Constructing evidence-based clinical intrapartum care algorithms for decision-support tools
- PMID: 35411684
- DOI: 10.1111/1471-0528.16958
Constructing evidence-based clinical intrapartum care algorithms for decision-support tools
Abstract
Aim: To describe standardised iterative methods used by a multidisciplinary group to develop evidence-based clinical intrapartum care algorithms for the management of uneventful and complicated labours.
Population: Singleton, term pregnancies considered to be at low risk of developing complications at admission to the birthing facility.
Setting: Health facilities in low- and middle-income countries.
Search strategy: Literature reviews were conducted to identify standardised methods for algorithm development and examples from other fields, and evidence and guidelines for intrapartum care. Searches for different algorithm topics were last updated between January and October 2020 and included a combination of terms such as 'labour', 'intrapartum', 'algorithms' and specific topic terms, using Cochrane Library and MEDLINE/PubMED, CINAHL, National Guidelines Clearinghouse and Google.
Case scenarios: Nine algorithm topics were identified for monitoring and management of uncomplicated labour and childbirth, identification and management of abnormalities of fetal heart rate, liquor, uterine contractions, labour progress, maternal pulse and blood pressure, temperature, urine and complicated third stage of labour. Each topic included between two and four case scenarios covering most common deviations, severity of related complications or critical clinical outcomes.
Conclusions: Intrapartum care algorithms provide a framework for monitoring women, and identifying and managing complications during labour and childbirth. These algorithms will support implementation of WHO recommendations and facilitate the development by stakeholders of evidence-based, up to date, paper-based or digital reminders and decision-support tools. The algorithms need to be field tested and may need to be adapted to specific contexts.
Tweetable abstract: Evidence-based intrapartum care clinical algorithms for a safe and positive childbirth experience.
Keywords: Algorithms; childbirth; first stage of labour; intrapartum care; labour complications; second stage of labour; third stage of labour.
© 2022 The World Health Organization. The World Health Organization retains copyright and all other rights in the manuscript of this article as submitted for publication.
References
-
- Kassebaum NJ, Bertozzi‐Villa A, Coggeshall MS, Shackelford KA, Steiner C, Heuton KR, et al. Global, regional, and national levels and causes of maternal mortality during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014;384:980–1004.
-
- Say L, Chou D, Gemmill A, Tunçalp Ö, Moller A‐B, Daniels J, et al. Global causes of maternal death: a WHO systematic analysis. Lancet Glob Health 2014;2:e323–33.
-
- Lawn JE, Blencowe H, Waiswa P, Amouzou A, Mathers C, Hogan D, et al. Stillbirths: rates, risk factors, and acceleration towards 2030. Lancet 2016;387:587–603.
-
- Bhutta ZA, Das JK, Bahl R, Lawn JE, Salam RA, Paul VK, et al. Can available interventions end preventable deaths in mothers, newborn babies, and stillbirths, and at what cost? Lancet 2014;384:347–70.
-
- Michalow J, Chola L, McGee S, Tugendhaft A, Pattinson R, Kerber K, et al. Triple return on investment: the cost and impact of 13 interventions that could prevent stillbirths and save the lives of mothers and babies in South Africa. BMC Pregnancy Childbirth 2015;15:39.
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources