Cole A Bortz1, Peter G Passias1, Frank Segreto1, Samantha R Horn1, Virginie Lafage2, Justin S Smith3, Breton Line4, Gregory M Mundis5, Khaled M Kebaish6, Michael P Kelly7, Themistocles Protopsaltis1, Daniel M Sciubba8, Alexandra Soroceanu9, Eric O Klineberg10, Douglas C Burton11, Robert A Hart12, Frank J Schwab2, Shay Bess13, Christopher I Shaffrey3, Christopher P Ames14. 1. Department of Orthopedics, NYU Langone Orthopedic Hospital New York, New York. 2. Department of Orthopedics, Hospital for Special Surgery, New York, New York. 3. Department of Neurosurgery, University of Virginia, Charlottesville, Virginia. 4. International Spine Study Group, Denver, Colorado. 5. San Diego Center for Spinal Disorders, La Jolla, California. 6. Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland. 7. Department of Orthopaedic Surgery, Washington University, St. Louis, Missouri. 8. Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland. 9. Department of Orthopaedic Surgery, University of Calgary, Calgary, Alberta, Canada. 10. Department of Orthopedic Surgery, University of California, Davis, California. 11. Department of Orthopedic Surgery, University of Kansas Medical Center, Kansas City, Kansas. 12. Department of Orthopaedic Surgery, Swedish Neuroscience Institute, Seattle, Washington. 13. Rocky Mountain Scoliosis and Spine, Denver, Colorado. 14. Department of Neurological Surgery, University of California, San Francisco, California.
Abstract
BACKGROUND: Nonroutine discharge, including discharge to inpatient rehab and skilled nursing facilities, is associated with increased cost-of-care. Given the rising prevalence of cervical deformity (CD)-corrective surgery and the necessity of value-based healthcare, it is important to identify indicators for nonroutine discharge. OBJECTIVE: To identify factors associated with nonroutine discharge after CD-corrective surgery using a statistical learning algorithm. METHODS: A retrospective review of patients ≥18 yr with discharge and baseline (BL) radiographic data. Conditional inference decision trees identified factors associated with nonroutine discharge and cut-off points at which factors were significantly associated with discharge status. A conditional variable importance table used nonreplacement sampling set of 10 000 conditional inference trees to identify influential patient/surgical factors. The binary logistic regression indicated odds of nonroutine discharge for patients with influential factors at significant cut-off points. RESULTS: Of 138 patients (61 yr, 63% female) undergoing surgery for CD (8 ± 5 levels; 49% posterior approach, 16% anterior, and 35% combined), 29% experienced nonroutine discharge. BL cervical/upper-cervical malalignment showed the strongest relationship with nonroutine discharge: C1 slope ≥ 14°, C2 slope ≥ 57°, TS-CL ≥ 57°. Patient-related factors associated with nonroutine discharge included BL gait impairment, age ≥ 59 yr and apex of CD primary driver ≥ C7. The only surgical factor associated with nonroutine discharge was fusion ≥ 8 levels. There was no relationship between nonhome discharge and reoperation within 6 mo or 1 yr (both P > .05) of index procedure. Despite no differences in BL EQ-5D (P = .946), nonroutine discharge patients had inferior 1-yr postoperative EQ-5D scores (P = .044). CONCLUSION: Severe preoperative cervical malalignment was strongly associated with nonroutine discharge following CD-corrective surgery. Age, deformity driver, and ≥ 8 level fusions were also associated with nonroutine discharge and should be taken into account to improve patient counseling and health care resource allocation.
BACKGROUND: Nonroutine discharge, including discharge to inpatient rehab and skilled nursing facilities, is associated with increased cost-of-care. Given the rising prevalence of cervical deformity (CD)-corrective surgery and the necessity of value-based healthcare, it is important to identify indicators for nonroutine discharge. OBJECTIVE: To identify factors associated with nonroutine discharge after CD-corrective surgery using a statistical learning algorithm. METHODS: A retrospective review of patients ≥18 yr with discharge and baseline (BL) radiographic data. Conditional inference decision trees identified factors associated with nonroutine discharge and cut-off points at which factors were significantly associated with discharge status. A conditional variable importance table used nonreplacement sampling set of 10 000 conditional inference trees to identify influential patient/surgical factors. The binary logistic regression indicated odds of nonroutine discharge for patients with influential factors at significant cut-off points. RESULTS: Of 138 patients (61 yr, 63% female) undergoing surgery for CD (8 ± 5 levels; 49% posterior approach, 16% anterior, and 35% combined), 29% experienced nonroutine discharge. BL cervical/upper-cervical malalignment showed the strongest relationship with nonroutine discharge: C1 slope ≥ 14°, C2 slope ≥ 57°, TS-CL ≥ 57°. Patient-related factors associated with nonroutine discharge included BL gait impairment, age ≥ 59 yr and apex of CD primary driver ≥ C7. The only surgical factor associated with nonroutine discharge was fusion ≥ 8 levels. There was no relationship between nonhome discharge and reoperation within 6 mo or 1 yr (both P > .05) of index procedure. Despite no differences in BL EQ-5D (P = .946), nonroutine discharge patients had inferior 1-yr postoperative EQ-5D scores (P = .044). CONCLUSION: Severe preoperative cervical malalignment was strongly associated with nonroutine discharge following CD-corrective surgery. Age, deformity driver, and ≥ 8 level fusions were also associated with nonroutine discharge and should be taken into account to improve patient counseling and health care resource allocation.