Clinical Orthopaedics and Related Research®

, Volume 468, Issue 10, pp 2612–2620 | Cite as

Computational Ontologies in Orthopaedic Surgery

  • Ricardo Pietrobon
  • Amrapali Zaveri
  • Luciana Cofiel
  • Jacson Barros
  • Jatin Shah
Symposium: ABJS Carl T. Brighton Workshop on Health Informatics



Information Technology (IT) plays an important role in storing and collating the vast amounts of healthcare data. However, analyzing and integrating this data to extract useful information is difficult due to the heterogeneous, siloed, disparate, and unstructured nature of the data.

Where are we now?

Attempts to standardize data reporting by establishing reporting standards, checklists and guidelines have not been optimal [3, 11, 19]. Moreover, efforts to integrate data through the use of registries, data sharing networks, vocabularies and data standards have also yielded limited results. These efforts, when applied to orthopaedics, where theoretical knowledge is scattered over subspecialties, make it a cognitively challenging and tedious process.

Where do we need to go?

Implementing data standardization is an important step towards homogenizing the data so that it can be integrated. Once integrated, the next step would be data analysis for information extraction. This information would be useful in answering important questions, especially in orthopaedic clinical practice and research, and could even help optimize methodologies in the education field.

How do we get there?

With the ability to describe concepts in a standardized manner and define existing interrelationships, ontologies are a potential solution. They assist in standardizing and integrating data and also impart strong inferential capabilities at a granular level. When applied to orthopaedics, they can standardize data collection, link data sources, generate knowledge based on the assumptions present in the interlinked data, thus answering important questions regarding orthopaedic clinical practice, research and education [22, 28, 30].


Knowledge Translation Musculoskeletal System Clubfoot Electronic Patient Record System Granular Level 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank the “Research on Research” team for the templates for writing the introduction and discussion sections of the manuscript as well as templates for Literature matrix, Duke University Health System. (Available at: Accessed Dec 12, 2009.)


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Copyright information

© The Association of Bone and Joint Surgeons® 2010

Authors and Affiliations

  • Ricardo Pietrobon
    • 1
  • Amrapali Zaveri
    • 1
    • 2
  • Luciana Cofiel
    • 1
  • Jacson Barros
    • 1
  • Jatin Shah
    • 3
  1. 1.Department of Surgery, Research on Research GroupDuke University Medical CenterDurhamUSA
  2. 2.National Neuroscience InstituteSingaporeSingapore
  3. 3.Duke-NUS Graduate Medical SchoolSingaporeSingapore

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