By GANESH ASAITHAMBI
In an episode of the sitcom How I Met Your Mother (HIMYM), Barney Stinson introduces a fictional word: possimpible. The possimpible combines “possible” and “impossible” and describes the extraordinary achievements by people who refuse to accept conventional limits. In modern healthcare, the possimpible is no longer a joke; it has quietly become an expectation.
Clinicians are expected to provide care that is safer, faster, and more compassionate despite rising administrative burdens, workforce shortages, and an increasingly complex patient population. These expectations often extend beyond what existing systems were designed to accommodate. The distance between what the system can provide and what patients need is increasingly filled by clinicians.
Picture this example at the end of a clinician’s day. A physician takes a seat to call a patient’s family. The phone conversation takes longer than expected with questions about their loved one’s prognosis and hesitancy about what to do next with fear about what is to come. The physician provides reassurance and guidance. The physician hangs up, only to find that note dictations are not complete and messages are still unread. None of this shows up as productivity, but it is needed to provide quality care. There are thousands of scenarios like this that take place every day in American health care.
These moments appear routine. However, they reflect something more consequential: healthcare has become quietly dependent on clinicians to stretch beyond the boundaries of the systems they work within.
This dependence has been normalized over time. While healthcare organizations continue to ask clinicians to do more (document more thoroughly, communicate more frequently, coordinate more complex care), actual workforce capacity has remained stagnant. In response, clinicians have raised the capacity of what is possible by working harder.
Clinicians bridge this gap through additional effort. They stay later to finish notes. They return messages after scheduled hours. They absorb additional responsibilities when staffing is thin. These actions are rarely framed as extraordinary. They are described simply as professionalism. Yet professionalism should not require constant overextension.
Burnout is frequently described as a crisis of resilience among clinicians. However, it is a crisis of system design. When organizations depend on sustained discretionary effort just to function, exhaustion is not an unexpected failure. Rather, it is a predictable outcome of a predictable design flaw. The possimpible describes this phenomenon perfectly. It represents the moment when the impossible becomes achievable only through personal sacrifice. Healthcare has always required moments of extraordinary effort. Emergencies and complex diagnoses demand skill and dedication beyond routine practice. These moments are part of the profession’s identity. What is new is the expectation that extraordinary effort occurs every day.
Sustainable systems cannot depend indefinitely on individual heroism. Over time, dependence on the possimpible erodes morale, reduces workforce stability, and ultimately threatens the quality of care itself. Addressing burnout requires more than resilience training or symbolic gestures. It requires something healthcare has rarely attempted: an honest accounting of the work that sustains the system. That accounting must begin with making the invisible visible.
Healthcare has spent years trying to solve burnout that include resilience training, wellness programs, and mental health resources. These efforts are not without value, but they share a common assumption: that the problem lives inside the clinician. In fact, the problem lives inside the system in which we work, and the reason it persists is simpler than most would admit: we have never measured it.
The invisible labor of clinical care does not appear on any productivity dashboard. It is not captured in any staffing model and generates no charge. Yet it is not peripheral to work; instead, it is the work. It is what fills the gap between what the system was designed to deliver and what patients need. We cannot redesign what we have never seen, and we have never looked.
In the early 2000s, Kaplan and Anderson introduced Time-Driven Activity-Based Costing (TDABC). The premise is straightforward: instead of asking people to estimate how they spent their time, you measure it directly. You assign costs based on actual time spent on actual activities, and what gets measured gets managed.
In healthcare, we have barely adopted TDABC. Most applications focus on procedure costs, care pathway efficiency, and supply change optimization. The methodology was used to find hidden costs in systems and was rarely used to find hidden labor within them. This is the gap worth closing.
If TDABC was applied not just to what gets billed, but to the full scope of what clinicians actually do, including everything that never creates a charge, the result would be something healthcare has never had before: a real accounting of where the system depends on invisible effort, who is carrying it, and how much of it exists. You cannot staff what cannot see. You cannot redesign what has never been measured. The methodology exists, but we have simply not pointed it in this direction.
AI has entered the conversation as a potential answer; however, framing AI as the solution misses the point. Healthcare does not have a technology deficit. Deploying AI into a system that cannot see itself clearly does not fix the system. It automates the dysfunction. AI is genuinely useful but only as an instrument. Ambient documentation tools already capture clinician activity in real time. Electronic medical record data already records when notes are completed, when messages are sent, and what time of day the work happens. Activity capture technology already exists to track the duration and nature of clinical tasks without adding a single documentation burden to the clinician. This is the raw material for TDABC to work. The data exists; it is simply not being used to ask the right question. Instead of using that data to monitor clinicians, health systems could use it to diagnose themselves. The patterns of after-midnight note completion is not a performance issue; rather it is a system signal.
Once invisible labor becomes visible, the downstream consequences are not complicated. Staffing models can be built around what clinicians actually do, not just what gets billed. Workflow redesign has an evidence base instead of anecdote. Leadership accountability becomes harder to avoid when the data exists, and payment reform, the slowest lever of all, finally has something concrete to point to.
But there is something more fundamental at stake than operational efficiency. High-performing systems do not win because they do more. They win because they do the basics with consistency. Pirkle has said, “Boring excellence beats brilliant chaos every time.” When fundamentals are unreliable, no strategy deck in the world will save you. When a system fails, it is rarely a failure of effort, it is instead a failure of reliability.
That is precisely what the possimpible has obscured. Healthcare has mistaken brilliant chaos—the daily heroics of a workforce absorbing what broken systems cannot—for high performance. Brilliant chaos is not high performance; it is a warning. Healthcare has always produced moments of genuine heroism: the resuscitation that should not have worked, the diagnosis made on instinct after everything else failed, or the clinician who stayed because leaving was just not an option. These moments are real. They are part of what draws people to this work. They deserve to be recognized as extraordinary.
However, they are not extraordinary when they happen every day before lunchtime. As Ted Mosby reminds Barney in HIMYM, “Every night can’t be legendary. If all nights are legendary, no nights are legendary.” The same is true in heroism in healthcare. When the extraordinary becomes the routine, it stops being a tribute to the people doing the work. It becomes an excuse for the system that depends on them.
The possimpible was always meant to describe the rare and the remarkable. When a system is designed so poorly that the impossible is required just to make it through a Tuesday, the possimpible stops being a celebration. It becomes the new normal, and no workforce can sustain a baseline built on exceptional.
Visibility does not eliminate heroism; it protects it. When systems are designed around what the work actually requires, clinicians are not depleted by the routine. They arrive at the moments that truly demand everything they have with something left to give.
Burnout is typically framed as a workforce issue: clinician wellbeing, retention, and or pipeline sustainability—these are all legitimate, but they direct the consequences of invisible labor to the clinician. The more uncomfortable reality is that the consequences extend to the patient.
Recall the earlier case example of the physician who called a patient’s family at the end of the workday. The physician stayed on the line while a family worked through fear and uncertainty. That conversation influenced what happened next. Whether the family understood the prognosis, whether they made an informed decision about the care plan, or whether the patient went home with the right support or returned to the emergency department two weeks later. None of this shows up as a quality metric.
This is where the measurement gap becomes a patient safety gap. If invisible clinician effort is load bearing, and if it is truly influencing outcomes, then its absence has consequences that extend far beyond the clinician who chose not to make the same call. We simply cannot prove the full causal chain yet, and not because the connection does not exist, but because we have never measured it.
The goal is not a healthcare system without extraordinary effort. It is a healthcare system that reserves it for extraordinary circumstances. The possimpible should remain possible; it should just no longer be required.
Healthcare has built entire quality infrastructures around measurable outcome: door-to-needle times, readmission rates, mortality indices, length of stay. These metrics all mater, but they measure the output of a system, not the effort that sustains it. A system that tracks outcomes without tracking the labor that produces them is flying with half its instruments in the dark. It is time to turn the lights on.
Ganesh Asaithambi, MD, MBA, MS, is a Minnesota-based stroke neurologist working at Alllina Health
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