AI creates new jobs in healthcare even as it eliminates them in other industries. A Stanford University study analyzing millions of payroll records found that entry-level employment in AI-exposed fields dropped 13% since ChatGPT launched in late 2022. Software developers aged 22–25 saw jobs fall nearly 20%.
Meanwhile, healthcare went in the opposite direction. The sector added 686,000 jobs in 2024 alone, accounting for nearly one-third of all new jobs created in the entire U.S. economy.
But there’s a catch.
Hospitals still can’t find enough workers. Labor costs keep climbing 5-6% every year. Rural hospitals in the Great Plains saw expenses jump 6% year-over-year. Small hospitals with fewer than 25 beds? Up 8%.
The math doesn’t work. Nursing schools turned away 65,766 qualified applicants in 2023 because they didn’t have enough faculty to teach them. The physician shortage will exceed 85,000 by 2036. Medicare hasn’t increased residency funding since 1996.
So what do you do when you can’t hire enough people, and never will be able to?
Caroline Hodge found an answer. She used AI to create a job rather than eliminate one.
The Woman Who Lived It Twice
Hodge spent 17 years in healthcare operations. Then she became a cancer patient. Twice.
That’s when she saw what hospital executives miss.
“Patients would get discharged with nowhere to go,” Hodge said. “Especially in rural areas. No follow-up. Driving three hours to see a doctor who might not even be available. Complications caught too late. Then they’re back in the ER, which destroys the hospital’s staffing schedule, triggers Medicare penalties, and starts the cycle over.”
The problem wasn’t that hospitals didn’t care. They didn’t have the staff to care. Bedside nurses were drowning. Care coordinators had impossible caseloads. And in rural markets facing 6-8% increases in labor costs, there often wasn’t a next level of care to send patients to.
So Hodge built Dimer Health around something that didn’t exist: the healthcare transitionist.
What A Transitionist Actually Does
This is the part where AI creates a job instead of killing one.
A transitionist is a licensed clinician who manages one thing: getting patients safely from hospital to home, and to their next in-person follow-up appointment.
They provide 24/7 monitoring using AI-backed alerts tied to each patient’s medical records. When vital signs trend wrong, when symptoms worsen, when someone stops taking their medications, transitionists catch it and intervene before the patient ends up back in the ER.
Here’s why hospitals facing 5-6% annual labor cost growth actually care about this:
It solves four problems at once:
- Hospitals can discharge patients earlier
Patients don’t need to stay in an inpatient bed until they’re 100% stable. If someone is monitoring them at home with the tools to intervene, they can leave sooner.
That cuts the length of stay. This directly cuts labor costs.
- It opens beds for new patients.
Every patient who leaves a day earlier creates capacity. For hospitals facing staffing shortages, that’s the difference between accepting a new admission and going on diversion.
Better patient throughput without hiring a single additional nurse.
- It prevents expensive readmissions.
Every patient who returns within 30 days triggers Medicare penalties and consumes scarce nursing hours. Transitionists catch complications early, before they become ER visits.
For small rural hospitals already facing 8% labor cost increases, reducing readmissions by even 10-15% meaningfully changes the staffing equation.
- It keeps rural patients at home.
Rural patients in places like the Great Plains, where labor costs jumped 6% year-over-year, often have to drive hours for follow-up care that might not even be available locally.
Remote monitoring means they don’t have to. A transitionist based anywhere can monitor patients across multiple rural facilities.
“We needed solutions that address the reality: massive changes in population demographics and a healthcare workforce that can’t keep pace,” Hodge said. “Delivering care into homes isn’t optional anymore when you’re facing permanent 5-6% annual labor cost growth. It’s the only way the math works.”
Why This Is Different From Regular Case Management
Traditional case managers work inside hospitals during business hours. They coordinate discharge planning while juggling dozens of other responsibilities.
Transitionists work 24/7 and focus on one thing: the days after discharge when patients are most likely to crash.
And because they work remotely, they can monitor patients in markets where recruiting any clinical staff is nearly impossible.
“It’s still intensive clinical work,” Hodge explained. “But it’s a different kind of intensity. And it’s attracting clinicians who want to stay in patient care but need more flexibility than bedside nursing allows.”
This is how AI creates jobs in healthcare while eliminating them everywhere else. It augments human expertise instead of replacing it.
The Patient Perspective Nobody Mentions
Hodge learned, as a cancer patient, something that doesn’t show up in labor cost reports.
Most patients don’t want to be in the hospital any longer than necessary.
“I didn’t want to be there,” she said. “I wanted to be home with my family. But I needed to know someone was watching, and that if something went wrong, it would be caught early.”
That’s the safety net transitionists provide. Clinical oversight that makes early discharge safe.
Which means this isn’t just about hospital finances. It’s about giving patients what they actually want: to be home, with professional monitoring and access to care.
The Win-Win-Win
For hospitals: Lower labor costs through shorter stays, better bed utilization, fewer readmissions, all without hiring more staff they can’t find anyway.
For patients: Go home earlier. Stay home. Get 24/7 access to clinicians who might not be available in rural areas. Better outcomes.
For the health system: Money saved. Capacity problems solved—patient satisfaction up.
“Patients recover better at home,” Hodge said. “The question was always: how do you make that safe when you don’t have enough staff? The transitionist role is the answer.”
What This Means For Healthcare Workers
While Stanford found that entry-level employment in AI-exposed fields dropped 13% since late 2022, healthcare is bucking the trend.
Not by hiring more bedside nurses, because there aren’t enough to hire.
By creating new specializations that let existing clinicians work differently, remote roles. Flexible schedules. Focus on stabilizing patients instead of managing acute crises.
The transitionist role proves that AI can create healthcare jobs even as it eliminates them in software development, customer service, and accounting.
For hospitals in the Great Plains seeing 6% labor cost increases, and small hospitals facing 8% jumps, this isn’t theoretical. It’s an operational reality.
When you can’t staff every bed, you redesign the system so you don’t need every bed to be full.
And for patients being discharged from rural hospitals, with only a printout and no one to call if things go wrong?
A transitionist might be the difference between recovering at home and ending up back in an ER that can barely staff the beds it already has.
Image Credit: Photo by Pixabay: Pexels
