|Appears in Collections:||Faculty of Health Sciences and Sport Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Risk assessment and decision making about in-labour transfer from rural maternity care: a social judgment and signal detection analysis|
Social judgment theory
Signal detection theory
|Citation:||Cheyne H, Dalgleish L, Tucker J, Kane F, Shetty A, McLeod S & Niven C (2012) Risk assessment and decision making about in-labour transfer from rural maternity care: a social judgment and signal detection analysis, BMC Medical Informatics and Decision Making, 12 (122).|
|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.|
|Rights:||© 2012 Cheyne et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1472-6947/12/122|
|Cheyne et al_BMCMedInfo&DecMak_2012.pdf||809.09 kB||Adobe PDF||View/Open|
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