Free the clinical workforce: Nurture the clinicians, enhance patient care, and transform healthcare delivery: PwC

Redesign the clinical workforce to align with modern healthcare needs and realities. The clinical workforce model is undergoing a transformation, prompted by relentless pressures that signal an inescapable need for change.

Today’s clinical workforce pressures are chronic

Pressures on the clinical workforce—labor shortages, widespread burnout, workplace safety concerns, persistent labor‑cost inflation—are well documented. Most hospitals face moderate to severe staffing shortages across multiple clinical roles, with substantial burnout among nurses and physicians.

Workplace safety risks remain acute. Healthcare and social assistance workers are five times as likely to experience workplace-violence injuries as workers overall.¹ At the same time, hospital labor costs remain high with salaries for RNs growing faster than the rate of inflation. Looking ahead, new federal student-loan caps (and the federal government’s proposed new “professional degree” definition) could reduce enrollment in key health profession programs, including nursing, and worsen workforce shortages.

These are symptoms of a larger problem. Today’s clinical workforce operating model is out of sync with the realities of modern care. Technology can help, but lasting progress will require redesigning roles, workflows, and support systems to make clinical work sustainable again.

Providers need to fundamentally redesign how care is delivered

The future operating model of the clinical workforce should be stronger and more sustainable. It should be clinically innovative and economically sound, designed to support the well‑being of clinicians, patients, and caregivers alike while preserving the hands‑on human care that remains essential to healing.

Clinicians will move away from fragmented, task‑by‑task labor toward work that revolves around judgment and human relationships. AI‑enabled longitudinal intelligence will quietly absorb coordination and administrative burden, sustaining performance and freeing clinicians to focus on what only they can do—make critical decisions, build trust, and care for people.

Reasons to believe

Healthcare is rapidly being reshaped by technological innovations, medical advances, shifting consumer expectations, and mounting economic pressure.² The way care is delivered, where it is delivered, how it is delivered, and which entities will be delivering it are changing. The work of clinicians will change too, for three reasons.

Inpatient capacity constraints will persist until the operating model changes. The US healthcare system is running out of staffed capacity. Occupancy averaged 75% from May 2023 through April 2024 (up from the prior decade), driven by a decline in staffed beds. Daily census is relatively flat.³ The tight capacity poses a structural constraint, highlighting the urgent need for model innovation rather than temporary fixes. As care continues shifting outside hospitals to reduce the inpatient constraint, different sites of care will require different clinician profiles to enter the equation.
Administrative burden, rework, and murky career pathways are routine features of the work environment, all contributors to burnout. ⁴ Our Behind the numbers report shows significant amounts of licensed clinical time is consumed by documentation, coordination, and recovery from broken processes, draining capacity from the bedside and direct patient care time. While tools like ambient listening are starting to reduce documentation time, progress is uneven and there’s still a long way to go. Reducing administrative work at scale would improve clinician satisfaction and release additional clinical capacity. Career progression is often opaque, with limited visibility into roles and advancement across settings, so clinicians who want to grow often job-hop to advance. Clearer, more personalized pathways would improve retention and keep experience in-house.
AI bolted onto a broken model just automates the dysfunction. Layering AI onto broken processes and outdated staffing models risks reinforcing systemic strain. Technology can accelerate relief when paired with intentional workflow and care model redesign. Technology is an accelerant (but not a substitute) for those changes. That redesign should explicitly consider care team models that enable roles to consistently operate at top of license, introduce agents where appropriate, standardize work (consistent with care‑engineering principles), and intentionally embed technology to reduce friction rather than automate it. Absent this redesign, even advanced AI risks hard‑coding today’s inefficiencies into tomorrow’s workforce model. AI’s best use is to elevate human capability, not scale what isn’t working, and it should augment and enhance clinical judgment and human-to-human care.

Three no-regrets moves to free the clinical workforce

1. Redesign clinical work, flow, and capacity as a single system, and make room for new clinical profiles.

Redesign clinical work as a flow and capacity problem, not a staffing shortfall. Treat workforce shortages as a design issue by reengineering the care delivery infrastructure, breaking work into task modules, eliminating non‑value‑added steps, and aligning care team skills to patient needs to unlock hidden capacity. At the same time, integrate throughput reliability into workforce planning by actively managing capacity as a critical, constrained resource, not an infinite buffer absorbed by clinicians. This is not a distant future state. Health systems already use technology to offload discrete clinical tasks, underscoring why care model redesign should precede broad‑scale transformation.

Replace static staffing with dynamic, needs‑based deployment. Move beyond fixed staffing ratios to assignment models that reflect real‑time acuity, complexity, site of care, and clinician capability, reducing mismatches that drive overload, rework, and burnout.
Reduce variability and enforce acuity and site‑of‑care discipline. Identify and eliminate sources of unnecessary variability that convert inefficiency into labor demand; provide patient care in the right setting; and align acuity with appropriate staffing to prevent mismatches and wasted effort.
Engineer friction out of daily clinical work. Redesign workflows to eliminate coordination, “seek/find,” and rework burden so clinicians can spend more time at the bedside and less time compensating for broken processes.
Actively manage throughput as a workforce strategy. Stabilize patient flow, reduce bottlenecks, and smooth demand so capacity is predictable rather than episodic, preventing clinicians from becoming the system’s default buffer for inefficiency.
Protect and purposefully redeploy freed capacity. Put governance and guardrails in place so gains from efficiency are not immediately reabsorbed. Intentionally redirect capacity toward improved access, lower costs, resilience, or strategic growth, without increasing burnout.

Innovator’s move: Integrate predictive analytics to anticipate patient surges and shifts in acuity, adjusting staffing preemptively based on patient needs and clinician skills to optimize resource allocation and sustain reliable flow.

2. Know the workforce as well as the patients and then act on it.

Providers will soon understand their patients, caregivers, and overall populations in more detail than ever before. These same tools and systems should be used to understand the clinical workforce’s needs and preferences to build far more personal and holistic retention and recruitment strategies.

Use longitudinal workforce intelligence to proactively support clinicians. Shift from reactive retention to proactive support by using AI‑enabled insights to surface patterns of overload, burnout risk, inequity, and unsafe assignment dynamics, such as high‑acuity streaks, frequent floating, and uneven workload, before attrition occurs. Implement virtual reality simulations for skill development and stress management, providing immersive training and support.
Make equity and growth tangible through data‑driven role and development alignment. Use workforce data to expose hidden biases and skill underutilization, then pair clinician experience with opportunities by aligning assignments, career aspirations, and personalized learning pathways tied to coordinated upskilling and competency attainment.
Acknowledge the (reasonable) fears that accompany change. Clinicians are more likely to stay when they can see themselves in the future you’re building. Communicate openly and often about your plans. Be sure that your clinicians understand the scale of change, their roles in new models, and how the human work of caring is valued, will be protected, and preserved.
Address recruitment and retention personally and holistically. Bolster the pipeline of clinicians; tailor benefits to their individual needs and preferences; redesign the care team and the model they operate within; and introduce technology thoughtfully. Expand the clinician pipeline through accelerated training and hospital‑academic partnerships, including expanded placements, teaching roles, and residency‑style programs, to grow sustainable capacity nationwide long term. Focus on the differing needs and preferences of clinicians, abandoning one-size-fits-all programs for data-driven tailoring that accommodates the aspirations and realities of workers. Some health systems have been developing archetypes of their workforce to better understand how to boost career satisfaction (for example, some clinicians wish to focus on furthering their education while others may be seeking research opportunities).

Innovator’s move: Create an internal “workforce marketplace” that matches clinicians to short‑term shifts, projects, and growth rotations across settings (virtual, ambulatory, inpatient) based on verified competencies, licensure, and preferences, giving clinicians more control and variety while helping leaders fill coverage gaps and retain talent.

3. Technology should serve the redesigned model, not prop up the old one.

Define future‑state workflows, roles, and business requirements for AI‑augmented care teams first, then select supporting technologies, including AI, Electronic Health Record (EHR) optimization, telemedicine, automation, and analytics that fit the designed care model.

Put strong foundations and governance in place to enable responsible technology use. Establish clear ethical oversight, role governance, and appropriate‑use policies; protect sensitive health data with robust cybersecurity; and support clinicians through structured change management as roles evolve.
Apply technology to stabilize flow, extend reach, and improve safety, not to patch broken systems. Use AI and analytics to reduce administrative burden, improve documentation, enable borderless virtual care through scalable and secure infrastructure, and proactively identify conditions that contribute to workplace violence before incidents escalate. Also provide physicians with conversational tools that surface the right patient history and longitudinal context on demand (for example, chat EHR capabilities), augmenting clinical judgment and supporting more informed care decisions and diagnoses.

Innovator’s move: Deploy a digital operations command center that uses predictive analytics and simulation to model demand, acuity, and throughput in real time, then generates staffing and bed allocation recommendations, flags capacity constraints and variability hotspots, and supports scenario-based planning so leaders can monitor real time, stabilize flow, right-size staffing, and redeploy freed capacity intentionally.

The workforce that emerges from redesign will be stronger than the one being stretched today.

The future of the clinical workforce does not have to be defined by burnout, crisis, and labor shortages. When friction is removed, administrative burden is reduced, the workplace experience is transformed, career pathways are strengthened, and clinicians gain the time and energy to listen, decide, connect, and flourish in their work.

Thoughtfully designed care models, supported by technology that absorbs coordination and stabilizes flow, can safeguard what matters most—safe care, professional judgment, and human connection. Used this way, technology does not replace care, it preserves it. Leaders who take a workforce‑first approach can cultivate environments where clinicians thrive, patients and caregivers receive better care, and health systems become more resilient.

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^{2. PwC, “From breaking point to breakthrough: the $1 trillion opportunity to reinvent healthcare,” Sept. 17, 2025. https://www.pwc.com/us/en/industries/health-industries/library/future-of-health.html}

^{3. R.K. Leuchter, B.A. Delarmente, S. Vangala, Y. Tsugawa, C.A. Sarkisian, “Health Care Staffing Shortages and Potential National Hohttps://doi.org/10.3390/healthcare11152216 spital Bed Shortage,” JAMA Network Open 8, no. 2 (2025): https://doi.org/10.1001/jamanetworkopen.2024.60645}

^{4. D. Terry, et al., “Navigating a nursing career four years after graduation: A qualitative descriptive study exploring drivers of staying amid wanting to leave,” Nurse Education in Practice 85 (2025): https://doi.org/10.1016/j.nepr.2025.104360}