Health care is providing more services than at any time in its history, but outcomes are not improving at the same rate. For a long time, higher spending and expanded activity were seen as signs of progress, allowing volume to supersede performance. Due to ongoing variations and still uneven efficiency across the system, this assumption is clearly under pressure. If this is progress, why does it seem inconsistent?
According to the latest report by Cms.govspending reaches $5.3 trillion by 2024, accounting for 18% of GDP in the United States.1 Figures this large no longer simply reflect scale. This invites closer scrutiny of what the scale actually produces.
The Point Where Volume Stops Explains Performance
Higher utilization used to be a reasonable interpretation of increased access and as a result better service. He wasn’t strong anymore. In some areas, this has been completely broken down, further complicating this is variation. Similar conditions are treated differently between providers, often without consistent differences in outcomes.
More care is provided, but this is not always safer or more efficient. These differences are at the heart of the shift toward value-based care. Value in this context does not mean reducing activity. It’s about holding actions accountable for their subsequent consequences.
Where the Pressure Actually Increases
Although the shift towards values is often discussed in general terms, it is driven by very specific pressures. One is specialized care, which has high costs, less standardized pathways, and variations that are difficult to explain.
According to a McKinsey analysis, a more consistent value-based approach in specialty care could save up to $100 billion in annual spending.2 This figure shows more inconsistencies than advantages. This highlights that the system currently lacks a reliable method for determining what is considered good in similar situations.
Payment Models Are Moving, But Aren’t Synced
Although the movement has been uneven, reimbursement structures have begun to change in response. Value-based contracts are growing, but have not yet reached the stage where they regularly change behavior.
This is a simple concept. Payments should consider outcomes, not just activity. Defining these outcomes in a way that is both operationally useful and clinically significant is a challenge.
Deloitte continues to identify data fragmentation and limited interoperability as key obstacles. Until these issues are addressed, value-based models are likely to remain selective rather than systemic.3
Technology Changes What Can Be Seen
Health care systems have had data for years, but it is inconsistent. There is information, but it is scattered throughout an ineffective communication system. That’s starting to change. Increased portability of patient data makes it possible to track outcomes over time, not just at a specific moment.
This is more important than it seems. Because assumptions can be tested once results are seen throughout the course of treatment. Some will survive. Others won’t.
AI Turns Visibility Into Action
Visibility alone does not create value. The difference now is that AI systems start acting on that visibility in real-time. Predictive models can identify risks before they occur, while generative systems reduce administrative barriers that delay service. Shifting from insight to intervention allows reducing emerging variations, rather than analyzing them retrospectively.
From Meetings to Tracks
Encounters are the foundation of traditional care delivery. Consultation, surgery and discharge. Each event is considered a contained event. Value-based care shifts the emphasis to the trajectory. What is important is how the patient’s condition changes as a result of an interaction, not just what happens during the interaction.
Technology helps with this by increasing visibility outside the clinical environment. Remote monitoring, for example, is not just a layer of convenience. This changes when intervention occurs, and sometimes whether escalation occurs or not.
Fragmentation Still Causes Most of the Damage
Fragmentation remains one of the system’s most enduring limitations, even with improved tools. Without a unified view of their health history or treatment plan, patients continue to change health care providers.
Value-based services are based on a level of coordination that is still inconsistent in reality. Although technology can facilitate data exchange, it does not guarantee that decisions are taken synchronously. This depends on incentives that are still not structured consistently. Results continue to be marred by fragmentation when alignment is poor.
Administrative Complexity Underestimated
Administrative procedures lead to more healthcare inefficiencies than clinical judgment. Pre-approval, billing, and claims handling add layers of costs that don’t directly improve service.
The scale is very large. According to the JAMA study, annual waste volume is estimated at between $760 billion and $935 billion, with administrative complexity being a major factor. 4 What is often thought of as operational overhead is, in fact, a structural problem. This affects how services are delivered and how much service is delayed.
AI and the Value-Based Care Economy
The financial mechanisms of value-based care depend on risk prediction, population management, and avoidance of avoidable costs. AI directly impacts each of these by enabling earlier and more precise intervention in high-cost cases. Automation of administrative workflows, including prior authorization and claims processing, reduces leaks that erode margins under value-based contracts. Continuous monitoring of the patient journey also allows reimbursement to be more closely aligned with real-world outcomes compared to episodic procedures.
Data Has Moved From Notes to Leverage
The data in a volume-based system primarily records past events. This begins to influence subsequent events in the value-driven system. This requires more than just access. This requires interpretation, and the ability to act on insights in real time.
This ability is still not consistent. However, when this happens, it begins to change decision making in ways that are difficult to undo.
Innovation Asked Various Questions
Especially in expensive fields such as oncology, treatment advances continue. The speed of innovation is not growing, but the way it is assessed is changing.
The importance of real-world performance is increasing. Value-based agreements attempt to link payment to the results seen after treatment, not just the results seen in a controlled environment.
Thus, a new type of accountability was introduced. Additionally, this makes it difficult to separate cost and value.
Why This Shift Is Accelerating Now
The current acceleration is no coincidence. This reflects the convergence of more standardized data through interoperability frameworks, the maturation of machine learning models, and the emergence of generative AI capable of working with unstructured clinical information. At the same time, cost pressures force the system to do more than incremental improvements. Together, these forces are pushing AI from experimentation into operational relevance, particularly in areas where traditional approaches struggle to deliver consistent results.
The Shift Is Already Underway, Even Though It’s Not Completed
The transition from volume to value is not speculative. Decisions have been influenced by this, but not evenly across the system. What is uncertain is not the direction, but the implementation. Aligning payment models, data infrastructure and service delivery takes time.
However, the underlying pressure is unlikely to ease. This system is expected to not only show how much benefit it provides, but also how much difference it makes.
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