Supporting electronic health record data usage in research for teams with varying data science and clinical knowledge: a food service analogy approach.

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.

• Publication year

  2025

• Venue

  JAMIA Journal of the American Medical Informatics Association

• Publication date

  2025-11-10

• Fields of study

  Medicine, Business, Computer Science

• Identifiers
  DOI 10.1093/jamia/ocaf188PMID 41211699PMCID PMC12844577
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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