Commentary by Austin Jordan, Head of Data Science, AI and ML, at Apixio
“The healthcare industry generates a vast amount of data — 80% of which is unstructured and difficult for providers and health plans to leverage to improve patient outcomes. Generative AI could help solve this data problem with its ability to synthesize complex datasets and provide actionable insights.
When applied in healthcare, generative AI could streamline workflows and reduce administrative burdens by creating concise patient summaries for clinicians before and after visits. With generative AI’s ability to follow specific instructions combined with clinicians’ expertise, it also has the potential to improve the patient experience through tailored education. Instead of receiving a generic, boilerplate instruction manual for their treatment plans, patients could receive personalized, AI-generated instructions, educational videos, and summaries that are unique to their needs and health history.
We’re not there quite yet. Generative AI still makes mistakes and needs to be monitored to prevent bias and ensure data security — especially in healthcare, where the stakes are so high. We need to be careful that we don’t rush to use AI unsupervised in areas where mistakes can be catastrophic, like recommending the wrong dosage or frequency of a medication. But this new reality could be within reach sooner than many realize. AI has improved faster than many believed possible. If the algorithm’s output can be safeguarded via clinical expertise and introduced into healthcare in a way that supports clinicians, not replaces them, healthcare will become more personalized, effective, and accessible.”