In lieu of traditional genetic variant testing approaches, an approach using scalable variant classification in primary human T cells with a clinically relevant readout can inform rapid diagnosis and treatment of inborn errors of immunity.

Single-cell transcriptomics analysis and multimodal profiling (STAMP) by imaging enables single-cell analysis of cells in suspension without the need for sequencing. The markedly reduced costs and flexible experimental designs support the profiling of millions of cells or the large-scale multiplexing of conditions, perturbations, and sample types.

Background: Health care continues to advance through digital innovation, and technology-enabled processes and interventions are increasingly being introduced to deliver and expand access to care. In this evolving digital health ecosystem, health care professionals (HCPs), learners, and organizations may not be prepared or equipped with the knowledge, skills, and behaviors required to navigate these new digital tools while simultaneously sustaining and integrating compassionate care. Moreover, the tools may not be designed and implemented in a manner that facilitates digital compassion. Objective: This study aimed to identify (1) core digital compassion competencies for health professionals and (2) digital compassion health IT attributes. Methods: We conducted this study based on the Delphi method, a consensus-building technique using structured group communication that allows a group of experts to identify competencies and agree on items such as standards and attributes by achieving consensus on a given topic. To encourage enriched discussions, we used a modified eDelphi method, where the first round consisted of a group activity and focus group rather than a questionnaire. Due to COVID-19 pandemic restrictions, the first round was held online. Subsequent rounds consisted of questionnaires administered via email and a web-based survey. Using purposive sampling, participants were recruited from project partners and networks of the research team. A panel of experts across Canada in the fields of compassion, health professional or medical education, and technology was engaged to identify and prioritize professional domains and competency statements, as well as essential attributes for the development and deployment of digital technologies for compassionate care. Results: A total of 54 experts across Canada were recruited, representing diverse professions including patients or service users, HCPs, administrators, policy makers, health educators, data scientists, health technology designers, and software engineers. Overall, 9 focus groups were conducted and analyzed thematically. Seven domains of digital compassion were identified: (1) digital literacy, (2) patient preference, (3) collaboration and co-design, (4) therapeutic relationship, (5) ethical implications, (6) patient safety, and (7) technology safety. Technology attributes to facilitate digital compassion were also generated. We reached consensus after several subsequent rounds, resulting in 58 digital compassion competency statements and 15 technology attributes. Conclusions: This study identified a digital compassion framework consisting of competencies for HCPs and attributes for digital technologies that would enhance compassion in virtual care encounters. To promote a cultural shift where technologies are perceived to be not only efficient but also compassionate, practices of co-design, training, and ongoing evaluation and iteration must be prioritized within health care organizations. Future research should explore the adaptability of the professional competencies and technology attributes to specific medical specialties or in patient populations.