Search

In this paper we describe a module that allows to collect (a) motivations for non-compliance to guidelines, (b) motivations for poor data entry into the electronic patient record, and (c) comments on medical aspects of guideline recommendations, on their formalisation into computerised rules, and on the guideline integration into the computerised clinical chart. We organised a well-structured taxonomy of non-compliance motivations in such a way that the main hierarchical levels correspond to different medical or technical roles suitable for feedback managing. We analysed about 400 consecutive cases of patients with ischemic stroke. About 40 non-compliances, as well as several incomplete data forms have been identified and motivated. [ABSTRACT FROM AUTHOR]

We describe a system that facilitates speech therapists to administer cognitive rehabilitation exercises and to evaluate treatment outcomes. We started by augmenting a commercial tool with a more user-friendly interface, meeting the needs of the healthcare professionals involved. Then we integrated, into the same tool, a new type of exercise, that is particularly patient-tailored, being based on the recognition of familiar images within a picture (such as a relative, a domestic animal, a home object, etc). Segmentation techniques are used to elaborate an input picture and individuate areas including interesting objects, that will be semi-automatically linked to text and sound. The picture and associated information are then stored in the system database and may be subsequently used as objects for the new exercise. Any number of images may be elaborated, personalised and stored for each patient. The performance has been tested on voluntary subjects with good results. [ABSTRACT FROM AUTHOR]

Willingness to use computerised decision support systems is often jeopardised by lack of effective integration into existing user interfaces for electronic patient record. Concepts illustrated in this paper stem from the need of developing a project for the comparison of the physicians' compliance to a clinical practice guideline before and after an electronic version of the guideline was introduced. Before starting the implementation, we performed a deep users' needs analysis. It was accomplished also on the basis of lesson learned on past guideline implementations. The new idea was to classify guideline suggestions on the basis of some attributes, whose values will determine the modality of presentation of the suggestion itself, and on a different management of non compliance advice. [ABSTRACT FROM AUTHOR]