Some bar-napkin math on income and therapist density by county.
My home state of California is out with a number of new reports assessing its mental health workforce,* with an eye toward ensuring that we have a future workforce adequate to meet the demand for mental health services. The reports are rich with data, much of it interesting; you’ll find, for example, that it seems to be mid-sized counties, rather than heavily populated urban areas like Los Angeles, that are most overpopulated with therapists.
You’ll also find that a lot of that is driven by a single county: Marin County, north of San Francisco and famous for, well, this kind of thing, has a whopping 600 licensed therapists for every 100,000 residents. Add unlicensed interns and trainees to that number, and Marin probably has at least one therapist for every hundred and fifty people. Just for contrast, San Diego county — which is often thought of as being overpopulated with therapists — has about 200 licensees for every 100,000 people, or about one-third the therapist density of Marin County, and San Diego is still just a bit above the state average.
Anyway, I wondered whether I could use this data to figure out where the best places in the state would be to start a private practice, if you’re newly licensed and relatively mobile. The short answer, happily, is yes — to figure out where opportunity lies, we really only need two statistics, and they both are readily available:
- Therapist density tells us how thoroughly a geographic area is already saturated with therapists (the more saturated, the harder to compete there). For this analysis, I included licensed psychologists, marriage and family therapists, clinical social workers, and professional clinical counselors.
- Average income tells us, at least indirectly, whether the people living in that area could afford your services (remember, we’re talking about private practice here).
Of course, there are plenty of other factors that would matter too,** so this analysis is definitely bar-napkin math and not formal scientific inquiry. But based just on the two factors above, where is the best place in California to set up a private practice as a psychotherapist?
I ran the analysis two ways. First, I took per-capita income and subtracted $17,505 — 1.5 times the current federal poverty level for an individual — figuring that at the lowest income ranges, it’s tough to afford therapy (especially from private practitioners). I took what remained and divided it by therapist density (therapists per 100,000 residents) to get a quick-and-dirty number we’ll call the “opportunity index.” And the winners are:
Private practice opportunity based on per-capita income
Those top three counties are all small, population-wise; they have 3, 1, and 14 licensed practitioners residing in them, respectively. And Alpine County has fewer than 1,200 residents. But before you go thinking that this method advantages the smaller counties, note that five of the others in the top ten have more than 1,300 licensed providers each. There are a few counties of interest further down the list, too; despite its high therapist density, Marin County comes in at a middle-of-the-road 30th of the state’s 58 counties, due largely to the county’s very high income average. And in this analysis, Marin still appears to be a better place to set up shop than Santa Barbara, San Bernardino, and Los Angeles counties, which came in 33rd, 36th, and 38th places.
But wait! Per capita income isn’t the only way, and arguably isn’t the best way, of measuring income for this kind of analysis. So I ran the data again, this time trying to account for family size. (Here’s the explanation for the data nerds, others can safely skip: I took the average household income for a county, and divided it by the per capita income, to get a sense of average household size. I then came up with an estimate of federal poverty level based on the household size, multiplied that by 1.5, subtracted that from household income, and divided that number by the number of therapists per 100,000 residents. Fun, eh?) Running the numbers this way produced similar-but-different results, since counties vary pretty widely in household size, and since per-capita income only partially correlates with household income.
Private practice opportunity based on household income
Colusa County, with a moderate average household income ($49,558) and very low therapist density (just three licensees for its roughly 21,000 residents) just obliterates the competition here. (San Joaquin County is at the top if you leave out counties with a population of fewer than 500,000.) Imperial County jumps to #2 here, from the bottom of the per-capita list, largely as a function of how I did the formulas — because the per-capita income in Imperial County is less than 1.5 times the poverty rate, its Opportunity Index was below zero when computed based on individual income.
So, hey, this is bar-napkin math, but is there anything to be learned here? I think so. If I were you, I wouldn’t go making major life decisions based on this informal of an analysis, but here’s what I would take away from this:
- There’s opportunity in rural areas, but those aren’t the only places of opportunity for therapists looking to set up shop. Even some of the state’s larger counties are below average in therapist density; I was surprised to see that Orange County is solidly middle-of-the-road on that statistic, with 176.5 therapists per 100,000 residents. Same with Ventura County at 169.2. Another way to say this: Some of the biggest counties by population aren’t as awash in therapists as we think they are, especially if we get out of the most therapist-heavy neighborhoods, where competition is naturally the most fierce.
- Therapists congregate in richer counties more than they congregate in bigger counties. There’s a link between county size and average income, but therapist density appears to more closely track wealth than it does the population numbers. If you rank the counties by per-capita income, 14 of the top 17 have greater-than-average therapist densities, and it’s a substantial difference: The state average for therapist density is 183.8, but those 17 wealthiest counties average more than 290 therapists per 100,000 population — more than 50% above the norm for the state as a whole. In other words, you may find greater opportunity to make a living in middle-class counties than in richer ones. Riverside County is a good example, with less than half the average therapist density and a fairly typical household income average.
- Take a second look at some places you may have written off. There are a surprising number of counties in the state that have enough of a combination of available wealth and underserved population that they present tremendous opportunities for new therapists. Solano County, nestled between San Francisco and Sacramento, comes in at 15th in both rankings (by per-capita income and by household income); it’s fairly wealthy and has about 20% fewer therapists than the state average.
I think those are worthwhile lessons. There’s plenty of opportunity for private-practice therapists in California, if you know where — and how — to find it.
Some quick notes about the data here: Therapist density comes from this report, which takes licensing board information on the number of licensees of various types in each county and compares that with census data on population. The data is from 2013. Median household income comes from the Census Bureau’s American Community Survey in 2011, by way of Wikipedia.
* That link is to the summary. Here are the reports themsleves: 1 2 3 4 5
** Even leaving aside all the personal factors driving your decision about where to live and work, if you only speak English and half of your local population is Spanish-speaking, that obviously impacts your ability to make money from your practice. County size could matter too, given that some of the state’s counties are geographically enormous and residents may not want to travel to your office even if it is in the same county. I could go on, and surely you could think of plenty of other factors that would weigh in your decision-making. Like I said, this isn’t exactly a formal scientific analysis.