Negative Spillover: A Potential Source of Bias in Pragmatic Clinical Trials
Fuente:
arXiv
Saved in:
| Main Author: | |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866910751601459200 |
|---|---|
| author | Mann, Sean |
| author_facet | Mann, Sean |
| contents | Pragmatic clinical trials evaluate the effectiveness of health interventions in real-world settings. Negative spillover can arise in a pragmatic trial if the study intervention affects how scarce resources are allocated between patients in the intervention and comparison groups. This can harm patients assigned to the control group and lead to overestimation of treatment effect. While this type of negative spillover is often addressed in trials of social welfare and public health interventions, there is little recognition of this source of bias in the medical literature. In this article, I examine what causes negative spillover and how it may have led clinical trial investigators to overestimate the effect of patient navigation, AI-based physiological alarms, and elective induction of labor. I also suggest ways to detect negative spillover and design trials that avoid this potential source of bias. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2309_10978 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Negative Spillover: A Potential Source of Bias in Pragmatic Clinical Trials Mann, Sean Methodology Quantitative Methods Pragmatic clinical trials evaluate the effectiveness of health interventions in real-world settings. Negative spillover can arise in a pragmatic trial if the study intervention affects how scarce resources are allocated between patients in the intervention and comparison groups. This can harm patients assigned to the control group and lead to overestimation of treatment effect. While this type of negative spillover is often addressed in trials of social welfare and public health interventions, there is little recognition of this source of bias in the medical literature. In this article, I examine what causes negative spillover and how it may have led clinical trial investigators to overestimate the effect of patient navigation, AI-based physiological alarms, and elective induction of labor. I also suggest ways to detect negative spillover and design trials that avoid this potential source of bias. |
| title | Negative Spillover: A Potential Source of Bias in Pragmatic Clinical Trials |
| topic | Methodology Quantitative Methods |
| url | https://arxiv.org/abs/2309.10978 |