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'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake
Published on: September 18, 2018
Supporting electronic health record data usage in research for teams with varying data science and clinical
Tanja Magoc1, Leigh Anne Tang2,3, Khoa A Nguyen4
1Quality and Patient Safety Initiative, College of Medicine, University of Florida, Gainesville, FL 32608, United States.
Objective:
To guide research data services (RDS) teams in managing researcher variability (eg, differing deadlines, funding, expertise) when honest-brokering data, we present a framework based on operations management principles and a food service analogy.
Materials And Methods:
Our framework describes 4 data service offerings with different levels of efficiency and service customization: vending machine, fast food, custom meal, and personal chef. We describe examples from 2 institutions.
Results:
Vending machine and fast food are efficient but less customizable, making them better-suited for researchers with limited funding or time. Custom meal and personal chef are less efficient but more customized, making them well suited for better-resourced researchers.
Discussion:
Efficiency and service tradeoffs should be balanced to align with demand and institutional goals. RDS teams can overcome such tradeoffs through uncompromised reduction or low-cost accommodation approaches.
Conclusion:
Our framework can be applied by RDS teams in their design and implementation of data services.
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