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Brookings issued a study recently on the impact of entry restrictions to certain majors at research universities. You might expect community colleges to be exempt from that dilemma, but they really aren’t.  

The most commonly restricted majors, in my experience, are in allied health fields. That’s largely because of limited numbers of clinical placements in a given region, although one could argue that programmatic accreditors’ desires for set minimum pass rates on the NCLEX and similar exams also reward gatekeeping.

I’ve seen a few different ways of allocating seats when there are more students who want them than there are clinical placements to take them.

One is a relatively strict competition using an entrance test (often TEAS) combined with a GPA requirement in prerequisite courses, like biology. It’s similar to the way that selective colleges do admissions, but the grades examined are in actual college courses. The idea is that success in courses like biology offer some sense of the likelihood of success in the program, and all else being equal, it’s best to allocate scarce seats to students who are most likely to succeed.

The drawbacks here are several. First, it adds time to everyone’s degree. Second, it puts many students through courses that wind up not having a payoff. Third, in the absence of concerted effort (which now invites a new level of legal scrutiny), it tends to select for students who bring greater social capital when they arrive. Finally, it’s in uncomfortable tension with the open-admissions mission of community colleges.

A second approach is a straightforward wait list: first come, first serve. That gets around issues with standardized tests, but it also adds time to degree and may allocate seats to students who are unlikely to finish. It rewards the ability to wait, which is unevenly distributed. When the wait lists get too long, sometimes students decamp for for-profit providers instead, which tend to charge more and succeed less.

Yet another approach, which many colleges seem to be backing into, is using high program fees as a de facto pricing exclusion: keep raising fees until the number of willing buyers matches the supply. Veterans of Econ 101 will recognize this as the textbook method for allocating scarce goods in a market economy. This method selects for ability to pay (or willingness to risk it), as opposed to demonstrated talent. It’s a for-profit model. As such, it tends to default to people who either already have the money or who have a potentially catastrophic risk tolerance. It’s not obvious to me that it’s the best way to staff our hospitals.

A recent supply-side innovation with promise involves the increased use of high-tech patient simulators. As simulators have become more sophisticated, in some domains they’ve been able to reduce the number of hours “on the floor” that a given student needs, thereby allowing more students. Over the course of my career, I’ve seen the sophistication of the simulators improve dramatically, and I expect that trend to continue. Simulators also allow for greater control over what students will experience. For example, a simulator can give birth multiple times per day, on command. In an actual hospital, you get the patients who are there at the time; if nobody comes in during your rotation with a given condition, too bad.

Still, as good as simulators are for certain things, there’s nothing like being on the floor. The preceptors need to see how the students handle having multiple patients at once, how they respond to stress and how they work with patients who sometimes talk back. Simulators can help, but they only get you so far.

We had a nursing shortage before the pandemic; it’s considerably worse now. In this context, one would hope to see the barriers to entry reduced. But the health-care system has been so stretched by the pandemic that it lacks much slack to devote to teaching, so clinical placements remain at a premium. Given greater demand for seats than supply, we still need some selection mechanism.

Wise and worldly readers, is there a better selection mechanism? If so, I’d love to hear about it. I can be reached at deandad (at) gmail (dot) com, on Twitter at @deandad or on Mastodon at @deandad at-sign masto (dot) ai. Thanks!

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