A metaresearch study finds unclear impact of institutional conflicts of interest on conclusions of studies investigating volume–outcome relationships
Bibliographic record
Abstract
OBJECTIVES: This study aimed to explore institutional conflicts of interest (COIs) in volume-outcome studies investigating whether higher hospital volume is associated with better patient outcomes. STUDY DESIGN AND SETTING: We used a sample of studies (n = 68) included in a systematic review on the hospital volume-outcome relationship in total knee arthroplasty. For studies in which at least one of the study authors was affiliated with a hospital, we contacted the study authors by email to obtain their institutional volume and to survey them about their opinion on institutional COIs. We categorized the studies' conclusions (positive vs nonpositive) and authors' hospital volume (high, intermediate, low). We compared conclusions for high- vs intermediate-/low-hospital volume categories. RESULTS: Of the 29 hospital-affiliated authors contacted, 20 replied. Authors from high-volume institutions were more likely to conclude that a hospital volume-outcome relationship existed compared to authors from intermediate- or low-volume institutions, although this was not statistically significant (odds ratio, 2.0; 95% CI: 0.21-18.7). Six out of 17 authors (35%) believed that institutional factors such as the case volume were (very) likely to influence the study design, analysis, or conclusions of research in the field of volume-outcome studies; four of 17 (24%) were neutral; and seven of 17 (41%) believed that this was (very) unlikely. CONCLUSION: This is the first study explicitly investigating institutional financial interests with benefit through increasing services provided by the institution. The findings suggest the possibility that institutional COI may influence the conclusions of volume-outcome studies, although the results are inconclusive. Surveyed authors had divergent opinions on whether institutional factors are likely to influence research integrity. Further research is needed to investigate institutional COIs. PLAIN LANGUAGE SUMMARY: This study examined COIs in research, focusing on benefits to the institution rather than to individual researchers. Authors might publish results in favor of their hospital to increase the amount of a service provided, such as surgery. We looked at 68 studies. These studies investigated whether hospitals performing more knee replacement surgeries had better patient outcomes. We found that authors from hospitals with many knee surgeries were more likely to report positive conclusions compared to those from lower-volume hospitals. We also surveyed study authors working at hospitals to get their views on COIs. Out of the 20 authors who responded, 35% thought institutional factors likely influenced study conclusions, 24% were neutral, and 41% thought this influence was unlikely. Our findings suggest that it is possible that COIs through researchers' institutions may affect study conclusions, but more research is needed to understand this issue better.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.267 | 0.621 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.030 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".