Clinician recruiting is antiquated. That’s why we launched Winnow.

Image for Clinician recruiting is antiquated. That’s why we launched Winnow.

Advances in technology, especially AI, are disrupting industries every day. But there’s one sector that has resisted modernization and remained rooted in the dusty past: clinician recruiting.

Healthcare is growing at a much faster pace than other occupations, while also facing high turnover rates. Despite those inherent challenges, in-house clinician recruiters are beholden to an antiquated, expensive, and often unsuccessful process that bogs them down in manual tasks. 

The consequence? Longer recruitment cycles and poor hires. Which, in turn, yields excessive strain on existing clinicians (aka “burnout”), higher expenses (locum tenens), and missed revenue. 

This dilemma of recruiting for clinical providers has been exacerbated by a historic shortage in the labor market brought on by COVID-19. Now recruiters are desperate. So they’re throwing ever more money at the problem only to produce the same results. Even when recruiters do (finally) fill vacancies, they’re often signing hires who aren’t aligned with the organization and end up leaving within a year. 

For recruiters, this archaic dysfunction makes their jobs torturous. For the team at SwitchPoint Ventures, the dire situation signaled an opportunity. 

Our AI-focused venture studio could see that clinician recruiting was overdue for disruption by AI. That’s why we launched Winnow, an AI solution that sources ideal clinician matches at warp speed. 


Recruiting, done well, is both an art and a science. Winnow’s goal is to handle the science part so that recruiters can practice their art.

We do this by empowering clinical providers to optimize the best tool they have: their own clinicians. Good referrals don’t just accelerate the recruiting process; clinician referrals lead to hires that are better and more lasting fits. After all, who better to validate a candidate’s fit to your culture than via their connection with your internal provider?

Our platform develops predictive analytics to accurately source the best clinical providers for each business and role. We then create opportunities for a medical organization’s own clinicians to easily refer a Winnow candidate within their own networks. 

The result is a quantum leap of efficiency: in the hands of a proactive recruiter, Winnow promises to cut average recruitment cycles in half and can reduce costs by over four times.


When it comes to recruiting clinicians, timing matters, context matters, and relationships matter. As we developed Winnow, we first had to understand where along this path traditional clinician recruiting had broken down.

We discovered 2 key problems:

  1. A focus on the small pool of candidates who are actively looking. At any given time, only 10% of clinicians are identifying themselves as actively searching. With today’s limited tools, most recruiters have no choice but to focus primarily on active candidates, which limits their searches to a paltry pool of options. 
  2. Too much competition for the wrong candidates. Every recruiter is waging a losing battle trying to get to the 10% pool and then fighting over those same candidates. The tug-of-war is a poor use of everyone’s time. Are these people really the best candidates to be pursuing in the first place? Why are they looking for a new job? And what are the chances that this small pool will offer up the best-aligned candidates for your open position?

As a result, recruiters spent an inordinate amount of their time just on sourcing candidates. 

When you’re wasting time sourcing, you’re not taking care of other parts of the recruiting process, such a building relationships, assessing and onboarding. And, let’s be honest, nobody wants to source. It’s the most tedious part of recruiting.

Recruiters are hampered by their reliance on highly outdated lists that they pay top dollar to access. The industry is littered with inadequate and inaccurate databases that claim to be the guiding tools for sourcing clinicians. These lists offer little to no value, yet they persist as a tool because there hasn’t been a viable alternative.

The Winnow team knew that if recruiters could broaden their pool of candidates from 10% to a total of 82%, they would empower recruiters to begin their search from a greater position of strength. Through predictive analyses, we also discovered that the passive but “willing to leave” population are the candidates who are most likely to be placed. 

So we were determined to leverage AI to access the entire pool of possible candidates for any given position. That meant reaching the incremental 72% of candidates who can be defined as ‘passive;’ not actively looking, but persuadable when presented with the right opportunity. 

How could we get to that 72%? These are people who aren’t coming up in traditional searches because they are not asking to be found. They’re busy. Possibly burned out. And not making any effort to be on a recruiter’s radar.


We decided to reverse engineer the process of reaching clinicians. Instead of a cold outbound process, Winnow pursued a warmer, inbound approach.

First, we developed an AI system that helps identify when a given clinician is likely to leave their job. 

Our system has now achieved a 90% predictive value around a given clinician’s propensity to change jobs. This means that we are identifying that magic 72% ‘passive’ pool with high predictive accuracy.

We also fueled our engine with reams of different criteria to help identify candidates who are aligned with given positions. 

Here’s what we learned: what drives 90% of clinicians to a new job is a referral from another clinician. Someone they trust, a colleague they have worked with in the past or would like to work with in the future.

So we shaped our solution to tap into clinician networks and to alert individuals when our AI engine identifies a good fit within their network. This way, we make it easy for clinicians to refer high-quality candidates who also have a high likelihood of taking a job, if they are asked in the right way. 


What does all of this look like in action? 

Let’s take a peek at the initial referral program of one of our customers. Their program followed typical industry practices: blasting out an email query for referrals to all of their clinicians any time a job was posted.

This “spaghetti at the wall” approach typically yielded few responses. After all, you’re asking busy clinicians to stop and think through their entire network. It was asking too much and delivering too little.

With Winnow in place, this customer’s program has now been revamped so that clinicians are only contacted for a referral when there’s a high likelihood that the candidate who is in their network has been identified through AI as a good fit. 

Now it’s easy for clinicians to participate in attracting and nurturing warm leads. The request has shifted from “Know anyone?” to “You know someone.” 

With this level of guidance, powered by data, it’s possible to think of this organization’s entire clinical provider workforce as a de facto sourcing team. It also allows the organization’s recruiters to do what they do best: build relationships with candidates, select the best fit, and ensure a smooth onboarding.

Imagine the possibilities if your recruiting team could essentially skyrocket from a dozen people to an army of a thousand.

That’s what we imagined, too.

Our vision is to be the most relied-upon resource for in-house clinician recruitment. We believe that AI-driven innovation will help health systems maximize both care for their patients and profits for their mission.

Find out more about Winnow’s AI platform here. Sign up for a demo and let’s explore how to revolutionize the way that you recruit.

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