Grand challenges in clinical decision support

By Dean F. Sittig, A. Wright, J. Osheroff, Blackford Middleton, J. Teich, Joan S. Ash, Emily M. Campbell, David W. Bates. Journal of Biomedical Informatics, 2008

609 citations recorded by the source corpus.

Subfields: Family Practice, Health Information Management

View Paper: https://www.semanticscholar.org/paper/62747a7dc2c6c7ddd8becade568c21a5cdfed448

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Family Practice

1. Wendy W. Chapman

In Health Information Management

1. Dina Demner-Fushman
2. Wendy W. Chapman
3. Clement J. McDonald
4. Walter Daelemans
5. Simon Suster

Citations in the corpus

• Electronic medical record phenotyping using the anchor and learn framework (2016, methodology): “The distillation of diverse information sources from the electronic medical record into intermediate variables that can then be used as trusted pieces of information in downstream logic has been identified as a grand challenge in clinical decision support.(4) We describe and evaluate a method of ext”
• Unremarkable AI: Fitting Intelligent Decision Support into Critical, Clinical Decision-Making Processes (2019, background): “(Pediatric surgeon) 6 DISCUSSION: DESIGNING AND EVALUATING DST AS A SITUATED EXPERIENCE Clinical DSTs, despite compelling evidence of their effectiveness in labs, have mostly failed when moving out of labs and into healthcare practice [15, 19].”
• Best Care at Lower Cost: The Path to Continuously Learning Health Care in America (2013, background): “multiple vendors, allowing this technology to be embedded seamlessly in the standard clinical workflow (Sittig et al., 2008; Wright and Sittig, 2008).”
• What can Natural Language Processing do for Clinical Decision Support? (2009, background): “In theory, NLP systems might also be able to represent clinical knowledge and CDS interventions in standardized formats [4–6].”