Institutional databases may underestimate the risk factors for 30-day unplanned readmissions compared to national databases
Journal of Neurosurgery: Spine, ISSN: 1547-5646, Vol: 33, Issue: 6, Page: 845-853
2020
- 4Citations
- 9Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations4
- Citation Indexes4
- CrossRef3
- Captures9
- Readers9
Article Description
OBJECTIVE The 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. METHODS The 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. RESULTS Among 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. CONCLUSIONS Overall, 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.
Bibliographic Details
Journal of Neurosurgery Publishing Group (JNSPG)
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