Support consistent, competent practice for data science in pathogen genomics: the development of an innovative competency framework

Background: A barrier to the application of pathogen genomics for service delivery is due to a lack of trained healthcare and public health professionals. We developed a pathogen genomics competency framework (CF) outlining the knowledge, skills and attitudes (KSAs) required for performing genomics pipelines, supporting analysis and interpretation.Methods: A mixed-method approach was applied, starting with a questionnaire aimed at healthcare and research professionals (n=90) to gather data on respondents’ roles and self-assessed proficiencies using an initial set of pathogen genomics competencies based on domain topics including biology, data science, genomic analysis and interpretation. We employed a consensus-building approach among the representative professionals to establish personas and ascertain the proficiency levels for each persona and competency. A database of competency statements reflecting six proficiency levels (Blooms taxonomy) was developed.An iterative design approach was adopted for continuous refinement and updating of the competency framework through consensus building among relevant stakeholders, allowing adaptation to the evolving landscape of genomics across various settings.Results: The CF covers six clinical and public health roles including Bioinformatician. The CF also encompasses a database of 60 pathogen genomics competencies, containing statements across 6 Blooms levels for each competency, allowing for the new roles to be created. This CF can evolve, catering to the diverse needs and interests of stakeholders.Conclusions: Providing a link between practice, education and training, the CF aids: institutions determining skills gaps and designing of training programmes; self-assessment by individuals to identify areas for development; the recruitment of staff with relevant skills.