Social Determinants of Health: APCD and Hospital Discharge Data Standards and Collection Practices

APCD Council

The full article is available here.


APCD and HDD programs’ data collection (and quality) typically reflect standard medical and pharmacy insurance electronic data interchange transactions with exceptions often due to data collection requirements in state law or regulation. However, industry stakeholders exchanging data might have different business needs, incentives, and methods for data storage. Health data organizations should not expect that including demographic and social determinants of health (SDoH) data elements in data submission guidance is sufficient to collect useful data, and must strike a balance between the need for demographics and SDoH data to support innovative analyses of health equity and disparities, and alignment with national standards that were not developed specifically for public health.

Based on these findings come the following recommendations: 

  1. Whenever possible, health data programs should leverage industry standards for exchanging health data.

    Where the relevant industry standards come up short (e.g., X12 transactions missing SOGI data), there is an opportunity to plan for or pursue the collection of data elements using alternate standards that are more complete, although that may require accepting data from a different origin point or source. There should also be an ongoing effort to encourage data standards maintenance organizations to address any shortcomings that limit the usefulness of the standards.
  2. Health data programs should build the functionality in the system during implementation that accommodates secondary data or build functionality in processes that anticipate change in the future.

    There are opportunities to collect reliable demographic and SDoH data from other sources. Health data systems should be technically compatible with a broad range of data sources.
  3. APCD and HDD programs should consider aggregate data for small geography (e.g., Census tracts or blocks) for imputation while being mindful of limitations.


This paper was funded partly by a research and evaluation project commissioned by the California Department of Health Care Access and Information.

Publication Authors
Charles Hawley, Bethany Swanson, Amy Costello, Jo Porter, and Norm Thurston