Structural equation model analysis of the length-of-hospital stay after lumbar spine surgery

Background contextLength-of-hospital stay (LOS) after lumbar spine surgery (LSS) can be affected by many factors. However, few studies have evaluated predictors of LOS, and all have used limited number of variables as predictors.PurposeThe purpose of the study was to identify presurgical, surgical, and postsurgical predictors of LOS after LSS.Study design/settingRetrospective review of consecutive patients who had LSS at the University of Kansas Hospital from October 2008 to April, 2012.Patient sampleFive hundred ninety-three patients underwent LSS consisting of laminotomy, laminectomy, or arthrodesis.Outcome measuresDependent variable: LOS. Multiple presurgical, surgical, and postsurgical variables were extracted from the patients' medical records and considered as possible predictors (independent variables) of LOS.MethodsPotential predictors that were significantly correlated with LOS were used as indicators to construct three latent factors presurgical, surgical, and postsurgical, which were in turn used to predict LOS in a structural equation model.ResultsThe average LOS was 4.01±2.73 days. The presurgical factor was indicated by age (61.97±14.49 years), previous level of function (60.5% were totally independent), previous hemoglobin level (13.70±1.36 mg/dL), and use of assistive devices (60% were assistive device users). The surgical factor was indicated by severity of illness (50.2% had minor disease severity), presence of complications (1.9%), and stay in an intensive care unit (4.0%). The postsurgical factor was indicated by postsurgical walking distance (166.43±175.75 ft), level of assistance during walking (5.18±0.81 out of 7 points), balance scores (6.18±1.82 out of 10 points), and bed mobility and transfer dependency scores (9.81±1.99 out of 14 points). These three latent factors explained 47% of variation in LOS.ConclusionsPostsurgical factors predicted the highest variation in LOS in comparison with presurgical and surgical factors and should be taken into consideration for discharge planning. Postsurgical factors are related to the patient's function, modifiable with rehabilitation, and can be improved to shorten LOS. Inclusion of more reliable and standardized presurgical variables could improve the predictability of the model.