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KMID : 0359620180300010050
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Journal of Korean Knee Society
2018 Volume.30 No. 1 p.50 ~ p.57
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Using Illness Rating Systems to Predict Discharge Location Following Total Knee Arthroplasty
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Rudasill Sarah
Dattilo Jonathan R.
Liu Jiabin
Clements Ari
Nelson Charles L.
Kamath Atul F.
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Abstract
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Purpose: Total knee arthroplasty (TKA) is increasing in frequency and cost. Optimization of discharge location may reduce total expenditure while maximizing patient outcomes. Although preoperative illness rating systems?including the American Society for Anesthesiologists Physical Classification System (ASA), severity of illness scoring system (SOI), and Mallampati rating scale (MP)?are associated with patient morbidity and mortality, their predictive value for discharge location, length of stay (LOS), and total costs remains unclear.
Materials and Methods: We conducted a retrospective analysis of 677 TKA patients (550 primary and 127 revision) treated at a single institution. The influence of ASA, SOI, and MP scores on discharge locations, LOS, and total costs was assessed using multivariable regression analyses.
Results: None of the systems were significant predictors of discharge location following TKA. SOI scores of major or higher (β=2.08 days, p＜0.001) and minor (β=?0.25 days, p=0.009) significantly predicted LOS relative to moderate scores. Total costs were also significantly predicted by SOI scores of major or higher (β=$6,155, p=0.022) and minor (β=?$1,163, p=0.007).
Conclusions: SOI scores may be harnessed as a predictive tool for LOS and total costs following TKA, but other mechanisms are necessary to predict discharge location.
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KEYWORD
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Knee, Osteoarthritis, Arthroplasty
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