SDoH-informed predictive models could improve patient engagement while alleviating physician burnout.

Physician burnout and SDoH: Letter to the editor

November 25, 2019
SDoH-informed predictive models could improve patient engagement while alleviating physician burnout.
Patricia Ingerick

This letter originally appeared in the September 2019 issue of the Journal of the American Board of Family Medicine in response to Physician Burnout and Higher Clinical Capacity to Address Patients’ Social Needs.

To the Editor:

Physician burnout is a critical issue that may affect patient safety1 and deserves appropriate attention across policy levels. The rate of reported physician burnout has increased in the past decade,2 likely due, at least in part, to the advent of value-based care, and the increased burden of documentation and reporting of quality metrics, for instance.

We read with interest the recent study3 that examined the association between physician burnout and the medical practices' capability to address social determinants of health (SDoH)-related barriers. We would like to offer a few additional comments that may support addressing this multipronged issue from a data and analytics perspective.

Having access to staff support to address SDoH-related challenges is important but only one part of the equation. For example, identifying an SDoH-related barrier is not always straightforward during the office visit. While SDoH information is now available from public resources as well as third-party commercial entities, provider-facing population health platforms reporting SDoH insights are only in their infancy. There are many reasons behind this.

Aggregating the information from public data is challenging as the information is dispersed among many resources. Its value is further limited by the fact that the data are typically available only at the group level, such as by zip code. However, some commercial sources do report SDoH at the individual patient level. The challenge here is the sensitivity of this information, which is sometimes perceived to be even more sensitive than healthcare data itself.

Even though patient privacy remains a concern, there are ways to blind the user from very detailed individual SDoH information. One very promising option is to use that data to inform predictive risk models. Such models would only report on the risk of a particular SDoH barrier (e.g., transportation, housing, food, and access to care) that would impact future need for care. SDoH-informed predictive models would only consume but not disclose specific and sensitive information (such as income, financial debt levels, or criminal history) to providers.

Another advantage to using SDoH-informed predictive models is to enable physicians and their support staff to gain greater actionable insights from SDoH data. For example, individual bits of data about a patient's income level or home address may not seem relevant to a patient's care and therefore become yet more data the physician needs to wade through. Conversely, when a physician sees an elevated aggregated SDoH risk score for a patient, it could encourage conversation between the patient and physician, which may lead to greater patient engagement and a physician focused more on the patient than the data.

SDoH are top of mind in U.S. healthcare today, as increased awareness and policy changes could potentially help address disparities in healthcare, reduce overall healthcare costs and ultimately improve patient health outcomes.4 Using appropriately aggregated data may help facilitate applicable interventions. As De Marchis et al3 argue, it is now apparent that patients are not the only ones who may benefit from data-driven social and health interventions. Physicians will benefit as well, as having access to SDoH driven insights may reduce physician burnout and help restore the joy of medicine to many practicing providers.



  1. Panagioti M, Geraghty K, Johnson J, et al. Association Between Physician Burnout and Patient Safety, Professionalism, and Patient Satisfaction: A Systematic Review and Meta-analysis. JAMA Intern Med 2018;178:1317–30.
  2. The Physicians Foundation. The Physicians Foundation 2018 Physician Survey. Available from: Retrieved on March 19, 2019.
  3. De Marchis E, Knox M, Hessler D, et al. Physician burnout and higher clinic capacity to address patients' social needs. J Am Board Fam Med 2019;32:69–78.
  4. Thornton RL, Glover CM, Cené CW, Glik DC, Henderson JA, Williams DR. Evaluating strategies for reducing health disparities by addressing the social determinants of health. Health Aff (Millwood) 2016;35:1416–23.