A team of six Stanford University scientists has used artificial intelligence to predict when people will die in order to improve access to palliative care, or specialized care for patients with particularly serious illnesses.
Currently, less than half of the 7 to 8 percent of individuals admitted to a hospital who need palliative care receive it, according to a report about the study written by Anand Avati and Andrew Ng from the Stanford Department of Computer Science; Kenneth Jung, Lance Downing, and Nigam H. Shah from the Stanford Center for Biomedical Informatics Research; and Stephanie Harmon, from the Stanford University School of Medicine.
Human physicians tend to be overly optimistic about whether and how long a patient will live, according to the brief. Also, Palliative caregivers and resources are limited. So to help increase access to care for those who would most benefit, the the Stanford team used artificial intelligence to identify patients who are likely to die between three and 12 months out.
If a patient is going to die in under three months, a palliative care team does not have enough preparatory time to administer the program. If a patient is predicted to die after 12 months, it is harder to accurately predict a time of death, the report says.
Typically, physicians review the chart for every new hospital case to determine whether a patient is eligible for palliative care. That's time consuming and doctors' personal biases can affect care decisions.
"Our predictions enable the palliative care team to take a proactive approach in reaching out to such patients," the report says, and provides "an objective recommendation based on the patient's EHR (electronic health records)."