Driving Transparency and Efficiency in Value-Based Care Through Bundled Episodes and Technology

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.

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Publication Details

Journal
Cureus
Published
2025-11-25
DOI
https://doi.org/10.7759/cureus.97752
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Driving Transparency and Efficiency in Value-Based Care Through Bundled Episodes and Technology

Amol Kodan
Cureus
Artificial Intelligence in Healthcare and Education
article

Driving Transparency and Efficiency in Value-Based Care Through Bundled Episodes and Technology

Amol Kodan
article en

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.

CureusVol. 17(11)
Monroe County Department of Public Health (US)
Openalex Percentile: Top 70%
Artificial Intelligence in Healthcare and Education
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