THE DEVELOPMENT AND EVALUATION OF SOFTWARE TO VERIFY DIAGNOSTIC ACCURACY

This article describes the development and evaluation of software that verifies the accuracy of diagnoses made by nursing students. The software was based on a model that uses fuzzy logic concepts, including PERL, the MySQL database for Internet accessibility, and the NANDA-I 2007-2008 classification system. The software was evaluated in terms of its technical quality and usability through specific instruments. The activity proposed in the software involves four stages in which students establish the relationship values between nursing diagnoses, defining characteristics/risk factors and clinical cases. The relationship values determined by students are compared to those of specialists, generating performance scores for the students. In the evaluation, the software demonstrated satisfactory outcomes regarding the technical quality and, according to the students, helped in their learning and may become an educational tool to teach the process of nursing diagnosis.

A rigorous approach to facilitate and guarantee the correctness of the genetic testing management in human genome information systems

Abstract Background Recent medical and biological technology advances have stimulated the development of new testing systems that have been providing huge, varied amounts of molecular and clinical data. Growing data volumes pose significant challenges for information processing systems in research centers. Additionally, the routines of genomics laboratory are typically characterized by high parallelism in testing and constant procedure changes. Results This paper describes a formal approach to address this challenge through the implementation of a genetic testing management system applied to human genome laboratory. We introduced the Human Genome Research Center Information System (CEGH) in Brazil, a system that is able to support constant changes in human genome testing and can provide patients updated results based on the most recent and validated genetic knowledge. Our approach uses a common repository for process planning to ensure reusability, specification, instantiation, monitoring, and execution of processes, which are defined using a relational database and rigorous control flow specifications based on process algebra (ACP). The main difference between our approach and related works is that we were able to join two important aspects: 1) process scalability achieved through relational database implementation, and 2) correctness of processes using process algebra. Furthermore, the software allows end users to define genetic testing without requiring any knowledge about business process notation or process algebra. Conclusions This paper presents the CEGH information system that is a Laboratory Information Management System (LIMS) based on a formal framework to support genetic testing management for Mendelian disorder studies. We have proved the feasibility and showed usability benefits of a rigorous approach that is able to specify, validate, and perform genetic testing using easy end user interfaces.