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

Mitchell Graham, Pratik Parikh, Sagar Hirpara, Mary C. McCarthy, Elliott R. Haut, Priti P. Parikh

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)1703-1709
Number of pages7
JournalAmerican Surgeon
Volume86
Issue number12
DOIs
StatePublished - Dec 2020

Keywords

  • Discharge planning in trauma
  • Trauma disposition
  • discharge location in trauma patients
  • early discharge planning
  • predicting discharge disposition
  • trauma patient discharge

ASJC Scopus subject areas

  • Surgery

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