By Juliana Bunim | Originally published on UCSF News
The IOM committee, co-chaired by Nancy Adler, PhD, vice chair of the Department of Psychiatry at UC San Francisco and William Stead, MD, of Vanderbilt University, was created in 2013 to conduct a two-phase study, first to identify the social and behavioral areas that most strongly determine health, and then to evaluate the measures that can most effectively be used in EHRs. Kirsten Bibbins-Domingo, MD, of the UCSF Department of Medicine, also served on the committee.
The committee reviewed the evidence linking social conditions and health behaviors to health, which suggests that health behaviors such as alcohol use, and social conditions such as financial resource strain account for more than half of all premature deaths in the United States. They evaluated more than 70 relevant domains and subdomains, 17 of which were judged to be most valuable for inclusion in electronic health records.
“Having access to information about health-related aspects of a patient’s life in the electronic health record can enable clinicians to make more accurate diagnoses and engage more effectively with the patient in making treatment choices,” said Adler. “The information can also help health systems understand the needs of the populations they serve and design more effective services.”
The second phase of the report, published Nov. 13, details 12 social and behavioral factors that should be included in electronic health records.
The new report, Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2, recommends that providers use their EHRs to capture patients' census information including race, ethnicity and address, in addition to tracking alcohol use, tobacco use and exposure, physical activity, educational attainment, social connections, depression, stress, financial resource strain, neighborhood and community compositional characteristics and exposure to violence.
“When analyzed along with genomic and clinical data, standardized social and behavior information in EHRs can enable new discoveries regarding the etiology and progress of disease,” said Adler. “It can also point to the effectiveness of specific treatments for patients with different psychosocial and biological profiles.”
