Association between physicians’ interaction with pharmaceutical companies and their clinical practices: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Pharmaceutical company representatives likely influence the prescribing habits and professional behaviors of physicians. The objective of this study was to systematically review the association between physicians' interactions with pharmaceutical companies and their clinical practices. METHODS: We used the standard systematic review methodology. Observational and experimental study designs examining any type of targeted interaction between practicing physicians and pharmaceutical companies were eligible. The search strategy included a search of MEDLINE and EMBASE databases up to July 2016. Two reviewers selected studies, abstracted data, and assessed risk of bias in duplicate and independently. We assessed the quality of evidence using the GRADE approach. RESULTS: Twenty articles reporting on 19 studies met our inclusion criteria. All of these studies were conducted in high-income countries and examined different types of interactions, including detailing, industry-funded continuing medical education, and receiving free gifts. While all included studies assessed prescribing behaviors, four studies also assessed financial outcomes, one assessed physicians' knowledge, and one assessed their beliefs. None of the studies assessed clinical outcomes. Out of the 19 studies, 15 found a consistent association between interactions promoting a medication, and inappropriately increased prescribing rates, lower prescribing quality, and/or increased prescribing costs. The remaining four studies found both associations and lack of significant associations for the different types of exposures and drugs examined in the studies. A meta-analysis of six of these studies found a statistically significant association between exposure and physicians' prescribing behaviors (OR = 2.52; 95% CI 1.82-3.50). The quality of evidence was downgraded to moderate for risk of bias and inconsistency. Sensitivity analysis excluding studies at high risk of bias did not substantially change these results. A subgroup analysis did not find a difference by type of exposure. CONCLUSION: There is moderate quality evidence that physicians' interactions with pharmaceutical companies are associated with their prescribing patterns and quality.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | low |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".