Integrating BMJ Best Practice into a hospital clinical decision support system is associated with more accurate diagnoses and shorter hospital stays, finds a new study from China published in JMIR Medical Informatics.
BMJ Best Practice is a clinical decision support tool that gives healthcare professionals fast and easy access to the latest information when making diagnosis and treatment decisions. It draws on the latest evidence-based research, guidelines and expert opinion to give guidance on diagnosis, prognosis, treatment and prevention.
BMJ Best Practice is currently freely available to university medical departments across China to help healthcare professionals tackle challenges, such as the COVID-19 outbreak, as part of BMJ’s commitment to helping to create a healthier world.
Clinical decision support systems (CDSS) have been used for many years to improve healthcare decision-making and quality of patient care. More recently, the development of artificial intelligence (AI-based) systems have the potential to further improve diagnosis and treatment, but their use in “real-world” clinical practice remains controversial. So the researchers set out to assess the effects on patient care of implementing an AI-based clinical decision support system integrated with BMJ Best Practice at their hospital.
Their findings are based on diagnosis data for 34,113 hospital patients in six clinical departments from December 2016 to February 2019.
After CDSS implementation, the researchers found improved consistency between the admission and the discharge diagnoses (from 70% to 73%), shorter confirmed diagnosis times, and shorter average hospital stays (from 7 days to 6 days).
These results were similar after further analyses, indicating that BMJ Best Practice has a positive impact on patient outcomes.
These findings “highlight the utility of artificial intelligence-based CDSS to improve diagnosis efficiency, but these results require confirmation in future randomized controlled trials,” they conclude.
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