Data work and practices in healthcare: A scoping review

Context: In healthcare, digitization has been widespread and profound, entailing a deluge of data. This has spurred ambitions for healthcare to become data-driven to improve efficiency and quality, and within medicine itself to improve diagnosing and treating diseases. The generation and processing of data requires human intervention and work, though this is often not acknowledged. Purpose: The paper investigates who, where, by which means, and for which purposes data work is conducted which is crucial for healthcare managers and policy makers if ambitions to become data-driven are to succeed. To guide further research, it also provides an overview of existing research on data work and practices. Methods: We conducted a scoping review based on a search for papers including the terms healthcare or health care combined with at least one of the following terms: data work, data worker*, data practice*, data practitioner* in Scopus and Web of Science. 74 papers on data work or practices in healthcare were included. Analysis: The 74 papers were coded and analyzed regarding the following themes: the kind of data workers and practitioners, organizational settings, involved technologies, purposes, data work tasks, theories and concepts, and definitions of data work and practice. Results: Data work is pervasive in healthcare and conducted by various professions and people and in various contexts. The field researching data work and practices is emerging, with publications spread across multiple venues. and there is a need for more precise definitions of data work. Further, data work and practices are useful concepts that have enabled the exploration of those efforts and tasks in detail. Conclusion: The research on data work and practices in healthcare is emerging and promising. We call for more research to consolidate the field and to better understand and support the work needed for healthcare to become data-driven.