Sizing the run rate: The cost of a 1:1 sitter
What does a continuous 1:1 sitter actually cost your behavioral health unit? We size the run rate, the first half of PLGL, with three inputs you already have.
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Sizing the run rate: What a single 1:1 sitter actually costs a unit a year
Series 2 · The Economics of Safety · Blog 2
Patient Liability & Grievous Loss (PLGL): Understanding the run rate
We started this series with an overview of a term we introduced: Patient Liability and Grievous Loss (PLGL). It’s a direct approach to sizing the cost of risk within a behavioral health hospital, and it has two pieces: the run rate and the tail. The run rate is the cost of a sitter. The tail is the catastrophic events you don’t size for, but that can carry an outsized impact when they happen.
In this piece, we take a deeper dive into sizing the first element: the run rate. It is the initial step in calculating your own PLGL.
Our goal here is simple: give you a clear view of what “watching” actually costs in your facility, so you can start to look at it differently.
Let’s begin with the cost of a sitter.
Daily sitter costs: The true price of 1:1 continuous observation
What do you think it costs to run a continuous 1:1 for a single day? We consulted the independent literature and found the number to be about $561 per day, fully loaded. A separate 2026 analysis of loaded nursing costs puts a comparable day near $586, which corroborates the range. That’s what “watching” costs, per patient, per day.
The annual cost basis of continuous patient observation
Now let’s zoom out. If you ran a 1:1 with one patient every single day, all year, that’s about $205,000 a year (365 × $561). Obviously you aren’t going to run that way for a single patient, but depending on the size of your facility and how often you place patients on continuous observation, the cumulative costs can easily reach seven figures, and it often goes unnoticed.
But I hear you: that’s not how you experience this cost. It shows up patient by patient, day by day, not as one continuous line.
So let’s model it the way it happens, on a per-bed basis.
What is an "at-risk bed" in behavioral health?
First, let’s ensure we are defining things the same way. When we say at-risk bed, we mean a bed where a patient could plausibly be placed on continuous 1:1 observation during their stay, not your total licensed bed count. It’s the subset of your census where this cost could land.
Calculating sitter costs per at-risk bed
Of your at-risk beds, how many patients go on a continuous 1:1 in a year, and for how many days each? The independent literature puts continuous observation at 13 to 16% of psychiatric inpatients at some point during their stay (Barnicot et al., 2017). For argument’s sake, say your at-risk beds carry 15 to 20 full days of 1:1 across the year at $561 a day. That’s a modeled blend of about $8,000 to $11,200 per at-risk bed a year.
How to calculate your hospital's PLGL run rate
To calculate it yourself, it only takes three inputs you should already have at hand: your loaded daily rate, the days of 1:1 per at-risk bed, and the number of at-risk beds. Run your own numbers. Make sure you’re sitting down when you do (and remember, this is only the first piece of PLGL).
What would that money fund clinically? What does it buy your patients therapeutically?
The stark reality is that even a small unit is spending six to seven figures a year on watching. And if that’s your internal day rate, what happens when you have to utilize agency or overtime?
Modernizing inpatient observation through technology
As you’re hopefully starting to see, sizing PLGL shines a direct light on a high-cost legacy workflow, one that innovation and technology can help support more therapeutically, more efficiently, and more effectively.
In my next piece, we’ll shift from the model to the daily realities on the ground. In other words, the actual cost basis you’re starting from when you look at this closely. And now that you can see it, we can start talking about how to manage it, and how innovation can provide the augmented support needed to watch in a better, more efficient way.
Author: Todd Haedrich, CEO, LIO