Movement Is the Vital Sign We Aren't Measuring

Every clinic visit starts with the same few numbers: blood pressure, heart rate, temperature, breathing rate, oxygen level, and often a pain score. They take a couple of minutes, they're recorded the same way everywhere, and they go into the record where they can be trended, flagged and used by the systems that help with clinical decisions.

What's usually missing is how the patient moves. Can they stand up from a chair without using their arms? How fast do they walk? How steady are they when they turn? For a lot of patients, especially older adults, people recovering from surgery and people with chronic conditions, that tells you more about their health than almost anything else on the chart. We mostly capture it by eye, in a line of free text, or not at all.

This is the first of six posts in a series I'm calling Healthcare, Measured. The idea is to treat functional movement as a vital sign. Over the next few months I'll cover what it takes to measure movement reliably, how to do it at home, how to turn it into a data point people can trust, and how to give AI something better to work with than a note that says "ambulating well."

This isn't a new idea

Clinicians have been saying this for years. In 2009, Stacy Fritz and Michelle Lusardi published a white paper in the Journal of Geriatric Physical Therapy called "Walking Speed: the Sixth Vital Sign." In 2011, JAMA published a pooled analysis of nine cohort studies covering more than 34,000 older adults. It found that gait speed was associated with survival.

So we've known for a long time that function tells us something important. What has lagged is how we capture it.

Why it never became routine

Blood pressure became a vital sign because it's quick, it's standardized, and it ends up as a number. Functional measures mostly haven't had that. Timed walk tests and chair-stand tests exist, but they're usually done with a stopwatch and a clinician's eye, they're done differently at each site, and the result lands in a note or a scanned form. They also tend to live in therapy settings, not in primary care.

After years in health system IT, I've come to one simple rule. If a data point isn't captured in a structured, consistent way, it might as well not exist for anyone downstream. You can't trend it, nothing can alert on it, it won't show up in a population report, and no model can learn from it.

One reading misses the story

Even when movement is measured well, it's usually one reading taken in a clinic. Function changes from day to day. The walk in from the parking lot, how stressful the appointment is, even the time of day, all affect the result.

The changes that matter most, like a slow decline before a fall or a recovery that stalls after a knee replacement, happen between visits. A vital sign checked every few months will miss the trend. That's why measuring at home matters, and it's what the next post is about.

Why this matters for AI

Health systems are building and buying AI tools to predict readmissions, falls and deterioration. Those models run mostly on labs, vitals, diagnoses, medications and utilization history. Function is usually missing, or buried in notes where it's hard to use.

A model can't use what it can't see. Objective, repeatable, structured movement data would give those tools a new kind of signal, one tied closely to independence and to the outcomes patients care about. The data has to be good, though. A noisy measure doesn't improve a model. It makes the predictions worse and more confident at the same time.

What it would take

Turning movement into a vital sign doesn't need a scientific breakthrough. It needs four things. Standardized tests with the same protocol everywhere, so a result means the same thing in every setting. Objective capture instead of a stopwatch and a judgment call. Structured data in the record, next to the other vitals, where clinicians and systems can use it. And measurement at home as well as in the clinic, so you can see trends between visits.

That's the same discipline that made blood pressure a number everyone trusts.

What's coming in this series

• Part 2: Bringing functional testing home
• Part 3: What makes a movement measure a real biomarker
• Part 4: Giving AI better inputs
• Part 5: Getting function into the workflow and the record
• Part 6: Paying for it and proving its value

If you run a health system or a clinical program, start by finding out where functional data sits in your record today, who captures it, and whether anyone can trend it. The answer usually shows how far there is to go.

Disclosure: I'm VP of Operations at BioMech Health, which works in objective movement measurement. This series reflects my own views and isn't about any specific product.