A large review of research has found that the use of AI and other clinical software tools can improve the quality of care women receive during pregnancy. The review, which was published in eClinicalMedicine, analyzed over 12,000 papers and 87 articles on different AI and related software tools used in maternity settings. The meta-analysis of 35 included studies found that the odds of improved outcomes were 1.69 times higher in women cared for using Clinical Decision Support Systems (CDSS), with data from over 5.2 million pregnancies in both High-Income and Low-and-Middle-Income Countries.
To encourage safer maternity services, academics from the University of Birmingham, Birmingham Health Partners, Keele University, Warwick University, and the Shrewsbury and Telford Hospitals NHS Trust evaluated almost 50 different types of CDSS across 49 High-Income and 38 Low-and-Middle-Income Countries. The findings revealed that although there were variations in each situation and implementation of CDSS that they reviewed, most showed improvements in outcomes for the pregnancies.
According to Neil Cockburn, lead author and research fellow in health informatics at the University of Birmingham, the use of CDSS can help expecting families and healthcare workers to make safe decisions. He added that there needs to be systematic, rigorous, and rapid evaluation of the tools being used to ensure they are doing what is expected while keeping up with the pace of change in technology.
Conclusion
The review highlighted two examples of CDSS that supported both clinical and individual decision-making concerning maternity care. In a study led by the Bristol University, a software program was designed to help women decide if they wanted a vaginal birth after previously having a c-section. This CDSS supported women in feeling more confident about their decisions by providing them with useful information about risks and benefits, while reducing the rate of c-section overall. Another study supported by the Tommy’s National Centre for Miscarriage Research trialled a risk-prediction model to accurately triage women as at low risk of having an ectopic pregnancy, which can be life-threatening in some cases.
The team noted that while substantial contributions can be made to maternity care with CDSS, it relies on appropriateness to each unique situation. As the first systematic review of CDSS, it is hoped that this will encourage evaluations of different CDSS to continue aiding clinicians, developers, and researchers in maternity care.
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