Recently National Quality Forum released findings from a two-year trial to determine if social risk factors should be risk adjusted when determining outcomes. It appears that it may not be easy to obtain social factors.
A recent article highlights not only the social determinants of health, but also the ways in which these factors can be captured within electronic health records.
The risk adjustment process is a fairly new concept when it comes to predicting health outcomes. Although the social risk factors may seem to intuitively impact outcomes, the fact is, until various statistics are performed on a very large dataset, no one will really know the amount of impact each factor may or may not have on outcomes. Health care providers want as many variables as possible considered and included in a risk adjustment process to help level the playing field in upcoming alternative payment models focused on value.
FOTO recently analyzed an enormous amount of data to assess its risk adjustment process. The analysis led to improvement in its risk adjustment process. You can see how FOTO uses its risk adjustment process to compare and predict outcomes of care.
Below you will find a quick view of the abstract.
"Social determinants of heath" (SDHs) are nonclinical factors that profoundly affect health. Helping community health centers (CHCs) document patients' SDH data in electronic health records (EHRs) could yield substantial health benefits, but little has been reported about CHCs' development of EHR-based tools for SDH data collection and presentation.
We worked with 27 diverse CHC stakeholders to develop strategies for optimizing SDH data collection and presentation in their EHR, and approaches for integrating SDH data collection and the use of those data (eg, through referrals to community resources) into CHC workflows.
We iteratively developed a set of EHR-based SDH data collection, summary, and referral tools for CHCs. We describe considerations that arose while developing the tools and present some preliminary lessons learned.
Standardizing SDH data collection and presentation in EHRs could lead to improved patient and population health outcomes in CHCs and other care settings. We know of no previous reports of processes used to develop similar tools. This article provides an example of 1 such process. Lessons from our process may be useful to health care organizations interested in using EHRs to collect and act on SDH data. Research is needed to empirically test the generalizability of these lessons.
J Am Board Fam Med. 2017 Jul-Aug;30(4):428-447. doi: 10.3122/jabfm.2017.04.170046.