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Published in: BMC Medical Informatics and Decision Making 1/2012

Open Access 01-12-2012 | Research article

Risk assessment and decision making about in-labour transfer from rural maternity care: a social judgment and signal detection analysis

Authors: Helen Cheyne, Len Dalgleish, Janet Tucker, Fiona Kane, Ashalatha Shetty, Sarah McLeod, Catherine Niven

Published in: BMC Medical Informatics and Decision Making | Issue 1/2012

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Abstract

Background

The importance of respecting women’s wishes to give birth close to their local community is supported by policy in many developed countries. However, persistent concerns about the quality and safety of maternity care in rural communities have been expressed. Safe childbirth in rural communities depends on good risk assessment and decision making as to whether and when the transfer of a woman in labour to an obstetric led unit is required. This is a difficult decision. Wide variation in transfer rates between rural maternity units have been reported suggesting different decision making criteria may be involved; furthermore, rural midwives and family doctors report feeling isolated in making these decisions and that staff in urban centres do not understand the difficulties they face. In order to develop more evidence based decision making strategies greater understanding of the way in which maternity care providers currently make decisions is required. This study aimed to examine how midwives working in urban and rural settings and obstetricians make intrapartum transfer decisions, and describe sources of variation in decision making.

Methods

The study was conducted in three stages. 1. 20 midwives and four obstetricians described factors influencing transfer decisions. 2. Vignettes depicting an intrapartum scenario were developed based on stage one data. 3. Vignettes were presented to 122 midwives and 12 obstetricians who were asked to assess the level of risk in each case and decide whether to transfer or not. Social judgment analysis was used to identify the factors and factor weights used in assessment. Signal detection analysis was used to identify participants’ ability to distinguish high and low risk cases and personal decision thresholds.

Results

When reviewing the same case information in vignettes midwives in different settings and obstetricians made very similar risk assessments. Despite this, a wide range of transfer decisions were still made, suggesting that the main source of variation in decision making and transfer rates is not in the assessment but the personal decision thresholds of clinicians.

Conclusions

Currently health care practice focuses on supporting or improving decision making through skills training and clinical guidelines. However, these methods alone are unlikely to be effective in improving consistency of decision making.
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Metadata
Title
Risk assessment and decision making about in-labour transfer from rural maternity care: a social judgment and signal detection analysis
Authors
Helen Cheyne
Len Dalgleish
Janet Tucker
Fiona Kane
Ashalatha Shetty
Sarah McLeod
Catherine Niven
Publication date
01-12-2012
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2012
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/1472-6947-12-122

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