Predicting Discharge Disposition in Trauma Patients: Development, Validation, and Generalization of a Model Using the National Trauma Data Bank

Abstract

Background Limited work has been done in predicting discharge disposition in trauma patients; most studies use single institutional data and have limited generalizability. This study develops and validates a model to predict, at admission, trauma patients’ discharge disposition using NTDB, transforms the model into an easy-to-use score, and subsequently evaluates its generalizability on institutional data. Methods NTDB data were used to build and validate a binary logistic regression model using derivation-validation (ie, train-test) approach to predict patient disposition location (home vs non-home) upon admission. The model was then converted into a trauma disposition score (TDS) using an optimization-based approach. The generalizability of TDS was evaluated on institutional data from a single Level I trauma center in the U.S. Results A total of 614 625 patients in the NTDB were included in the study; 212 684 (34.6%) went to a non-home location. Patients with a non-home disposition compared to home had significantly higher age (69 ± 19.7 vs 48.3 ± 20.3) and ISS (11.2 ± 8.2 vs 8.2 ± 6.3); P < .001. Older age, female sex, higher ISS, comorbidities (cancer, cardiovascular, coagulopathy, diabetes, hepatic, neurological, psychiatric, renal, substance abuse), and Medicare insurance were independent predictors of non-home discharge. The logistic regression model’s AUC was 0.8; TDS achieved a correlation of 0.99 and performed similarly well on institutional data (n = 3161); AUC = 0.8. Conclusion We developed a score based on a large national trauma database that has acceptable performance on local institutions to predict patient discharge disposition at the time of admission. TDS can aid in early discharge preparation for likely-to-be non-home patients and may improve hospital efficiency.

Influence of socioeconomic factors on discharge disposition following traumatic cervicothoracic spinal cord injury at level I and II trauma centers in the United States

“…Our findings are consistent with the previously published literature related to insurance status and discharge disposition after trauma admissions [21] , [22] , [23] , [24] , [25] , [26] , [27] . In their 2011 article, Sacks et al.…”

“…Furthermore, we show that patients with severe ISS [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] , [26] were significantly associated with higher odds of non-home discharge compared to patients with minor ISS scores. In a single-institutional cohort study, Claridge et al.…”

“…Similarly, Graham et al. (2020) [21] studied the 2015 NTDB of all trauma patients. The group reported that uninsured patients were significantly less likely to have a non-home discharge (CI=0.42-0.46).…”

“…The NTDB defines home discharge disposition as return to the patient's current place of residence with or without at-home services. All other discharge dispositions were coded as non-home [21] .…”

Association between the participation of the plastic surgery department and qualitative prognoses in severe trauma patients: A retrospective observational study

“…Similarly, previous studies have argued that discharge disposition is affected by age, ISS, ICU LOS, and facial injuries. [ 12 , 13 ] The reason for the high rate of discharge to home in the PS group was that while this population usually suffered facial injuries, they could often ambulate. Therefore, it was difficult to conclude whether the patients’ satisfaction with PS was significantly high, as the rate of disability diagnosis was similar in both groups.…”