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俄克拉荷马州重大创伤患者出院目的地预测模型的验证:一项横断面研究。

Validation of the Oklahoma predictor model for discharge destination in patients with major traumatic injury: a cross-sectional study.

作者信息

Alvarado Aaron, Nguyen Vivian, Cox Bradley, Esparham Ali, Charles Michael, Mushtaq Nasir, Chow Geoffrey, Khorgami Zhamak

机构信息

Department of Surgery, University of Oklahoma School of Community Medicine - Tulsa, 4444 41st St, Suite #1700, Tulsa, OK, 74135, USA.

School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.

出版信息

Eur J Trauma Emerg Surg. 2025 Jul 21;51(1):256. doi: 10.1007/s00068-025-02925-4.

Abstract

PURPOSE

Protracted in-patient stays affect trauma patient costs and hospital resource utilizations. Proper discharge placement stratification may help with early discharge planning in this group of patients. No standardized discharge destination prediction model exists. A scoring model has been developed after examining Oklahoma Trauma Database discharge destination predictors. This study's goal was patient data-driven model validation.

METHODS

Level II trauma center patient data over three months, including comorbidities, injuries, and demographics were analyzed. We compared the scoring model discharge destination prediction with actual destinations.

RESULTS

The study included 459 patients, with 108 facility discharges. The scoring model demonstrated significant facility placement prediction (Scores ≤ 7: 11.94% or Negative Predictive Value of 88.1%; Score 8-14: 47.22% as Positive Predictive Value: and Score ≥ 15: 60.00%). Scoring 8-14 showed a 6.60-fold (95%CI: 4.11, 10.61) increase compared to ≤ 7. Scoring ≥ 15 was 11.07 times (95%CI: 1.79, 68.42) more likely than ≤ 7.

CONCLUSION

The Oklahoma Trauma Discharge Predictive Scoring Model demonstrated significant facility discharge prediction and may assist with decreasing delay of anticipated patient discharge destination.

摘要

目的

长期住院会影响创伤患者的费用及医院资源利用情况。合理的出院安置分层有助于该类患者的早期出院规划。目前尚无标准化的出院目的地预测模型。在对俄克拉荷马创伤数据库出院目的地预测因素进行研究后,开发了一种评分模型。本研究的目标是对基于患者数据的模型进行验证。

方法

分析了二级创伤中心三个月内患者的数据,包括合并症、损伤情况及人口统计学信息。我们将评分模型对出院目的地的预测结果与实际目的地进行了比较。

结果

该研究纳入了459例患者,其中108例从医疗机构出院。评分模型显示出对医疗机构安置的显著预测能力(评分≤7分:11.94%或阴性预测值为88.1%;评分8 - 14分:阳性预测值为47.22%;评分≥15分:60.00%)。评分8 - 14分与≤7分相比增加了6.60倍(95%置信区间:4.11,10.61)。评分≥15分比≤7分的可能性高11.07倍(95%置信区间:1.79,68.42)。

结论

俄克拉荷马创伤出院预测评分模型显示出对医疗机构出院的显著预测能力,可能有助于减少预期患者出院目的地的延迟。

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