Artificial intelligence (AI) is transforming workflows across industries, revolutionizing the way we work, solve problems, and innovate. In healthcare, AI tools continue to gain traction. Healthcare providers are finding innovative opportunities for AI-systems to optimize clinical workflows, enhance precision, promote efficiency, and improve patient outcomes.
By automating repetitive tasks, expediting decision-making, and streamlining complex processes, AI-powered tools can optimize clinical workflows, and empower healthcare providers to focus more on patient care.
Enhancing clinical workflows for medication safety
Medication errors remain one of the most significant challenges in patient safety—but the right tools can make a difference. Medical evidence continues to grow at an exponential pace. It’s become increasingly difficult for clinicians to quickly find the medication insights they need to make safe decisions for patients. Leveraging clinical decision support systems to provide the latest curated evidence, sourced from the world’s medical literature, ensures healthcare professionals will find accurate answers to support their decisions, even in complex patient care scenarios.
By pairing AI technology with the large content repositories underlying clinical decision support systems, critical insights can be delivered even faster, in a way that better supports the clinical workflow to accelerate decision-making. Applying AI technologies like large language models (LLMs) and machine learning to the search functionality within these trusted, high-quality datasets based on curated evidence is a game-changer. Especially in terms of boosting the “findability” of specific information needed to support medication safety.
Many of today’s tools offer generative AI driven, summarized answers that can eliminate multiple clicks, scrolls and reduce the cognitive burden of having to synthesize information from multiple documents. For example, a clinician looking for alternatives to a therapy that is not working or to discern which medication is best suited for a patient with multiple comorbid conditions.
Considerations for safe AI-powered clinical decision support solutions
Not all AI solutions are created equal. Close attention to how generative AI is leveraged, the underlying knowledge source and approach to clinical validation must be carefully considered when a tool will be used to inform patient care. Clinicians should be part of the development and continuous quality monitoring process.
Other AI applications in healthcare workflows
New use cases for AI continue to evolve, automating and simplifying tasks with a goal of freeing up clinician time for patient care. Click to read the full blog for 6 more examples of AI in clinical workflows, and what this means for the future of artificial intelligence in healthcare delivery.
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