AI Article Synopsis

  • A Patient Safety Learning Laboratory was created with core and individual project teams to develop digital health tools for real-time patient safety improvement.
  • One core team applied systems engineering and human factors methods to assess issues, enhance interventions, and evaluate the integrated system.
  • Research involved surveys and focus groups from participation, leading to insights about the effectiveness of qualitative methods compared to quantitative methods and identifying challenges in a decentralized project structure.

Article Abstract

We established a Patient Safety Learning Laboratory comprising 2 core and 3 individual project teams to introduce a suite of digital health tools integrated with our electronic health record to identify, assess, and mitigate threats to patient safety in real time. One of the core teams employed systems engineering (SE) and human factors (HF) methods to analyze problems, design and develop improvements to intervention components, support implementation, and evaluate the system of systems as an integrated whole. Of the 29 participants, 19 and 16 participated in surveys and focus groups, respectively, about their perception of SE and HF. We identified 7 themes regarding use of the 12 SE and HF methods over the 4-year project. Qualitative methods (interviews, focus, groups, observations, usability testing) were most frequently used, typically by individual project teams, and generated the most insight. Quantitative methods (failure mode and effects analysis, simulation modeling) typically were used by the SE and HF core team but generated variable insight. A decentralized project structure led to challenges using these SE and HF methods at the project and systems level. We offer recommendations and insights for using SE and HF to support digital health patient safety initiatives.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7647327PMC
http://dx.doi.org/10.1093/jamia/ocz002DOI Listing

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