AUTHORS: Mariam Bibi, Manahill Baig, Joyce Atim
OBJECTIVES
Clinical decision support systems (CDSS) are crucial tools in modern healthcare, aiming to improve patient outcomes by providing evidence-based recommendations at the point of care. Traditionally, CDSS relied on pre-programmed guidelines. However, the integration of real-world data (RWD) from various sources is revolutionising CDSS development, enabling more personalised, data-driven decision-making.
METHODS
We reviewed sample patients with diabetes from EMR, claims data for patients with breast cancer and Melanoma registry data, exploring the CDSS for hypothetical patients.
RESULTS
The clinical decision support systems analyses the patients EMR data and suggests a treatment plan based on similar cases with successful outcomes. The patient claims data provides insights into population-level trends. For example, analysis of claims data reveals that a specific chemotherapy regimen leads to better survival rates among breast cancer patients. The CDSS utilises this data to recommend treatment options. Disease-specific registries tracked detailed data on specific patient populations. Consider a cancer registry that tracks immunotherapy outcomes for melanoma patients. The CDSS uses this data to predict the likelihood of response in new patients.
CONCLUSION
The future of RWD-powered clinical decision support systems is promising, with the integration of AI and machine learning for more precise predictions and personalised treatment plans. Ensuring interoperability between healthcare IT systems is essential for wider CDSS adoption. Data quality, standardisation, and privacy remain crucial considerations. Robust data security and adherence to privacy regulations are paramount. By harnessing the power of RWD, CDSS can evolve into dynamic tools that empower clinicians to make informed decisions, personalise care, and improve healthcare outcomes.
Read our full research below (available post-conference).
Plus, read our other research abstracts for ISPOR Europe 2024 here.