Applicability of decision support algorithm in perineal assessment for childbirth

Abstract

Objective: To develop an algorithm for perineal assessment in childbirth care and assess its applicability and accuracy using a decision support system prototype. Methods: This is applied research of technological development, consisting of the construction of an algorithm, assessment by professionals with expertise in the area, creation of a Decision Support System prototype using online tools and assessment of its applicability and accuracy during care for 305 childbirths performed by nurses. Data were analyzed using descriptive statistics, chi-square and Fisher’s exact tests, in addition to the Kappa coefficient to assess the agreement between the procedure indicated by the system and that performed by professionals. Results: There was agreement between the algorithm’s suggestion and professional decision in 93.1% of childbirths. In 6.9%, professionals decided opposite paths to the recommended one. The professionals who chose to follow the algorithm’s suggestion had perineal integrity or the occurrence of first-degree tear as an outcome. Those who chose not to follow the recommendation had second- or third-degree tears in 28.6% of parturient women. In the accuracy analysis, the algorithm suggested that episiotomy should be performed in 45 of the 305 assisted childbirths. There was an association between divergences in conduct and the number of adverse events (p=0.001). Conclusion: The algorithm proved to be a useful tool for perineal assessment in childbirth care.