A rule-based method for continuity of care identification in discharge summaries.
Discharge summaries are an important clinical narrative as they include the continuity of care information. Identification of data contained in their text is a difficult task due to its freeform text and lack of consensus on essential content. This research proposes a rule-based method to verify the presence of information about continuity of care in Portuguese texts, applying Natural Language Processing (NLP) techniques, and based on an annotated medical corpus. After the experiments, 4 rules were defined and applied in the text of 200 summaries to identify if they have or not the continuity of care information. This process had resulted in Precision value of 84%, Recall value of 70%, Specificity value of 97% and F-Measure value of 76% related to algorithm evaluation.
Health Technology Post-Graduate Program, Polytechnic School, Pontifical Catholic University of Paraná, Brazil.
Lucas E
LE
Silva e Oliveira
Andréia C
AC
de Souza
Percy
P
Nohama
Claudia M C
CM
Moro
D000465:Algorithms; D001185:Artificial Intelligence; D003266:Continuity of Patient Care / Q000145:classification* / Q000706:statistics & numerical data; D057225:Data Mining / Q000379:methods; D009323:Natural Language Processing; D063886:Patient Discharge Summaries / Q000145:classification* / Q000706:statistics & numerical data; D011174:Portugal; D011785:Quality Assurance, Health Care / Q000379:methods*; D018875:Vocabulary, Controlled