%0 Journal Article
%@ 2291-9694
%I JMIR Publications
%V 11
%N 
%P e37805
%T Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement
%A Tamang,Suzanne
%A Humbert-Droz,Marie
%A Gianfrancesco,Milena
%A Izadi,Zara
%A Schmajuk,Gabriela
%A Yazdany,Jinoos
%+ Division of Rheumatology, University of California, San Francisco, 10 Koret Way, Room K-219, San Francisco, CA, 94143, United States, 1 415 576 1000, jinoos.yazdany@ucsf.edu
%K clinical natural language processing
%K electronic health records
%K population health science
%K clinical decision support
%K information extraction
%D 2023
%7 3.1.2023
%9 Viewpoint
%J JMIR Med Inform
%G English
%X Experts have noted a concerning gap between clinical natural language processing (NLP) research and real-world applications, such as clinical decision support. To help address this gap, in this viewpoint, we enumerate a set of practical considerations for developing an NLP system to support real-world clinical needs and improve health outcomes. They include determining (1) the readiness of the data and compute resources for NLP, (2) the organizational incentives to use and maintain the NLP systems, and (3) the feasibility of implementation and continued monitoring. These considerations are intended to benefit the design of future clinical NLP projects and can be applied across a variety of settings, including large health systems or smaller clinical practices that have adopted electronic medical records in the United States and globally.
%M 36595345
%R 10.2196/37805
%U https://medinform.jmir.org/2023/1/e37805
%U https://doi.org/10.2196/37805
%U http://www.ncbi.nlm.nih.gov/pubmed/36595345