Simple and actionable preoperative prediction of postoperative healthcare needs of single-level lumbar fusion patients

Austin J. BorjaDepartment of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia;

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Ali S. FarooqiDepartment of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia;

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Joshua L. GolubovskyDepartment of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia;

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Gregory GlauserDepartment of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia;

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Krista StrouzMcKenna EpiLog Fellowship in Population Health, University of Pennsylvania, Philadelphia; and

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Jan-Karl BurkhardtDepartment of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia;

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Scott D. McClintockThe West Chester Statistical Institute and Department of Mathematics, West Chester University, West Chester, Pennsylvania

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Neil R. MalhotraDepartment of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia;
McKenna EpiLog Fellowship in Population Health, University of Pennsylvania, Philadelphia; and

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OBJECTIVE

Preoperative prediction of a patient’s postoperative healthcare utilization is challenging, and limited guidance currently exists. The objective of the present study was to assess the capability of individual risk-related patient characteristics, which are available preoperatively, that may predict discharge disposition prior to lumbar fusion.

METHODS

In total, 1066 consecutive patients who underwent single-level, posterior-only lumbar fusion at a university health system were enrolled. Patients were prospectively asked 4 nondemographic questions from the Risk Assessment and Prediction Tool during preoperative office visits to evaluate key risk-related characteristics: baseline walking ability, use of a gait assistive device, reliance on community supports (e.g., Meals on Wheels), and availability of a postoperative home caretaker. The primary outcome was discharge disposition (home vs skilled nursing facility/acute rehabilitation). Logistic regression was performed to analyze the ability of each risk-related characteristic to predict likelihood of home discharge.

RESULTS

Regression analysis demonstrated that improved baseline walking ability (OR 3.17), ambulation without a gait assistive device (OR 3.13), and availability of a postoperative home caretaker (OR 1.99) each significantly predicted an increased likelihood of home discharge (all p < 0.0001). However, reliance on community supports did not significantly predict discharge disposition (p = 0.94).

CONCLUSIONS

Patient mobility and the availability of a postoperative caretaker, when determined preoperatively, strongly predict a patient’s healthcare utilization in the setting of single-level, posterior lumbar fusion. These findings may help surgeons to streamline preoperative clinic workflow and support the patients at highest risk in a targeted fashion.

ABBREVIATIONS

EHR = electronic health record; RAPT = Risk Assessment and Prediction Tool; SNF = skilled nursing facility.
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Images from Gami et al. (pp 713–721).

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