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Toward Understanding the Value of Missing Social Determinants of Health Data in Care Transition Planning
Sue S Feldman1, Ganisher Davlyatov1, Allyson G Hall1
1University of Alabama at Birmingham, Birmingham, Alabama, United States.
Background:
Social determinants of health play an important role in the likelihood of readmission and therefore should be considered in care transition planning. Unfortunately, some social determinants that can be of value to care transition planners are missing in the electronic health record. Rather than trying to understand the value of data that are missing, decision makers often exclude these data. This exclusion can lead to failure to design appropriate care transition programs, leading to readmissions.
Objectives:
This article examines the value of missing social determinants data to emergency department (ED) revisits, and subsequent readmissions.
Methods:
A deidentified data set of 123,697 people (18+ years), with at least one ED visit in 2017 at the University of Alabama at Birmingham Medical Center was used. The dependent variable was all-cause 30-day revisits (yes/no), while the independent variables were missing/nonmissing status of the social determinants of health measures. Logistic regression was used to test the relationship between likelihood of revisits and social determinants of health variables. Moreover, relative weight analysis was used to identify relative importance of the independent variables.
Results:
Twelve social determinants were found to be most often missing. Of those 12, only "lives with" (alone or with family/friends) had higher odds of ED revisits. However, relative logistic weight analysis suggested that "pain score" and "activities of daily living" (ADL) accounted for almost 50% of the relevance for ED revisits when compared among all 12 variables.
Conclusion:
In the process of care transition planning, data that are documented are factored into the care transition plan. One of the most common challenges in health services practice is to understand the value of missing data in effective program planning. This study suggests that the data that are not documented (i.e., missing) could play an important role in care transition planning as a mechanism to reduce ED revisits and eventual readmission rates.
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