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Constructing evidence-based clinical intrapartum care algorithms for decision-support tools.

M Bonet1, L Ciabati2, L L De Oliveira2

  • 1UNDP/UNFPA/UNICEF/WHO/World Bank Special Program of Research, Development and Research Training in Human Reproduction (HRP), Department of Sexual and Reproductive Health and Research, World Health Organization, Geneva, Switzerland.

BJOG : an International Journal of Obstetrics and Gynaecology
|April 12, 2022
PubMed
Summary
This summary is machine-generated.

This study outlines standardized methods for developing evidence-based intrapartum care algorithms. These clinical algorithms aim to improve labor and childbirth management for a safer, positive experience.

Keywords:
Algorithmschildbirthfirst stage of labourintrapartum carelabour complicationssecond stage of labourthird stage of labour

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Area of Science:

  • Obstetrics and Gynecology
  • Clinical Decision Support Systems
  • Evidence-Based Medicine

Background:

  • Intrapartum care requires standardized approaches for effective management of labor and childbirth.
  • Developing clinical algorithms can enhance consistency and quality of care.
  • Existing guidelines may not fully address all aspects of intrapartum complications.

Purpose of the Study:

  • To describe standardized iterative methods used by a multidisciplinary group to develop evidence-based clinical intrapartum care algorithms.
  • To create algorithms for managing both uneventful and complicated labors.
  • To support the implementation of World Health Organization (WHO) recommendations.

Main Methods:

  • Utilized literature reviews to identify standardized algorithm development methods and intrapartum care evidence.
  • Searched multiple databases (Cochrane Library, MEDLINE/PubMed, CINAHL, etc.) using specific keywords.
  • Developed nine algorithm topics covering various aspects of labor monitoring and complication management, including case scenarios.

Main Results:

  • Identified nine key topics for intrapartum care algorithm development.
  • Included case scenarios for common labor deviations, complications, and critical outcomes.
  • Algorithms provide a framework for monitoring and managing labor and childbirth.

Conclusions:

  • Intrapartum care algorithms offer a structured approach to monitoring and managing labor complications.
  • These algorithms can support the development of decision-support tools for improved childbirth experiences.
  • Field testing and contextual adaptation are necessary for effective implementation.