Design of Genetic Classification Software: The Case of Representation of Research References

Abstract

Background: The development of genetic classification software for laboratory engineers and laboratory doctors to aid in the diagnostic classification of patient genetic tests for hereditary diseases. The software needs to be robust enough to handle the new sequence technology (HTS) that increases users workload, the need for handling complexity and the need for informatics systems to support their work. Lab engineers and lab doctors use both complex domain knowledge and tacit knowledge in their practice. For the clinical genetic variant classification software to support their work successfully, they need to be involved in the development process. Objective: This study examines the development of genetic classification software identifying user needs and improving some of the functionalities of the software. The first phase of the research was focused on getting to know the design context and identifying the task users experienced to be most challenging. This phase identified evaluation of research references that was used in the classification of gene variant mutations as an important challenge. The second phase of research, then, focused on how the research evaluation functionality of the software should be designed to support the users work best. Methodology: User-centered design with user participation, where users have high professional and domain knowledge, was deployed to involve users in the design process. Results: The findings in this thesis indicate that the combination of the approaches used may be a good way of overcoming usability challenges when working in complex domains. User-centered design in combination with actor-network theory, design theory and emerging knowledge processes get a deeper understanding of the situated design context. 24 design issues and themes for diagnostic genetic research article evaluation was identified through user studies. The main findings are the multiple user strategies for deciding which article from a list references to evaluate first. One strategy deployed by the users is to manually search the research articles content with the name of the gene variant targeted in the classification. The strategy is used to investigate if the variant is mentioned in the article and how many times. Conclusion: This study indicates that the article evaluation functionality needs to support diverse users strategies deployed to evaluate research articles, to create an interrelationship between the technology and their work practice. The research gives a unique contribution to HCI research by displaying how user-centered design is both applicable and beneficial for systems in the complex domain of clinical genetic variant classification.