Nearly every time we work with consulting clients working on implementing integrated care the complaint is the same. There’s a healthcare administrator breathing down their neck about how many scheduling slots are going unutilized. It’s as if the golden hammer of healthcare optimization is managing slots.

It’s time we call this what it is – lazy healthcare administration.

I don’t mean to get personal here – there are many fine healthcare administrators and I personally think the field gets a bad rap, but I have seen this enough times where you’ve got to call a spade a spade.

Slot utilization is not a meaningful metric for PCBH or CoCM. In fact, relying on it reveals something deeper: a system still viewing integrated care through a specialty-care lens—where individual clinicians “fill their schedules” instead of teams caring for populations. It’s a lazy metric because it measures the wrong thing and reinforces the wrong behaviors. In fact, it often subverts the goals of administrators because it also yields lower overall raw productivity, especially in the long run.

Now this last statement still requires validation through research, something I’m interested in tackling here at CFHA: The Integrated Care Association. But our experience in close to a decade of working with clients as part of our Technical Assistance program is that attempts to pre-fill spots only re-creates the conditions integrated care was brought in to solve: high no-shows due to pre-booked slots far in advance of appointments, and decreased contact between referrers (PCPs) and BHCs/care managers resulting in lower referrals (lower trust, top-of-mind awareness). And thus, lower billable activity.

And most frustratingly, it ignores the reality that BHCs and care managers are not responsible for surfacing their own patients. Primary care teams are. (So who should we be talking to if utilization is low if not the teams themselves?!)

Why Slot Utilization Fails Integrated Care

Slot utilization assumes:

• Clinicians should be scheduled like specialists.
• Their efficiency is defined by volume of pre-booked encounters.
• Demand is clinician-driven rather than population-driven.

None of these assumptions fits PCBH or CoCM.

1. PCBH Is Built on Access, Not Slots

The PCBH model is fundamentally an access model. When we measure it with specialty-care metrics, we distort the model.

The right metrics:

• Population penetration at the team level. Are BHCs reaching 10–20% of the panel? Are they available when the team needs them?
• Unique patients seen per day at the individual level. A BHC seeing 8-12 patients per day is reaching max productivity. And they should be seeing a high number of unique patients so their visit cadence can be measured by looking at mean time to follow-up rates in these categories: 1-2 weeks; 3-4 weeks; 5+ weeks (should be well distributed versus bringing all patients back in the same time frame)
• Warm handoffs. Not because the number itself is sacred, but because warm handoffs reflect real-time responsiveness to team need. We usually shoot for 50% warm handoffs per day.

A BHC who leaves 50% of their day unfilled because they are immediately available for warm handoffs is more effective—not less—than one who is fully booked.

Slot utilization cannot see that.

2. CoCM Is About Active Caseloads, Not Calendar Density

The Collaborative Care Model is designed around registry-driven, population-level care. The main productivity metrics that matters are:

• Active patients per care manager per time period (mean or raw).
• Billable patients per month per month.

A full panel is a sign of clinical reach and population impact. Whether a care manager had “open slots” on Tuesday afternoon tells us nothing.

CoCM care managers work asynchronously, flexibly, and in short bursts across dozens of patients. This cannot be reduced to a template of 30-minute appointments.

Slot utilization misses 80% of the actual work.

3. BHCs and Care Managers Don’t Generate Their Own Demand

The biggest flaw in slot-based thinking is that it treats behavioral health like a storefront—open the doors and hope “customers” show up.

But in integrated care:

• Primary care drives demand.
• Team processes surface needs.
• Registries identify gaps.
• Workflows—not marketing—bring patients.

At best slot utilization is an evaluation of how well the system drives patients to behavioral health—not the performance of the BHC or care manager. Measuring them by a variable they cannot control is both unfair and uninformative.

It’s the equivalent of evaluating a lab tech on how many labs the PCPs ordered that day.

So What Should Healthcare Admins Do To Maximize Billable Efficiency?

OK, time to help our healthcare administrators out. The above metrics are indeed the right ways to measure PCBH and CoCM but they don’t map out neatly to monitoring personnel or ensuring financial efficiency. In other words, they won’t get the bean counters off your back.

Here’s my recommendation: Act as a bridge between finance and clinical.

1. Nail finance down on a dollar amount needed from the behavioral health service line for a specified time period (I suggest 6 months).
2. Then work with your clinical teams to fine-tune this number and figure out how much activity would be needed to reach that goal within the operation of the integrated care model (eg. X number of active cases; X number of billable patients seen per day). Walk that number back to finance if it is outside the scope of the model/ personnel performance ranges to seek additional refinement.
3. Once both sides have settled on a number, then go back to the clinical team and make a plan for how to engage and monitor the referrers for those services (eg. typically the PCPs). At that point you have a clear financial metric, not a sloppy proxy metric like slots utilized and you have consensus on the goal from your major stakeholders.
4. Your last step is to actually hold the right people accountable for the right activities. The behavioral health personnel can only be held accountable for doing the work that is placed in front of them. The referrers are the ones who can be held accountable for referring or not referring. That should mean you develop metrics for the referrers. It should also naturally lead to process improvements like automated reports on patients likely eligible for behavioral health support per day to ease the job of the referrers in case finding.

Can We Agree To Eliminate Slot Utilization From Our Lexicon?

So by now you probably know I have a hate-hate relationship with slot utilization as a metric. To be honest it stems from my early days in primary care when I saw my PCP colleagues hammered by administrators for unused slots on their schedules. Now I am well aware of the history of PCPs and administration fighting over time slots, visit types and other strategies to make a primary care day both livable and financially viable. But take my word for it, this is not that fight. Forget you ever learned about slots in healthcare administration school when it comes to integrated care and start measuring what actually makes this work clinically and financially.

Photo by Daniel Herron on Unsplash