Data ambiguity and clinical decision making: A qualitative case study of the use of predictive information technologies in a personalized cancer clinical trial

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.

The use of cognitive task analysis in clinical and health services research — a systematic review

Background

At times, clinical case complexity and different types of uncertainty present challenges to less experienced clinicians or the naive application of clinical guidelines where this may not be appropriate. Cognitive task analysis (CTA) methods are used to elicit, document and transfer tacit knowledge about how experts make decisions.

Methods

We conducted a methodological review to describe the use of CTA methods in understanding expert clinical decision-making. We searched MEDLINE, EMBASE and PsycINFO from inception to 2019 for primary research studies which described the use of CTA methods to understand how qualified clinicians made clinical decisions in real-world clinical settings.

Results

We included 81 articles (80 unique studies) from 13 countries, published from 1993 to 2019, most commonly from surgical and critical care settings. The most common aims were to understand expert decision-making in particular clinical scenarios, using expert decision-making in the development of training programmes, understanding whether decision support tools were warranted and understanding procedural variability and error identification or reduction. Critical decision method (CDM) and CTA interviews were most frequently used, with hierarchical task analysis, task knowledge structures, think-aloud protocols and other methods less commonly used. Studies used interviews, observation, think-aloud exercises, surveys, focus groups and a range of more CTA-specific methodologies such as the systematic human error reduction and prediction approach. Researchers used CTA methods to investigate routine/typical (n = 64), challenging (n = 13) or more uncommon, rare events and anomalies (n = 3).

Conclusions

In conclusion, the elicitation of expert tacit knowledge using CTA has seen increasing use in clinical specialties working under challenging time pressures, complexity and uncertainty. CTA methods have great potential in the development, refinement, modification or adaptation of complex interventions, clinical protocols and practice guidelines.

Registration

PROSPERO ID CRD42019128418.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40814-022-01002-6.