Understanding Human Factors Challenges on the Front Lines of Mass COVID-19 Vaccination Clinics: Human Systems Modeling Study.
Ryan TennantMoses TetuiKelly Anne GrindrodCatherine Marie BurnsPublished in: JMIR human factors (2022)
Modeling mass COVID-19 vaccination clinics from a human systems perspective identified 2 high-level opportunities for improving the inefficiencies within this health care delivery system. First, clinics may become more resilient to unexpected changes in client intake or vaccine preparation using strategies and artifacts that standardize data gathering and synthesis, thereby reducing uncertainties for end-of-day dose decision-making. Second, improving data sharing among staff by co-locating their workstations and implementing collaborative artifacts that support a collective understanding of the state of the clinic may reduce system complexity by improving shared situational awareness. Future research should examine how the developed models apply to immunization settings beyond the Region of Waterloo and evaluate the impact of the recommendations on workflow coordination, stress, and decision-making.
Keyphrases
- endothelial cells
- decision making
- primary care
- coronavirus disease
- healthcare
- sars cov
- induced pluripotent stem cells
- electronic health record
- quality improvement
- magnetic resonance
- mass spectrometry
- magnetic resonance imaging
- machine learning
- body mass index
- health information
- social media
- deep learning
- clinical practice
- image quality
- data analysis
- contrast enhanced
- liquid chromatography
- affordable care act
- heat stress
- cone beam