Automatic Search of Nursing Diagnoses

  • Matías A. Morales
  • Rosa L. Figueroa
  • Jael E. Cabrera
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7042)

Abstract

Nursing documentation is all the information that nurses register regarding the clinical assessment and care of a patient. Currently, these records are manually written in a narrative style; consequently, their quality and completeness largely depends on the nurse’s expertise. This paper presents an algorithm based on standardized nursing language that searches and sorts nursing diagnoses by its relevance through a ranking. Diagnoses identification is performed by searching and matching patterns among a set of patient needs or symptoms and the international standard of nursing diagnoses NANDA. Three sorting methods were evaluated using 6 utility cases. The results suggest that TF-IDF (83.43% accuracy) and assignment of weights by hit (80.73% accuracy) are the two best alternatives to implement the ranking of diagnoses.

Keywords

NANDA Nursing documentation Pattern Matching Diagnosis retrieval Decision Support TF TF-IDF 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Matías A. Morales
    • 1
  • Rosa L. Figueroa
    • 1
  • Jael E. Cabrera
    • 2
  1. 1.Electrical Engineering DepartmentUniversity of ConcepciónChile
  2. 2.Cardiac Surgery DepartmentGuillermo Grant Benavente Hospital, Cardiac Surgery ICUChile

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