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Exploring Human-Data Interaction in Clinical Decision-making Using Scenarios: Co-design Study.

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Summary
This summary is machine-generated.

Health care professionals need better data-supported decision-making (DSDM) tools for chronic obstructive pulmonary disease (COPD) care. Understanding HCPs

Keywords:
COPDclinical decision-makingdata-supported decision-makingdecision supportdigital healthhealth care professionalshealth technologiesrespiratory carerespiratory conditionsscenario-based designuser-centered design

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Area of Science:

  • Health Informatics
  • Human-Computer Interaction
  • Clinical Decision Support

Background:

  • Healthcare professionals (HCPs) managing chronic conditions like COPD use diverse data sources for decision-making.
  • Existing research on data-supported decision-making (DSDM) technologies often overlooks HCPs' real-world engagement and contextual needs.
  • A deeper understanding of human-data interaction is crucial for designing effective DSDM tools in healthcare settings.

Purpose of the Study:

  • To qualitatively explore how DSDM technologies can enhance HCP decision-making in COPD care.
  • To uncover nuanced findings on human-data interaction through a co-designed, scenario-based tool (Respire).
  • To identify real-world challenges HCPs face in utilizing data for patient care decisions.

Main Methods:

  • A 2-year co-design study involving 9 respiratory HCPs from two healthcare organizations.
  • Development of Respire, an interactive web app visualizing HCP data needs for COPD care, informed by workshops.
  • 11 one-to-one sessions using Respire to gather insights on its potential support for HCP work and decision-making.

Main Results:

  • HCPs exhibit differential trust in data based on its source and origin.
  • Patient-generated data, while valuable, presents unique decision-making challenges due to its sporadic and subjective nature.
  • HCPs require enhanced support for interpreting new data and understanding its practical applications.

Conclusions:

  • Sociotechnical factors and human-data interaction complexities significantly impact DSDM technology design and deployment in healthcare.
  • Designing DSDM technologies requires a holistic approach, considering the intricate ways HCPs engage with data in real-world clinical contexts.
  • Incorporating these considerations early in the design process is vital for creating effective and user-centered DSDM solutions.