Passive candidates for clinician jobs are “needles in haystacks.” AI finds them.

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The crisis in healthcare recruiting is crushing providers and patients across the country. Amidst historic growth in healthcare, there’s also a historic rate of burnout and turnover. The result: too many open positions and too few candidates, leading to recruitment cycles that are torturously long and cost a fortune. 

With such a desperate need for solutions, recruiting platforms have popped up everywhere in an attempt to support clinical providers with a wide range of tools and resources. 

But these tools are not solving the problem. At best, many of them just create modest organizational efficiencies on the margins that don’t address the biggest issue. 

The vast majority of recruiting tools in the market either help spread awareness of openings (e.g., job boards) or source lists and databases where recruiters then play a numbers game. That’s why even with all of the tech advances in the market, physician searches are taking longer than ever.


Given the labor pool drought and the frenzied state of healthcare recruiting, let’s understand why – now more than ever – recruiters prize passive job candidates. 

One of the most underutilized solutions within healthcare recruiting involves tapping the giant pool of passive candidates. These are clinicians who are currently employed and not actively looking but who might consider taking a new job if the right one came along.

In the world of clinicians, only 10.5% of the workforce is defined as actively looking. And every recruiter is competing for and picking apart this tiny pool. It’s a highly crowded and competitive little space, and healthcare facilities in less desirable areas are at a distinct disadvantage in this tug-of-war for active candidates. 

On the other hand, 73% of the global workforce is “passive,” offering a higher likelihood that within this pool there will be an ideal candidate who will be interested in and within reach for any given open position.

More than half of the physicians surveyed in a New England Journal of Medicine questionnaire said they have actually looked for a position within the past two years. However, most of those physicians are not classified as “active”, nor are they on the radars of in-house recruiters. 

But it’s not just the size of the talent pool that explains why recruiters prefer to search amongst passive candidates. 

Anecdotally, passive candidates are likely to be better fits and stay longer. They’re not desperate for a job, so there’s a sense that they’re making decisions based upon a true fit instead of bare necessity.

Conversely, active candidates elicit natural questions for recruiters. Why is this candidate looking? Is there a reason they don’t have a job? Were they fired? Did they have an issue with their team? And indeed, recruiters sometimes find that some active candidates turn out to be focused solely on the highest paying job and pit organizations against each other to do so.

All of this explains why clinician recruiters seek out passive candidates, especially for hard-to-fill positions in specialized sectors. 

The problem is that passive candidates are also highly elusive. By definition, passive candidates aren’t looking. 

Clinical recruiters know that they simply must get much better at targeting passive candidates. But they don’t have the tools to do this effectively or at scale. The majority of tools and platforms that are saturating the recruiting market don’t help recruiters identify passive candidates, only active ones.

Recruiters are thus forced to go through a laborious manual process of cold outreach, general marketing tactics, and fishing expeditions. 

Who has time for this? It’s a lot easier to just stick with the active candidates who are actually looking. 

That’s why the vast majority of in-house recruiters and third-parties focus solely on the 10.5% of clinical providers actively looking for a new home. This only represents 13% of those willing to leave their jobs.

Only an AI solution like Winnow allows recruiters to capture the other 73%.


Every candidate exists on a spectrum of success for a given organization. When it comes to passive candidates, the key is to understand not just their qualifications for the position but also their potential motivation to be interested.

For clinicians, a candidate who accepts a new job often has to uproot their families from their home, school, and community. What criteria will spur a passive candidate to make such a huge shift? Especially if that facility you’re recruiting for is in a rural, unknown location?

If a recruiter is blindly pursuing every qualified passive candidate, they have no way of knowing how to prioritize or target their efforts. Only through predictive analytics can recruiters understand where to focus their efforts and how. 

There is literally no way to passively recruit without AI predictions.

How does AI recruitment work in action? Let’s look at Winnow’s process.

We use AI to compile profiles for all clinical providers, whether they’re active or passive candidates. This amounts to sourcing trillions of data points total, with hundreds for each candidate, including personal contact information.

Candidates meeting specified criteria are then AI-screened through predictive analysis modeling to provide a list of best-aligned fits. Candidates are stack-ranked based on predictive alignment according to factors listed by the hiring facility. Recruiters are then equipped with predictive insights to vastly improve their engagement with candidates. 

When in-house recruiters are armed with insights on a candidate’s preferences and network connections, their outreach efforts are far more effective. With Winnow, that translates into a 10x higher click-thru rate and an industry-leading response rate.

We offer recruiters pre-built email templates with different themes based on the critical factors that will be enticing to the candidate. For example, this could be a reference to the improvement in standard of living, to an old schoolmate at the hiring facility, or dozens of other attention-grabbing subjects. Our AI models can pinpoint the motivating factors that will trigger the interest of a passive candidate.

Winnow then automatically tracks the effectiveness of our outreach, click-thru rates, candidates in the pipeline, and much more. In this way, we fuel machine learning that perfects our models over time.


Passive candidates represent the largest and most promising candidate pool for clinical recruiters. AI now offers recruiters a path to not just pursue these candidates, but to effectively target and engage with them.

Amidst the crisis in healthcare recruiting, leveraging AI to prioritize and pursue the right passive candidates is an essential approach for successfully filling clinical positions with long-term fits.

Paul Vernich is CEO of Winnow, a healthcare recruiting solution that uses AI to dramatically reduce recruitment cycles and costs.

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