Assessing the quality of reporting of studies using Vascular Quality Initiative (VQI) data

The Society for Vascular Surgery Vascular Quality Initiative (VQI) has become an increasingly popular data source for retrospective observational vascular surgery studies. There are published guidelines on the reporting of data in such studies to promote transparency and rigor, but these have not been used to evaluate studies using VQI data. Our objective was to appraise the methodological reporting quality of studies using VQI data by evaluating their adherence to these guidelines.

The Society for Vascular Surgery VQI publication repository was queried for all articles published in 2020. The REporting of studies Conducted using Observational Routinely-collected Health Data (RECORD) statement and the Journal of American Medical Association-Surgical Section (JAMA-Surgery) checklist were utilized to assess the quality of each article's reporting. Five and three items from the RECORD statement and JAMA-Surgery checklist were excluded, respectively, because they were either inapplicable or nonassessable. Journal impact factor (IF) was queried for each article to elucidate any difference in reporting standards between high and low IF journals.

Ninety studies were identified and analyzed. The median score on the RECORD checklist was 6 (of 8). The most commonly missed item was discussing data cleaning methods (93% missed). The median score on the JAMA-Surgery checklist was 3 (of 7). The most commonly missed items were the identification of competing risks (98% missed), the use of a flow chart to clearly define sample exclusion and inclusion criteria (84% missed), and the inclusion of a solid research question and hypothesis (81% missed). There were no differences in JAMA-Surgery checklist or RECORD statement median scores among studies published in low vs high IF journals.

Studies using VQI data demonstrate a poor to moderate adherence to reporting standards. Key areas for improvement in research reporting include articulating a clear hypothesis, using flow charts to clearly define inclusion and exclusion criteria, identifying competing risks, and discussing data cleaning methods. Additionally, future efforts should center on creating tailored instruments to better guide reporting in studies using VQI data.