This is a Physician in the Loop special topic.

Who gets the time back

Most hospitalists already use AI, and Epic is bringing more of it to the wards. The minutes it saves are few, and they belong to patients and doctors, not to a higher census.

Sutter Health's rollout of AI scribes in 20 California hospitals did not go the way its doctors expected. More than half of those studied thought the software, which listens to a visit and drafts the note, would free up time for one more patient a shift. They ended up using it for about 3% of their notes, and their time on notes did not change.

The study, published in September, is a fair guide to what is coming. Epic's records cover most of America's hospital beds; more than 85% of its customers already use its AI, which can draft hospital courses and summarize charts, and its listening tool, which drafts notes and queues orders, is offered for inpatient care. Tools for hospitals to build their own AI agents are due to become widely available in 2027, as is a model that forecasts how long patients will stay. The time these tools save is real but small. It belongs to patients and to doctors' evenings, not to a higher census, and hospitalists must claim a say before the tools go live.

The evidence on time is consistent. In one of the largest studies, of some 8,500 clinicians in academic clinics, AI scribes saved about 16 minutes of documentation for every eight hours with patients, about one extra visit every two weeks, and after-hours time in the record did not change significantly. A small pilot among hospitalists found no measurable change in time spent documenting or at the bedside. And drafts need checking: AI-written discharge narratives had more errors than physicians' own, though the potential for harm was low for both, and Epic's hospital-course drafts, though more complete, made up more details.

The push to turn those minutes into patients has begun: as AI spreads, one physician in five already reports higher expectations for productivity. Hospitalists have little slack. In one survey, those outside academia averaged nearly 17 encounters a shift but called about 15 reasonable, and in one study, length of stay rose on busy days once a hospitalist's census passed about 17. The Society of Hospital Medicine told the federal health department that time saved by AI belongs at the bedside, and that success should not be measured in "higher encounter quotas."

The strongest objection comes from those who run the beds: hospitals are full and short of money, so if software saves time, some of it should come back while patients wait in the emergency department. But the time is not there to take. A quarter of an hour a shift does not make room for an admission; beds and discharges do, and in one hospital, AI's predicted discharge dates were right to within a day less than half as often as case managers' the day before discharge. And the tools can pay for themselves without more patients: one health system says higher billing more than covered its scribes.

Hospitalists have more standing than they may think. The American Medical Association says the medical staff should help choose and implement AI "at the outset," and guidance from the Joint Commission and the Coalition for Health AI asks hospitals to govern these tools, test them locally and keep monitoring them. Hospitalists should take seats on their hospital's AI committee, or start one, and insist on a pilot on their own service before go-live, judged by local measures: errors in drafts, time after hours, length of stay. Local testing matters: even Epic's newer sepsis model varied widely between health systems and raised many false alarms. And they should demand training; only a third of hospitalists who use AI say they were adequately trained.

Replacement is not the near-term threat. In the latest national survey, most hospital medicine groups expected to grow, and when one physician group cut 177 jobs in a move described as largely driven by AI, the cuts fell on its billing office, not its doctors. The slower risks are census creep and coverage moved off the ward; remote hospitalists let some veterans' hospitals cut on-site clinicians. Hospitalists should write workload into their contracts, with a census limit and a rule that AI's time savings are not turned into quotas without their agreement, and claim the work software cannot do: the sickest admissions, family meetings, procedures, and checking the tools. In September, doctors at two Allina hospital campuses in Minnesota, hospitalists among them, reached a tentative first contract after a four-day strike in which AI was among their worries.

The doctors in Sutter's study wrote few of their notes with the scribe, and fewer of them came away thinking it would buy them another patient a shift. Hospitals should run the same experiment on their own wards before they write that extra patient into anyone's targets.

This special topic was read by an AI voice. Its sources are linked at physicianintheloop.org.