Developing a Predictive Tool for Hospital Discharge Disposition of Patients Poststroke with 30-Day Readmission Validation.
Developing a Predictive Tool for Hospital Discharge Disposition of Patients Poststroke with 30-Day Readmission Validation.
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DOI：
10.1155/2021/5546766
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发表时间：
2021
影响因子：
1.5
通讯作者：
Sartipi M
中科院分区：
文献类型：
--
作者：
Cho J;Place K;Salstrand R;Rahmat M;Mansouri M;Fell N;Sartipi M
在短期急性中风住院治疗后，患者可以出院回家或其他机构继续医疗或康复管理。急性期后护理的部位影响总体死亡率和功能结局。确定出院处置是医疗团队的一项复杂决策。早期预测出院目的地可以优化卒中后护理并改善预后。先前试图预测中风后出院处置结果的临床验证有限。在这项研究中，再入院状态被用来衡量出院处置预测的临床意义和有效性。低再入院率表明适当和彻底的护理与适当的出院处置。我们在分析中使用了从2014年和2015年基本索赔子集中获取的医疗保险受益人数据。创建了一个预测工具，以根据与调整后比值比相关的多变量logistic回归系数得出的风险评分确定出院处置。前五位风险评分分别是从专业护理机构入院、急性心脏病发作、脑出血、从“其他”来源入院和75岁或以上。使用再入院率完成预测工具的验证。75%的设施排放概率对应于大于9的风险评分。然后将预测结果与实际排放情况进行比较。对每个队列进行进一步分析，以确定每组中发生了多少次再入院。在实际的家庭排放中，95.7%预计会在那里。然而，只有47.8%的家庭出院预测实际出院回家。预测的设施排放量与实际设施排放量有15.9%的匹配。实际出院回家和预测出院到机构的情况表明，186例患者再次入院。在这种情况下，遵循算法将建议继续对这些患者进行医疗管理，可能会防止这些再入院。
After short-term, acute-care hospitalization for stroke, patients may be discharged home or other facilities for continued medical or rehabilitative management. The site of postacute care affects overall mortality and functional outcomes. Determining discharge disposition is a complex decision by the healthcare team. Early prediction of discharge destination can optimize poststroke care and improve outcomes. Previous attempts to predict discharge disposition outcome after stroke have limited clinical validations. In this study, readmission status was used as a measure of the clinical significance and effectiveness of a discharge disposition prediction. Low readmission rates indicate proper and thorough care with appropriate discharge disposition. We used Medicare beneficiary data taken from a subset of base claims in the years of 2014 and 2015 in our analyses. A predictive tool was created to determine discharge disposition based on risk scores derived from the coefficients of multivariable logistic regression related to an adjusted odds ratio. The top five risk scores were admission from a skilled nursing facility, acute heart attack, intracerebral hemorrhage, admission from “other” source, and an age of 75 or older. Validation of the predictive tool was accomplished using the readmission rates. A 75% probability for facility discharge corresponded with a risk score of greater than 9. The prediction was then compared to actual discharge disposition. Each cohort was further analyzed to determine how many readmissions occurred in each group. Of the actual home discharges, 95.7% were predicted to be there. However, only 47.8% of predictions for home discharge were actually discharged home. Predicted discharge to facility had 15.9% match to the actual facility discharge. The scenario of actual discharge home and predicted discharge to facility showed that 186 patients were readmitted. Following the algorithm in this scenario would have recommended continued medical management of these patients, potentially preventing these readmissions.
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