One of the early concerns when starting to build a practice is how to have enough referrals for a stable caseload. Most studies show that when a client comes for treatment, they will stay for 8 sessions on average. In the practice I managed, we did our own internal studies across our 40 clinicians in our three locations. We found that on average our clients stayed 10 sessions for a course of treatment.
With this 8 to 10 session number, we can calculate how many referrals it takes to generate a 1000-session caseload.
Putting the numbers together looks like this:
1000 ÷ 8 = 125 cases per year, which is almost 10 per month, or 2.5 new clients per week
Of course they do not need to be totally all new clients. Returning clients are valuable as well. In fact as you stay in the same location for years, former clients, many who become returning clients, are your best advertisement. They are your walking billboard leading to more than enough referrals for a stable caseload.
So this leads to the mystery question: How many positive contacts with referrers do you need to make to have 2.5 new cases show up each week? For example, how many people have to consider calling you for therapy for each one that does actually call? No one knows the answer exactly. But clearly we can see that lots of people need to know about us to have a sufficient number who actually do call; way more than 2.5 clients per week. This highlights the importance of consistent marketing efforts. (See how we did it in this post: A community-based marketing method: Community Connection Plans).
In the practice I managed, we learned that not all clinicians were the same. They varied a lot in how many new referrals were needed to support their full-time caseload. From our study, our therapists needed from about 50 to 140 new cases a year to support a “full-time caseload.” Clearly such large variability suggests that there are many factors that affect how many actual referrals are needed.
In other posts I write about how we looked at the therapists who had higher retention rates—and therefore required fewer new cases to sustain them—to see if we could find patterns that keep people engaged in therapy. See if you agree with our analysis.
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