Pre-Operative Predictors for Discharge to Post-Acute Care Facilities After Total Knee Arthroplasty

被引:9
作者
Zeng, Chan [1 ]
Koonce, Ryan C. [2 ]
Tavel, Heather M. [1 ]
Argosino, Suzanne E. [3 ]
Kiepe, Denise A. [3 ]
Lyons, Ella E. [1 ]
Ford, Morgan A. [1 ]
Steiner, Claudia A. [1 ,4 ]
机构
[1] Kaiser Permanente Colorado, Inst Hlth Res, 2550 S Parker Rd,Suite 200, Aurora, CO 80014 USA
[2] Univ Colorado, Sch Med, Dept Orthoped Surg, Highlands Ranch, CO USA
[3] Kaiser Permanente Colorado, Orthoped Dept, Denver, CO USA
[4] Colorado Permanente Med Grp, Denver, CO USA
关键词
total knee arthroplasty; total joint arthroplasty; predictive model or tool; discharge disposition; post-acute care facility; rehabilitation; TOTAL JOINT ARTHROPLASTY; RISK-FACTORS; DESTINATION; HIP; REHABILITATION; DISPOSITION; OUTCOMES; MODELS; TRENDS; COSTS;
D O I
10.1016/j.arth.2021.09.019
中图分类号
R826.8 [整形外科学]; R782.2 [口腔颌面部整形外科学]; R726.2 [小儿整形外科学]; R62 [整形外科学(修复外科学)];
学科分类号
摘要
Background: Joint replacement surgery is in increasing demand and is the most common inpatient surgery for Medicare beneficiaries. The venue for post-operative rehabilitation, including early outpatient therapy after surgery, influences recovery and quality of life. As part of a comprehensive total joint program at Kaiser Permanente Colorado, we developed and validated a predictive model to anticipate and plan the disposition for rehabilitation of our patients after total knee arthroplasty (TKA). Methods: We analyzed data for TKA patients who completed a pre-operative Total Knee Risk Assessment in 2017 (the model development cohort) or during the first 6 months of 2018 (the model validation cohort). The Total Knee Risk Assessment, which is used to guide disposition for rehabilitation, included questions in mobility, social, and environment domains. Multivariable logistic regression was used to predict discharge to post-acute care facilities (PACFs) (ie, skilled nursing facilities or acute rehabilitation centers). Results: Data for a total of 1481 and 631 patients who underwent TKA were analyzed in the development and validation cohorts, respectively. Ninety-three patients (6.3%) in the development cohort and 22 patients (3.5%) in the validation cohort were discharged to PACFs. Eight risk factors for discharge to PACFs were included in the final multivariable model. Patients with a diagnosis of neurological disorder and with a mobility/balance issue had the greatest chance of discharge to PACFs. Conclusion: This validated predictive model for discharge disposition following TKA may be used as a tool in shared decision-making and discharge planning for patients undergoing TKA. (c) 2021 Elsevier Inc. All rights reserved.
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页码:31 / +
页数:10
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