How Machine Learning is Transforming Clinical Decision Support Tools

With the right data, integration methods, and personnel in place, machine learning has the potential to advance clinical decision support and help providers deliver optimal care. In the era of value-based healthcare, digital innovation, and big data, clinical decision support systems have become vital for organizations seeking to improve care delivery. Clinical decision support (CDS) tools have the ability to analyze large volumes of data and suggest next steps for treatment, flagging potential problems and enhancing care team efficiency. While these systems can add significant value to the healthcare industry, CDS technologies have also come with substantial challenges. Poorly implemented CDS tools that generate unnecessary alerts often result in alarm fatigue and clinician burnout, trends that can threaten patient safety and lead to worse outcomes.