Blending socioeconomic and geographic data with EHRs could offer new valuable insights for population health management, but first, the healthcare industry must standardize data collection and improve interoperability.
In a follow-up to a 2014 report issued by the President's Council of Advisors on Science and Technology on improving efficiency, productivity, and quality in healthcare, a commentary published in the American Journal of Public Health calls for the creation of community health records (CHRs) that contain defined “social, physical, and lifestyle determinants of health” within each community. By blending CHRs with the clinical data in EHRs, physicians would have access to a broad selection of data that would highlight high-risk populations.
For example, writes Deryk Van Brunt, an associate professor at the University of California Berkeley's School of Public Health, a physician caring for a single-parent pregnant woman living at or below the poverty level would know, based on CHR data, that the patient may not have access to transportation to receive routine prenatal screenings.
“Clinical transformation and community health professionals can work together to use CHR data to gain insights into the health of populations and to reengineer processes and factors that influence health and healthcare delivery,” Van Brunt wrote. “As organizations begin to take on increasingly more risk for the health of populations, … CHRs can be used, along with traditional clinical data, to prioritize areas of need, drive reengineering process improvement and improve health.”
As Michael Dulin, CCO for analytics and outcomes research at Carolinas HealthCare System, points out in a recent op-ed for CIO Review, adding data surrounding social determinants of health to claims and clinical data can be a key to improving population health efforts. In the future, he argues, EHR vendors will have to identify ways to integrate these data sets as clinicians seek additional insight into social and behavioral factors.
However, Van Brunt notes that there are significant barriers. Community data is poorly defined and lacks standardization, which leads to inefficient collection reporting efforts. Listed among his 14 recommendations for improving population health, Van Brunt called on the Office of the National Coordinator for Health IT to lead efforts to define community health standards and improve interoperability.
Although MACRA has placed more pressure on providers to use health IT systems to address population health issues, few are equipped to do so because they don’t account for outside factors such as housing, nutritional habits, and socioeconomic status. Recently, however, some health information exchanges have made strides to incorporate behavioral health data, while policy experts have urged the CMS to gather data on social risk factors among Medicare beneficiaries.