012 - Providing meaningful information from social determinants of health data to inform policies to improve health

Background. As patients' social determinants of health (SDoH) data are increasingly collected in electronic health records (EHRs), they can potentially help providers tailor clinical recommendations for individuals who are at risk of negative health outcomes, facilitating referrals to community services. The National Academy of Medicine released recommendations on core measures of SDoH that should be documented in EHRs. However, the risk categories from these SDoH measures have not been investigated for their associations with health outcomes. To support meaningful use of the collected SDoH information, our aim was to investigate the added value of tracking SDoH information beyond routinely collected demographic information.

Methods. The eligible sample was composed of all adult patients (age 18 or older) who had a primary care provider in Mayo Clinic and responded to the SDoH questionnaire from July to December 2019 across Mayo Clinic campuses (MN, AZ, FL) and Mayo Clinic Health System (SE MN, SW MN, SW WI, and NW WI). Outcomes included any hospitalization and any emergency department (ED) visit in 2020, which were pulled from the medical records. Other outcomes included patient-reported feelings of depression and anxiety in 2020, which were reported in the current visit information (CVI) questionnaire. Patients who answered the enterprise-system-triggered SDoH questionnaire in the latter half of 2019 and CVI questionnaire in 2020 were included in the final sample.

Logistic regression models were estimated for each combination of the four outcomes and nine SDoH domains (i.e., alcohol use, financial resource strain, food insecurity, intimate partner violence, physical activity, social connections, feeling stressed, tobacco use, and transportation needs). While there were no missing data on the outcomes, missing data rates on the SDoH domains ranged from 1.7% to 42.6% (median=11.9%). Missing data were addressed via multiple imputation. The covariates included age, female, white race, Hispanic, being in committed relationship, education level, Charlson comorbidity index, and geocoded SDoH (i.e., area deprivation index). To address a time effect due to observations being collected at different times, the amount of time between SDoH answer date and either the last date of 2020 or date of death was used as an offset variable. An α level of 0.001 was used. We calculated the odds ratios (ORs) and interpreted ORs of 1.46 or greater to be meaningful.
Results. In our sample (N=159,258), 8.1% were hospitalized, 18.0% had ED visit, 7.5% reported depression, and 13.6% reported anxiety in 2020. Among those who were not-at-risk for each SDoH domain, the average proportion of patients experiencing hospitalization was 7.3%, 16.3% for ED visit, 6.4% for feeling depressed, and 11.44% for feeling anxious. The strongest predictors for ED visit were high-risk financial resource strain, food insecurity, and unmet transportation needs. The strongest predictor for hospital admission was physical inactivity in the prior year. In addition, feeling stressed followed by intimate partner violence were most predictive of feeling depressed or anxious. Social isolation was also significantly associated with feeling depressed. Being a heavy drinker, being at medium risk for financial resource strain, insufficient physical activity, moderate social isolation, and being a former smoker were not associated with any of the studied outcomes at a meaningful level.
Conclusions. Some risk categories predicted health outcomes, while others did not. Implications for further actions would be to provide alerts to providers and recommendations or referrals to community resources for patients emphasizing those SDoH domains that were found to be predictive of adverse outcomes. Future studies should investigate whether providing these recommendations and connecting patients with community resources is associated with improved patient outcomes.

Social determinants of health

electronic health records

patient-reported outcomes

provider-facing dashboard

risk categories

referrals to community resources 

Mid-Level

Community

International Conference on Health Policy Statistics 2023