Skip to main content
Journal cover image

Towards an on-demand peer feedback system for a clinical knowledge base: a case study with order sets.

Publication ,  Journal Article
Hulse, NC; Del Fiol, G; Bradshaw, RL; Roemer, LK; Rocha, RA
Published in: J Biomed Inform
February 2008

OBJECTIVE: We have developed an automated knowledge base peer feedback system as part of an effort to facilitate the creation and refinement of sound clinical knowledge content within an enterprise-wide knowledge base. The program collects clinical data stored in our Clinical Data Repository during usage of a physician order entry program. It analyzes usage patterns of order sets relative to their templates and creates a report detailing the usage patterns of the order set template. This report includes a set of suggested modifications to the template. DESIGN: A quantitative analysis was performed to assess the validity of the program's suggested order set template modifications. MEASUREMENTS: We collected and de-identified 2951 instances of POE-based orders. Our program then identified and generated feedback reports for thirty different order set templates from this data set. These reports contained 500 suggested modifications. Five order set authors were then asked to 'accept' or 'reject' each suggestion contained in his/her respective order set templates. They were also asked to categorize their rationale for doing so ('clinical relevance' or 'user convenience'). RESULTS: In total, 62% (309/500) suggestions were accepted by clinical content authors. Of these, authors accepted 32% (36/114) of the suggested additions, 74% (123/167) of the suggested pre-selections, 76% (16/25) of the suggested de-selections, and 68% (131/194) of the suggested changes in combo box order. CONCLUSION: Overall, the feedback system generated suggestions that were deemed highly acceptable among order set authors. Future refinements and enhancements to the software will add to its utility.

Duke Scholars

Published In

J Biomed Inform

DOI

EISSN

1532-0480

Publication Date

February 2008

Volume

41

Issue

1

Start / End Page

152 / 164

Location

United States

Related Subject Headings

  • Utah
  • Medical Informatics
  • Medical Informatics
  • Information Storage and Retrieval
  • Health Knowledge, Attitudes, Practice
  • Expert Systems
  • Databases, Factual
  • Database Management Systems
  • Biomedical Engineering
  • 4601 Applied computing
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Hulse, N. C., Del Fiol, G., Bradshaw, R. L., Roemer, L. K., & Rocha, R. A. (2008). Towards an on-demand peer feedback system for a clinical knowledge base: a case study with order sets. J Biomed Inform, 41(1), 152–164. https://doi.org/10.1016/j.jbi.2007.05.006
Hulse, Nathan C., Guilherme Del Fiol, Richard L. Bradshaw, Lorrie K. Roemer, and Roberto A. Rocha. “Towards an on-demand peer feedback system for a clinical knowledge base: a case study with order sets.J Biomed Inform 41, no. 1 (February 2008): 152–64. https://doi.org/10.1016/j.jbi.2007.05.006.
Hulse NC, Del Fiol G, Bradshaw RL, Roemer LK, Rocha RA. Towards an on-demand peer feedback system for a clinical knowledge base: a case study with order sets. J Biomed Inform. 2008 Feb;41(1):152–64.
Hulse, Nathan C., et al. “Towards an on-demand peer feedback system for a clinical knowledge base: a case study with order sets.J Biomed Inform, vol. 41, no. 1, Feb. 2008, pp. 152–64. Pubmed, doi:10.1016/j.jbi.2007.05.006.
Hulse NC, Del Fiol G, Bradshaw RL, Roemer LK, Rocha RA. Towards an on-demand peer feedback system for a clinical knowledge base: a case study with order sets. J Biomed Inform. 2008 Feb;41(1):152–164.
Journal cover image

Published In

J Biomed Inform

DOI

EISSN

1532-0480

Publication Date

February 2008

Volume

41

Issue

1

Start / End Page

152 / 164

Location

United States

Related Subject Headings

  • Utah
  • Medical Informatics
  • Medical Informatics
  • Information Storage and Retrieval
  • Health Knowledge, Attitudes, Practice
  • Expert Systems
  • Databases, Factual
  • Database Management Systems
  • Biomedical Engineering
  • 4601 Applied computing