Evidence map›Paper›PMID 41717153›Full record

ArticleCureus2026

Enhancing Payment Integrity in U.S. Healthcare Through Value-Based Care: The Role of Bundled Episodes and Alternative Payment Models.

Amol Kodan

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Amol KodanPublic Health, Monroe University, New York City, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Improper payments, unnecessary utilization, and administrative inefficiencies represent persistent structural challenges within the United States healthcare system. This places significant pressure on healthcare spending. Value-based care (VBC), particularly through bundled episode payments and alternative payment models (APMs), has emerged not only as a potential cost containment strategy but also as a potential framework for strengthening payment integrity and promoting appropriate resource use. This article examines how value-based care models, particularly bundled payments and APMs, strengthen payment integrity by addressing structural drivers of improper payments through improved transparency, accountability, and stewardship of healthcare resources across the care continuum. Bundled episode payments establish a single, prospectively defined payment for all services associated with a discrete episode of care, supporting greater predictability of spending and improved coordination across settings, while reducing fragmentation within the care continuum. By shifting reimbursement away from volume-based incentives toward outcome-oriented accountability, VBC facilitates clearer evaluation of utilization patterns and enables earlier identification of unexplained variation through routine monitoring and analytics. These design features complement traditional oversight and utilization management efforts by addressing the underlying payment and delivery-system drivers of fee-for-service (FFS) reimbursement.  This technical report synthesizes existing evidence and policy analysis to examine how value-based care models address a critical policy gap by embedding payment integrity and utilization oversight within payment design, rather than relying solely on retrospective enforcement.

Indexed as

alternative payment modelepisode based carehealthcare reimbursementpayment integrityutilization managementvalue based care

Identifiers

PMID41717153
PMCPMC12914492

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.