Measuring text similarity and its associated factors in electronic nursing progress notes: A retrospective review

To measure text similarity in electronic nursing progress notes and determine factors associated with text similarity.

Electronic clinical notes with redundant information masks clinically relevant information, increases clinicians' cognitive burden and undermines patient safety.

Retrospective review of electronic medical record nursing progress notes.

The study was conducted between November 2018 and February 2019 in two Australian Paediatric Intensive Care Units. De-identified, randomly selected inpatient data were extracted from the network's database. Manually classified shift summary progress notes for each admission were sequenced from admission to discharge. Text similarity was calculated for consecutive pairs of nursing progress notes. Linear regression was undertaken to determine the association between the similarity scores and variables of interest: note word count, total number of notes and unit. The STROBE checklist was used for reporting.

921 shift summary nursing progress notes were analysed. Similarity scores were widely distributed with a median of 10.37%. Only 17.2% (n = 144) of the notes have similarity scores above 20%. Of these, 5% (n = 47) were above 50% similar in comparison with a previously written note. Similarity above 50% was observed as early as the first note pair in the course of a patient's admission. A significant difference was found between the similarity scores of Unit 1 and Unit 2. Hospital unit was the only variable of interest significantly associated with similarity scores.

Text similarity among electronic nursing progress notes in Australian Paediatric ICUs is minimal; however, notes with >50% similarity have been identified. Text analytics provides measurable data and insights about electronic clinical documentation to inform future nursing practice, research and eMR design.

Findings have implications for nursing practice in the way that nursing staff are educated to maintain data quality, professional accountability and effective communication in electronic documentation and to avoid unnecessary repetition of text.