Automating data collection methods in electronic health record systems: a Social Determinant of Health (SDOH) viewpoint

Health Syst (Basingstoke). 2022 May 19;12(4):472-480. doi: 10.1080/20476965.2022.2075796. eCollection 2023.

Abstract

Social Determinant of Health (SDOH) data are important targets for research and innovation in Health Information Systems (HIS). The ways we envision SDOH in "smart" information systems will play a considerable role in shaping future population health landscapes. Current methods for data collection can capture wide ranges of SDOH factors, in standardised and non-standardised formats, from both primary and secondary sources. Advances in automating data linkage and text classification show particular promise for enhancing SDOH in HIS. One challenge is that social communication processes embedded in data collection are directly related to the inequalities that HIS attempt to measure and redress. To advance equity, it is imperative thatcare-providers, researchers, technicians, and administrators attend to power dynamics in HIS standards and practices. We recommend: 1. Investing in interdisciplinary and intersectoral knowledge generation and translation. 2. Developing novel methods for data discovery, linkage and analysis through participatory research. 3. Channelling information into upstream evidence-informed policy.

Keywords: Social Determinants of Health; big data; digital transformation; electronic health records; health equity; population health; precision medicine.

Publication types

  • Review

Grants and funding

This work was supported by the Canadian Institute of Health Research(CIHR) grant 397824 Data collection initiative using artificially intelligent technology for social determinants and risk factors surveillance.