困境中的医疗健康必须演进的三种方式

​Every day, healthcare teams are left to complete work across systems that were never designed to work together. They chase the next step, correct errors, close gaps, and keep care moving through a maze of disconnected workflows. Healthcare has an unfinished work crisis, one that is driving clinical burnout and costing the United States nearly $1 trillion a year in administrative overhead.

Research from McKinsey and analysis in the

Journal of the American Medical Association confirm that approximately $265 billion of this waste stems from entirely redundant processes. We’ve spent two decades allocating billions to digital transformation and various iterations of AI, but the administrative burden on clinicians and back-office teams remains at an all-time high.

For distressed healthcare organizations, the way forward is not another disconnected tool. It requires three shifts:

Build a deeply integrated system of action to complete the work.

Utilize explainable glass-box AI to make action trusted, auditable, and accountable.

Work with accountable partners who deliver outcomes, not just software.

The relationship between the system of record and the system of action

As health technology consolidates, the need for a new infrastructure is clear: an AI-driven orchestration layer built on a system of action. The healthcare IT stack relies on electronic health records (EHRs), which were designed for billing and compliance. While EHRs support patient care, they commonly lack advanced AI capabilities and struggle to keep pace with innovation, creating a gap between AI models and clinical practice. AI needs a robust infrastructure and workflows to operate safely and effectively. Without trusted integration from the system of record, even advanced AI models risk becoming irrelevant or compromising patient safety.

Building this key layer doesn’t require dismantling current EHRs or legacy infrastructure. A system of action can wrap around existing systems and turn disconnected databases into active operational engines. The more powerful future state, though, is a connected model where the system of record and the system of action coexist, continuously exchanging data, context, and outcomes. In this model, the system moves from data to action to outcome, then to continuous improvement, with explainable AI and human intervention when accountability matters most.

This deeply integrated system of action means uniting operational, technological, clinical, and financial tasks as an intelligence layer that changes how administrative and operational work gets distributed across the enterprise. It is a structural delegation of the friction that currently buries clinicians and staff in administrative tasks. While this architecture lets teams finally operate at the top of their license, its true value is deeper. It introduces systemic accountability, with the technology itself responsible for carrying out the work until it is completed.

The AI ROI paradox and why explainable AI makes a difference

We have achieved unprecedented access to clinical insights using Gen AI and sophisticated analytics. However, a new study from Oliver Wyman reports that while 63% of providers surveyed use advanced AI/automation in some capacity, only 20% to 40% use these tools enterprise-wide. AI can summarize, predict, recommend, and flag, but people still have to validate the output, route the task, correct the record, and make sure the work is completed.

This is where explainable AI (XAI) can make a difference. Unlike black-box systems that produce outputs without a clear reasoning path, XAI makes recommendations transparent, traceable, and auditable. In healthcare, it’s important that leaders and care teams understand how an answer was derived, what data informed it, where uncertainty remains, and when human assessment should be applied. This allows connected AI-driven workflows to be trusted, monitored, improved, and scaled.

When explainable AI is embedded into a connected system of action, intelligence can move across the patient journey with increased confidence and accountability, and complete the work. The value lies in making sure the action can be understood, acted on, monitored, and improved over time.

For example:

The connected system begins by extracting data from external documents to create a patient history while simultaneously verifying insurance and financial clearance.

During the encounter, ambient listening documentation is directly fed into partially autonomous coding agents, with appropriate validation, auditability, and oversight when risk, ambiguity, or compliance requirements require it.

After the visit, the system triages the inbox, manages prescription refills, and ensures clean claims are sent to payers. All of this occurs while maintaining visibility into the reasoning and actions taken.

Hold partners accountable for outcomes

The shift to an integrated system of action can be highly transformative. When an organization connects the entire patient journey, including the administrative tasks that add friction, into a single orchestration layer, compounding value can be realized. But healthcare organizations cannot blindly adopt innovation models that promise value without building accountability into their plans.

In a world of value-based care and outcome-linked performance, too many healthcare technology and services models still reward vendor activity more than client outcomes. This conflict makes no sense in the current environment. When vendor compensation links to revenue performance and operational improvement, incentives begin to align with the outcomes healthcare organizations need most. This is what makes transformation sustainable. Connected workflows create the operating model. Explainable AI makes the model trusted and scalable. Accountable partnerships ensure that the work delivers measurable value.

The intelligence layer of our industry has matured, but it’s clear that healthcare cannot outrun systemic pressures by simply throwing technology at the problem. Even the most advanced AI models will struggle to deliver measurable gains without a connected operating environment and partners held accountable for results. What healthcare needs now is a connected, deeply integrated system of action that works with the system of record to complete work across the enterprise, supported by accountable partners willing to stand behind the outcomes they create. Then healthcare can move from fragmented activity to sustainable performance, reducing avoidable burden, strengthening financial resilience, and creating a better healthcare experience for everyone.

Picture: CifoTart, Getty Images Sachin K. Gupta Sachin K. Gupta is Founder and Chief Executive Officer of IKS Health, a global leader in care enablement solutions. Gupta founded IKS Health in 2007 and has pioneered its emergence as the leading care enablement platform in the United States. Fueled by Gupta’s blend of entrepreneurial spirit, executive acumen, and strategic vision, IKS Health has grown to 12,000+ employees, serving more than 600 healthcare organizations. Gupta continues to steer the organization toward rapid growth and success, including taking IKS Health public in December 2024 on the National Stock Exchange of India.

Gupta believes IKS Health serves as an accountable advisor to healthcare organizations, guiding them through the complexities of modern healthcare in order to achieve sustainable growth. His priorities include delivering a comprehensive care enablement platform that combines pragmatic AI-driven technology with dedicated expertise to alleviate administrative, clinical, and financial burdens, helping clinicians and staff to focus on delivering high-quality patient care.

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