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156. Forecasting spinal deformity health care burden and operative utilization in the United States from 2015 to 2040: an epidemiological-based autoregressive integrated moving average (ARIMA) computation modeling.

Authors :
Kalakoti, Piyush
Menger, Richard P.
Hendrickson, Nathan R.
Shamrock, Alan
Eisenberg, Joshua M.
Saifi, Comron
Sciubba, Daniel M.
Schmidt, Meic H.
Pugely, Andrew J.
Source :
Spine Journal. Sep2019 Supplement, Vol. 19, pS75-S76. 2p.
Publication Year :
2019

Abstract

Spinal deformity constitutes a spectrum of disorders affecting the spinal curvature. Management of spinal deformities often involves multidisciplinary teams and can be resource intense in patients requiring a prompt surgical correction for axial stability. Operative management warrants adequate subspecialty (fellowship) training and expertise for optimized health care delivery. With recent advances in diagnostic modalities and operative techniques in conjunction with an aging population, assessing the current and forecasting the future impact of spinal deformity spectrums on health care can be beneficial for meticulous planning and resource allocation to meet rising demands, ensuring the future economic viability of these procedures in the setting of cost-containment reforms. To forecast the health care burden and socioeconomics of spinal deformity disorders in the United States from 2015 to 2040. Epidemiological-based, time-series forecasting. A total of 2,424,941 patients with underlying spinal deformity (based on extrapolated, weighted sampling across non-federal inpatient admissions). Forecasting crude estimates of hospitalization burden and socioeconomics [operative utilization, costs, length of stay (LOS)] related to spinal deformities in the US from 2015 to 2040. A time-series, computation modeling using autoregressive integrated moving average (ARIMA) and seasonal ARIMA algorithms were constructed to forecast the impact of spinal deformities on health care delivery and resource utilization until 2040. Modeling of annual estimates for forecasting analysis relied upon the epidemiological data obtained from the Healthcare Cost and Utilization (HCUP) national datasets [National Inpatient Sample 2001-2014]. All forecast estimates were compared to the baseline 2014 year and evaluated as a percent change in primary endpoints. Diagnostics for forecasting models were assessed prior to model selection. In 2030 and 2040, hospital admissions from spine deformities will increase by approximately 75% and 122% from their baseline 2014 crude admission rates. From 2014-2030, crude annual admissions related to scoliotic disorders will witness highest increment (+80.9%), followed by lordotic (+77%) and kyphotic (73.8%) disorders, respectively. Between 2030 and 2040, the crude annual admissions from lordotic disorders of the spine will surpass scoliosis by a 10-year cumulative net marginal increase of 3.72% (change in lordosis and scoliosis in 2040 from 2014: 131.34% and 131.54% respectively). The rate of surgical correction of deformity will outpace conservative management techniques and likely to see increases of 87.9% (in 2030) and 143% (in 2040) above 2014 rates. The cost of care will increase by 48% (2030) and 76% (2040) compared to 2014 estimates ($23,031) despite the decrease in LOS (−11.6% in 2030 and −18.1% in 2040 vs 5.54 days in 2040). The current investigation provides projection forecasting for various spectrums of spinal deformities and for operative spinal correction. The study notes that operative utilization for deformity surgery will outpace conservative strategies. From a policymaking perspective, the data call for preparedness in establishing focused fellowship curriculae for training the adequate number of orthopedic or neurosurgeons specializing in spine deformity surgery to meet the increasing demand, reducing access disparities, and appropriately allocating resources for optimized care. This abstract does not discuss or include any applicable devices or drugs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15299430
Volume :
19
Database :
Academic Search Index
Journal :
Spine Journal
Publication Type :
Academic Journal
Accession number :
138181051
Full Text :
https://doi.org/10.1016/j.spinee.2019.05.173