ArticleBMC research notes2022
A case study of adapting a health insurance decision intervention from trial into routine cancer care.
Article in BMC research notes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Adapting a Cancer Cost and Health Insurance Tool for Implementation: Rapid Qualitative Analysis.Health expectations : an international journal of public participation in health care and health policy · 2026Article
- Assessing the effect of virtual navigation interventions to improve health insurance literacy and decrease financial burden in cancer survivors: The HINT II study protocol.Contemporary clinical trials · 2025Article
- A Scoping Review of Interventions to Address Financial Toxicity in Pediatric and Adult Patients and Survivors of Cancer.Cancer medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
objectiveThis study adapted Improving Cancer Patients' Insurance Choices (I Can PIC), an intervention to help cancer patients navigate health insurance decisions and care costs. The original intervention improved knowledge and confidence making insurance decisions, however, users felt limited by choices provided in insurance markets. Using decision trees and frameworks to guide adaptations, we modified I Can PIC to focus on using rather than choosing health insurance. The COVID-19 pandemic introduced unforeseen obstacles, prompting changes to study protocols. As a result, we allowed users outside of the study to use I Can PIC (> 1050 guest users) to optimize public benefit. This paper describes the steps took to conduct the study, evaluating both the effectiveness of I Can PIC and the implementation process to improve its impact.
resultsAlthough I Can PIC users had higher knowledge and health insurance literacy compared to the control group, results were not statistically significant. This outcome may be associated with systems-level challenges as well as the number and demographic characteristics of participants. The publicly available tool can be a resource for those navigating insurance and care costs, and researchers can use this flexible approach to intervention delivery and testing as future health emergencies arise.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.