ArticleCureus2025
Driving Transparency and Efficiency in Value-Based Care Through Bundled Episodes and Technology.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The current healthcare system often feels confusing and fragmented for patients, with unclear costs, repeated tests, and delays in care. The traditional fee-for-service (FFS) model in healthcare, which reimburses providers for each individual service regardless of necessity or outcome, has long fostered inefficiencies, redundant testing, and administrative burden. This approach often leads to fragmented care, delayed diagnoses, and a breakdown in patient trust, especially when costs are unclear and care decisions lack transparency. In response, there has been a national shift toward value-based care (VBC) and episode-based alternative payment models (APMs), which aim to prioritize quality, coordination, and outcomes over volume. However, the success of these models hinges on one essential principle: transparency. This article explores how transparency, when applied at clinical, financial, and operational levels, can rebuild patient trust, reduce unnecessary procedures, and improve accountability across healthcare systems. The integration of advanced technologies, particularly artificial intelligence (AI), further enhances the scalability and effectiveness of transparency initiatives. This article advocates for a healthcare system where decisions are clear, billing is understandable, and care is coordinated, with transparency and technology working hand in hand to achieve lasting reform.
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.