Combating shortage and burnout with new float pool models

A highlight from AHA’s conference this week was a presentation from Thomas Jefferson University Hospital in PA about their inter-facility float (“IFF”) program. This is an emerging trend: across the country, health systems are amidst experiments with pools of nurses that are shared, dynamically, between not just floors, but campuses. I personally have spoken with >5 such IFF programs, all of which were first started 2022 or later.

“Wow, you made float pools sexy”, said the moderator- and it was fairly true. These positions are coveted and competed for, they get a lot of applicants, dozens more than typical nurse vacancies. Thomas Jefferson has scaled up fast, going from 25 nurses in the pool in Spring ‘22 to now more than 150.

“Wow, you made float pools sexy”, said the moderator- and it was fairly true

It’s early days for these programs. With these experiments popping up all over the country and still new, there are remarkable commonalities in why and how these hospitals have deployed a similar, new model.

A common “Why” for IFF programs
  1. COVID as a jolt: though most of the programs started in 2022 or later, many of the nursing leaders who designed them learned from trying to quickly deploy and redeploy their clinical teams in 2020-2021 and previewed what mobile teams could look like
  2. Cost savings: “We’re paying too much, for too many agency nurses” is part of the “why” these programs have sprung up. Though they tend to pay nurses 150-200% of hourly pay as a normal staff member, it’s still well cheaper than the 300%+ they paid 2021-22 for agency and therefore justifies itself fairly easily (at least for now).
  3. Satisfier & retention: Further, these programs allow hospitals to satisfy a number of increasing needs for RNs (flexibility, higher pay for being “on call”, variety of work experience)- therefore, they’re a way to both meet the need of flexible labor with the same RNs who might’ve jumped to agency without the option

Common enablers: “what else do you need to try IFF?”

  1. Urban/suburban density (and local dominance): Systems running these programs have 5+ facilities (often 10) in reasonable driving distance of one another- and usually that’s reflective of meaningful, 30-50%+ local market share as well
  2. Sufficient clinical integration: If hospitals in the program have different EMRs or meaningfully different protocols (e.g., a hospital that has been recently bought and not fully integrated)- too high of a barrier. Systems trying this have been in the market operating the facilities >10 years.

In the early days of IFF, there are also some distinct differences amongst implementations of IFF.

Difference 1: Demand side- how are nurses requested?

Some programs fully “federate” the decision - that means, any unit can request IFF staff- but it will count against their clinical budget. For others, a central team is making the decisions, usually based on operational metrics. For example, the team at Thomas Jefferson has specific by-unit vacancy % triggers to receive IFF staffing.

Difference 2: Supply side - how are nurses signing up?

Some IFF programs are run with updates made daily, some place the IFF nurses on 4- or 6- week “rotations”, and some are fully self-scheduled, meaning that units can post openings that nurses in the pool can sign up for directly

Thomas Jefferson had one of the most detailed training programs for SEAL I’d seen, specifically geared to onboard these nurses to the program with tailored curriculum that helps them operate across facilities.

Difference 3: All ICU? no ICU? somewhere in-between?

When nurses are being staffed across multiple locations in a system, how they are trained and certified is a question. Some programs start by having nurses certified up to ICU-level (so they can go anywhere, essentially, without their certification being an issue). At Thomas Jefferson, their inter-facility float pool (called "SEAL" nurses) has a mix of certifications, with specific requirements around where nurses with ICU training may float. Thomas Jefferson had one of the most detailed training programs for SEAL I’d seen, specifically geared to onboard these nurses to the program with tailored curriculum that helps them operate across facilities.

What’s next?

I expect that some true best practices will start to emerge over next ~5 years and as new systems launch their own version, they’ll converge on a model. Tech enablers will speed this up. At In-House, our demand prediction platform supports increased range and flexibility for IFF programs.

When you have Uber/Lyft to matchmake, you need fewer queues of taxis waiting outside an airport or a hotel. Over time, demand and supply prediction can make IFFs more flexible and scaled.

For example, because nursing teams can use In-House’s platform to predict supply/demand for nursing, they can more easily handle different levels of training amongst nurses. Over time, this will even allow IFF to extend the geographic range in which it operates- not every nurse needs to be able to drive to every facility for it to work, as long as the model is optimizing matchmaking. When you have Uber/Lyft to matchmake, you need fewer queues of taxis waiting outside an airport or a hotel. Over time, demand and supply prediction can make IFFs more flexible and scaled.

I think IFF is great, and view it as one of the desperately needed innovations to combat fundamental increasing shortage in clinical workforces.

Written by

Ari Brenner

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