Advanced Care Planning Content Encoding with Natural Language Processing.

While advanced care planning (ACP) is an essential practice for ensuring patient-centered care, its adoption remains poor and the completeness of its documentation variable. Natural language processing (NLP) approaches hold promise for supporting ACP, including its use for decision support to improve ACP gaps at the point of care. ACP themes were annotated on palliative care notes across four annotators (Fleiss kappa = 0.753) and supervised models trained (Huggingface models bert-base-uncased and Bio_ClinicalBERT) using 5-fold cross validation (F1=0.8, precision=0.75, recall=0.86, any theme). When applied across the full note corpus of 12,711 notes, we observed variability in documentation of ACP information. Our findings demonstrate the promise of NLP approaches for informatics-based approaches for ACP and patient-centered care.

Development and Usability Evaluation of an Opioid Management App.

We describe the development and usability evaluation of a novel patient engagement tool (OPY) in its early stage from perspectives of both experts and end-users. The tool is aimed at engaging patients in positive behaviors surrounding the use, weaning, and disposal of opioid medications in the post-surgical setting. The messaging and design of the application were created through a behavioral economics lens. Expert-based heuristic analysis and user testing were conducted and demonstrated that while patients found the tool to be easy to use and subjectively somewhat useful, additional work to enhance the user interface and features is needed in close partnership with developers and stakeholders.