A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Evaluating Pain in Intensive Care
Tekijät: Suominen H, Lundgren-Laine H, Salantera S, Salakoski T
Julkaisuvuosi: 2009
Lehti:: Studies in Health Technology and Informatics
Tietokannassa oleva lehden nimi: CONNECTING HEALTH AND HUMANS
Lehden akronyymi: ST HEAL T
Vuosikerta: 146
Aloitussivu: 192
Lopetussivu: 196
Sivujen määrä: 2
ISBN: 978-1-60750-024-7
ISSN: 0926-9630
DOI: https://doi.org/10.3233/978-1-60750-024-7-192
Tiivistelmä
Optimal pain management is essential for good care outcomes, but assessing pain is particularly complex in intensive care, as patients are often unable to communicate. We hypothesize that the task could be supported through human language technology. To evaluate the feasibility of such tools, we study how pain is documented in electronic Finnish free-text intensive care nursing notes by statistically comparing annotations of ten nursing professionals on a set of 1548 documents. The aspects considered include the amount and writing style of pain-related notes, pain intensity, and given pain care. More than half of the documents contained information relevant for patients' pain status but it was expressed usually indirectly. Also pain medication was commented as free-text. Although annotators' pain intensity evaluations diverged, the substantial amount of pain-related notes encourages developing computational tools for pain assessment.
Optimal pain management is essential for good care outcomes, but assessing pain is particularly complex in intensive care, as patients are often unable to communicate. We hypothesize that the task could be supported through human language technology. To evaluate the feasibility of such tools, we study how pain is documented in electronic Finnish free-text intensive care nursing notes by statistically comparing annotations of ten nursing professionals on a set of 1548 documents. The aspects considered include the amount and writing style of pain-related notes, pain intensity, and given pain care. More than half of the documents contained information relevant for patients' pain status but it was expressed usually indirectly. Also pain medication was commented as free-text. Although annotators' pain intensity evaluations diverged, the substantial amount of pain-related notes encourages developing computational tools for pain assessment.
Turun yliopiston Tutkimustietojärjestelmän portaali