Abstract:
This thesis reports a qualitative study that collected multiple perspectives of New Zealand genetic services stakeholders concerning genetic information management issues. With the rapid development of human genetic variation knowledge and medical testing technologies, the demand for clinical genetic services is expanding in many healthcare systems. There are, however, many challenges in managing genetic testing and understanding test results. Taking a grounded theory approach, semi-structured interviews were conducted with 48 participants in order to understand their experiences, expectations, and concerns. The interview data were triangulated with our field notes, literature, and by applying a semantic space modelling technique - hyperspace analogue to language. The data analysis took a general inductive approach with a constant analytic comparison strategy. Three themes emerged from the data that identify gaps in the use of information relating to genetic services. Firstly, four service delivery models were identified in operation, including both those expected models involving genetic counsellors and some variations that do not route through the formal genetic services program. Secondly, a number of issues were perceived by the participants as barriers to sharing and using genetic information, including technological, organizational, institutional, legal, ethical, and social issues. Thirdly, the wider use of genetic testing technology is also impeded by the mixed understanding of genetic test utilities, particularly among clinicians, and is limited by the capacity of clinical genetic services. Due to the effect of these three themes, the potential of human genetic variation knowledge to enhance healthcare delivery has been put on a "leash." Targeting these problems, information technologies and knowledge management tools may support key tasks in genetic services delivery, improve knowledge processes in the domain, and enhance knowledge networks. Promising technologies include decision support systems, electronic referral systems, electronic health record or personal health record systems, data submission and other knowledge processing tools, ontology, and knowledge networking tools. The establishment of effective ethics and policy frameworks is also important in leveraging the power of genetic information for better healthcare outcomes.