Trends in Utilization of Large Databases in Spine Surgery Research from 2012 to 2022
Year: 2025
Type: article
Study design: Systematic Review
Abstract: Study Design: Systematic review. Objective: To evaluate large database studies across major spine surgery journals over time. Background: Orthopedic research output has increased in the past decade, partially due to large database studies. Although databases increase statistical power, variability in data encoding and lack of granularity are weaknesses. Materials and methods: Articles published (2012–2022) across Global Spine Journal (GSJ), Spine, The Spine Journal, International Journal of Spine Surgery, and Journal of Neurosurgery-Spine were analyzed. All studies were reviewed for use of the National Inpatient Sample, Centers for Medicare & Medicaid Service Data, National Surgical Quality Improvement Program, National Trauma Data Bank, PearlDiver, and IBM Market Scan. Studies were excluded if they were basic science/commentaries/letters-to-the-editor/systematic reviews or published as special issues/invited articles. Results: A total of 16,908 studies were included (409 large database studies). The publication rate of database studies changed significantly from 2012 to 2022 ( P < 0.001). The proportion of database studies from each journal changed significantly with a decrease from Spine (68.7%–29.5%) and increase from GSJ (0%–29.5%; P < 0.001). PearlDiver was the most utilized database overall, though NSQIP was the most used in GSJ ( P < 0.001). There was an increase in first authors with BS/BA degrees (22.4%–40.0%, P < 0.001) and number of affiliated institutions (2.30–3.44, P < 0.001). There were significant changes in 1 to 5 author works (37.7%–0%), and 16 to 20 (1.82%–14.7%) and 21+ (1.36%–16.5%) author works ( P < 0.001). The average number of citations to date per article was highest for TSJ ( P < 0.001). Conclusion: The use of large databases generally increased over the study period. The proportion of database studies from each journal shifted. Multi-institutional collaboration, increased author count, and inclusion of more junior first authors were observed. Given these trends, further investigation is needed to evaluate for heterogeneity, granularity, and potential over-powering of database studies. Level of evidence: Level III.
Source: Spine Open
Authors: Jonathan Dalton, Rajkishen Narayanan, Omar Tarawneh, Jarod Olson, Robert J. Oris, Yulia Lee, Mitchell Ng, William Green, Nicholas B. Pohl, Alec Giakas, Mark Miller, Matthew Meade, Grace Bowen, Jacob Fanizza, William Sutton, Zuhair Al-Bharani, Jose A. Canseco, Alan S. Hilibrand, Alexander R. Vaccaro, Gregory D. Schroeder, Christopher K. Kepler
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4415905953