Integrating patient voices into the extraction of social determinants of health from clinical notes: ethical considerations and recommendations

Identifying patients' social needs is a first critical step to address social determinants of health (SDoH)-the conditions in which people live, learn, work, and play that affect health. Addressing SDoH can improve health outcomes, population health, and health equity. Emerging SDoH reporting requirements call for health systems to implement efficient ways to identify and act on patients' social needs. Automatic extraction of SDoH from clinical notes within the electronic health record through natural language processing offers a promising approach. However, such automated SDoH systems could have unintended consequences for patients, related to stigma, privacy, confidentiality, and mistrust. Using Floridi et al's AI4People framework, we describe ethical considerations for system design and implementation that call attention to patient autonomy, beneficence, nonmaleficence, justice, and explicability. Based on our engagement of clinical and community champions in health equity work at University of Washington Medicine, we offer recommendations for integrating patient voices and needs into automated SDoH systems.

Automated summary

Identifying patients' social needs is crucial for addressing social determinants of health. Automated systems for extracting social determinants of health from clinical notes can offer promising solutions, but ethical considerations regarding stigma, privacy, and mistrust must be addressed. Integrating patient voices and needs into automated systems is recommended for ensuring patient autonomy and justice.