classifier comparison we used two performance metrics: The receiving operator characteristic (ROC) area under the curve [area under the ROC curve (AUC)] and the normalized partial area under the curve (pAUC). This study used four classifiers: Linear discriminant analysis (LDA), artificial neural network (ANN), and two variants of our decision-fusion technique, AUC-optimized (DF-A) and pAUC-optimized (DF-P) decision fusion. We applied each of these classifiers with 100-fold cross-validation to two heterogeneous breast cancer data sets: One of mass lesion features and a much more challenging one of microcalcification lesion features. For the calcification data set, DF-A outperformed the other classifiers in terms of AUC (p < 0.02) and achieved AUC=0.85 +/- 0.01. The DF-P surpassed the other classifiers in terms of pAUC (p < 0.01) and reached pAUC=0.38 +/- 0.02. For the mass data set, DF-A outperformed both the ANN and the LDA (p < 0.04) and achieved AUC=0.94 +/- 0.01. Although for this data set there were no statistically significant differences among the classifiers' pAUC values (pAUC=0.57 +/- 0.07 to 0.67 +/- 0.05, p > 0.10), the DF-P did significantly improve specificity versus the LDA at both 98% and 100% sensitivity (p < 0.04). In conclusion, decision fusion directly optimized clinically significant performance measures, such as AUC and pAUC, and sometimes outperformed two well-known machine-learning techniques when applied to two different breast cancer data sets. / Dissertation

PURPOSE: To demonstrate the feasibility of using a knowledge base of prior treatment plans to generate new prostate intensity modulated radiation therapy (IMRT) plans. Each new case would be matched against others in the knowledge base. Once the best match is identified, that clinically approved plan is used to generate the new plan. METHODS: A database of 100 prostate IMRT treatment plans was assembled into an information-theoretic system. An algorithm based on mutual information was implemented to identify similar patient cases by matching 2D beam's eye view projections of contours. Ten randomly selected query cases were each matched with the most similar case from the database of prior clinically approved plans. Treatment parameters from the matched case were used to develop new treatment plans. A comparison of the differences in the dose-volume histograms between the new and the original treatment plans were analyzed. RESULTS: On average, the new knowledge-based plan is capable of achieving very comparable planning target volume coverage as the original plan, to within 2% as evaluated for D98, D95, and D1. Similarly, the dose to the rectum and dose to the bladder are also comparable to the original plan. For the rectum, the mean and standard deviation of the dose percentage differences for D20, D30, and D50 are 1.8% +/- 8.5%, -2.5% +/- 13.9%, and -13.9% +/- 23.6%, respectively. For the bladder, the mean and standard deviation of the dose percentage differences for D20, D30, and D50 are -5.9% +/- 10.8%, -12.2% +/- 14.6%, and -24.9% +/- 21.2%, respectively. A negative percentage difference indicates that the new plan has greater dose sparing as compared to the original plan. CONCLUSIONS: The authors demonstrate a knowledge-based approach of using prior clinically approved treatment plans to generate clinically acceptable treatment plans of high quality. This semiautomated approach has the potential to improve the efficiency of the treatment planning process while ensuring that high quality plans are developed. / Dissertation