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Evaluation of Injury Recidivism Using the Electronic Medical Record
Peter J Abraham1, Mackenzie N Abraham1, Russell L Griffin1
1Department of Surgery, University of Alabama at Birmingham, Birmingham, AL.
Background:
Traumatic injuries remain one of the leading causes of death in the United States. Patients who survive traumatic injuries but return to the emergency department with repeat injuries are said to suffer from injury recidivism. Numerous studies have described trends in injury recidivism using trauma registry and survey data. To our knowledge, no prior study has leveraged electronic medical record (EMR) data to characterize injury recidivism. The EMR is potentially more comprehensive as it contains details of patients who visited the emergency department after injury but did not meet the criteria for inclusion in the trauma registry. Such injuries could be predictive of future recidivism. We therefore aimed to describe patterns of injury recidivism seen at a Level 1 trauma center using the EMR.
Methods:
A retrospective review was conducted of all injury-related encounters between January 2016 and December 2019. Manual review was conducted of all recidivistic encounters with < 11 months between encounters to ensure the recidivistic encounter was not a sequela of the index visit. A general estimating equation logistic regression adjusted for age, race, sex, and insurance payor, estimated odds ratios (ORs) and 95% confidence intervals (CIs) for the association between injury mechanism and odds of recidivistic encounter.
Results:
A total of 20,566 index encounters was included during the study period. Of the 20,566 encounters, 7.6% (n = 1570) had a recidivistic encounter during the study period, half of which (n = 781) occurred within the first year of the index encounter. An over two-fold increased odds of recidivism was observed for blunt assault encounters (OR 2.53, 95% CI 2.03-3.15) and unintentional falls (OR 2.10, 95% CI 1.76-2.52). For both mechanisms, this increase was observed across the three years following the index encounter.
Conclusions:
Our study found that patients with assault injuries have the highest odds of injury recidivism and assault-related recidivistic encounters. These results demonstrate the feasibility and utility of incorporating EMR data, and suggest that the development of targeted interventions focused on mitigating assault injuries, such as hospital-based violence intervention programs, should be considered in our region.
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