Back to Authors

Kurian, Shyam J.

https://orcid.org/0000-0003-2656-2522

Mayo Clinic

Mayo Clinic

Citations 3

Deep Learning for Radiographic Measurement of Femoral Component Subsidence Following Total Hip Arthroplasty
Rouzrokh, Pouria , Wyles, Cody C. , Kurian, Shyam J. , Ramazanian, Taghi , Cai, Jason , Huang, Qiao , Zhang, Kuan , Kremers, Hilal Maradit , Erickson, Bradley J. , Maradit Kremers, Hilal , Erickson, Bradley J , Wyles, Cody C , Rouzrokh, Pouria , Taunton, Michael J.

Radiology: Artificial Intelligence | May 4, 2022 | Volume: 4 | Issue: 3 | Pages: No page available

10.1148/ryai.210206 Get It

Do all outpatient spine surgeries cost the same? Comparison of economic outcomes data from a state-level database for outpatient lumbar decompression performed in an ambulatory surgery center or hospital outpatient setting
Alvi, Mohammed Ali , Wahood, Waseem , Kurian, Shyam J. , Zreik, Jad, Jeffery, Molly M. , Naessens, James M. , Spinner, Robert J. , Bydon, Mohamad , Jeffery, Molly Moore , Alvi, Mohammed Ali

Journal of Neurosurgery: Spine | September 3, 2021 | Volume: 35 | Issue: 6 | Pages: 787-795

10.3171/2021.2.spine201820 Get It

OBJECTIVE Spinal procedures are increasingly conducted as outpatient procedures, with a growing proportion conducted in ambulatory surgery centers (ASCs). To date, studies reporting outcomes and cost analyses for outpatient spinal procedures in the US have not distinguished the various outpatient settings from each other. In this study, the authors used a state-level administrative database to compare rates of overnight stays and nonroutine discharges as well as index admission charges and cumulative 7-, 30-, and 90-day charges for patients undergoing outpatient lumbar decompression in freestanding ASCs and hospital outpatient (HO) settings. METHODS For this project, the authors used the Florida State Ambulatory Surgery Database (SASD), offered by the Healthcare Cost and Utilization Project (HCUP), for the years 2013 and 2014. Patients undergoing outpatient lumbar decompression for degenerative diseases were identified using CPT (Current Procedural Terminology) and ICD-9 codes. Outcomes of interest included rates of overnight stays, rate of nonroutine discharges, index admission charges, and subsequent admission cumulative charges at 7, 30, and 90 days. Multivariable analysis was performed to assess the impact of outpatient type on index admission charges. Marginal effect analysis was employed to study the difference in predicted dollar margins between ASCs and HOs for each insurance type. RESULTS A total of 25,486 patients were identified; of these, 7067 patients (27.7%) underwent lumbar decompression in a freestanding ASC and 18,419 (72.3%) in an HO. No patient in the ASC group required an overnight stay compared to 9.2% (n = 1691) in the HO group (p < 0.001). No clinically significant difference in the rate of nonroutine discharge was observed between the two groups. The mean index admission charge for the ASC group was found to be significantly higher than that for the HO group ($35,017.28 ± $14,335.60 vs $33,881.50 ± $15,023.70; p < 0.001). Patients in ASCs were also found to have higher mean 7-day (p < 0.001), 30-day (p < 0.001), and 90-day (p = 0.001) readmission charges. ASC procedures were associated with increased charges compared to HO procedures for patients on Medicare or Medicaid (mean index admission charge increase $4049.27, 95% CI $2577.87–$5520.67, p < 0.001) and for patients on private insurance ($4775.72, 95% CI $4171.06–$5380.38, p < 0.001). For patients on self-pay or no charge, a lumbar decompression procedure at an ASC was associated with a decrease in index admission charge of −$10,995.38 (95% CI −$12124.76 to −$9866.01, p < 0.001) compared to a lumbar decompression procedure at an HO. CONCLUSIONS These “real-world” results from an all-payer statewide database indicate that for outpatient spine surgery, ASCs may be associated with higher index admission and subsequent 7-, 30-, and 90-day charges. Given that ASCs are touted to have lower overall costs for patients and better profit margins for physicians, these analyses warrant further investigation into whether this cost benefit is applicable to outpatient spine procedures.
Institutional databases may underestimate the risk factors for 30-day unplanned readmissions compared to national databases
Kurian, Shyam J. , Yolcu, Yagiz U. , Zreik, Jad, Alvi, Mohammed Ali , Freedman, Brett A. , Bydon, Mohamad , Yolcu, Yagiz Ugur, Alvi, Mohammed Ali

Journal of Neurosurgery: Spine | July 31, 2020 | Volume: 33 | Issue: 6 | Pages: 845-853

10.3171/2020.5.spine20395 Get It

OBJECTIVEThe National Surgical Quality Improvement Program (NSQIP) and National Readmissions Database (NRD) are two widely used databases for research studies. However, they may not provide generalizable information in regard to individual institutions. Therefore, the objective of the present study was to evaluate 30-day readmissions following anterior cervical discectomy and fusion (ACDF) and posterior lumbar fusion (PLF) procedures by using these two national databases and an institutional cohort.METHODSThe NSQIP and NRD were queried for patients undergoing elective ACDF and PLF, with the addition of an institutional cohort. The outcome of interest was 30-day readmissions following ACDF and PLF, which were unplanned and related to the index procedure. Subsequently, univariable and multivariable analyses were conducted to determine the predictors of 30-day readmissions by using both databases and the institutional cohort.RESULTSAmong all identified risk factors, only hypertension was found to be a common risk factor between NRD and the institutional cohort following ACDF. NSQIP and the institutional cohort both showed length of hospital stay to be a significant predictor for 30-day related readmission following PLF. There were no overlapping variables among all 3 cohorts for either ACDF or PLF. Additionally, the national databases identified a greater number of risk factors for 30-day related readmissions than did the institutional cohort for both procedures.CONCLUSIONSOverall, significant differences were seen among all 3 cohorts with regard to top predictors of 30-day unplanned readmissions following ACDF and PLF. The higher quantity of significant predictors found in the national databases may suggest that looking at single-institution series for such analyses may result in underestimation of important variables affecting patient outcomes, and that big data may be helpful in addressing this concern.