Optimal surgical planning and decision making surrounding surgical interventions requires patient-specific risk assessment which incorporates patient pre-operative clinical assessment and clinical literature. In this paper, we utilized population-based data analysis to construct surgical outcome predictive models for spinal fusion surgery using hospital, patient and admission characteristics. We analyzed population data from the Nationwide Inpatient Sample (NIS) -a nationally representative database- to identify data elements affecting inpatient mortality, length of stay, and disposition status for patients receiving spinal fusion surgery in the years 2004-2008. In addition to outcomes assessment, we want to make the analytic model results available to clinicians and researchers for pre-operative surgical risk assessment, hospital resource allocation, and hypothesis generation for future research without an individual patient data management burden. Spinal fusion was the selected prototype procedure due to it being a high volume and typically inpatient procedure where patient risk factors will likely affect clinical outcomes.
|Original language||English (US)|
|Number of pages||10|
|State||Published - 2012|