Discovery of Serious Illness Conversations
Communication that clarifies patient care preferences is widely endorsed as an indicator of care quality in frail and seriously ill patients. Routine assessment of these conversations is nearly impossible because the information is embedded as free-text within clinical notes.
We team with patient partners to pilot the implementation of existing National Quality Forum (NQF) endorsed measures using advanced computational methods. We have developed text processing algorithms that can identify the documentation of goals of care conversations in electronic health record.
Requires that the patient’s values, in the form of care preferences, are documented and properly disseminated to the entire clinical care team.
While it is vital that the care team knows these preferences, it is equally important that the patients, and the patients’ family, are confident that the clinicians involved understand, and will follow through with, those preferences.
the neural network
This computational method for finding documentation of patient care preferences decreases the amount of time spent by clinicians manually uncovering these care preferences, so we can increase the time clinicians can spend working directly with patients.
Patients will find themselves being equal partners in our attempt to discover the most modern methods available ensure their physical, emotional, and spiritual needs are met.