Measuring Length of Stay for Hospitalists

When you’re running a hospitalist program, there are lots of metrics you can look at to help you get a handle on how your practice is doing.  As the saying goes, you can’t manage what you don’t measure.  So, as the start of an ongoing series, I’d like to talk about some of the metrics I like to use to help me better understand how my practice is running.

One of the first things we tend to look at as hospitalists is length of stay (LOS).  This is important for lots of reasons.  It affects how many beds are occupied, patient flow, costs, and more.  However, given hospitalist staffing models, it can be very difficult to attribute the length of stay to one doctor.  Who is the LOS assigned to – the admitting doc, the discharging doc, the doc who rounded on the patient the most times?  All of these have their pros and cons, but none of them really give you the full picture.  Maybe I inherited a patient today who has been in the hospital for 11 days already, and now I discharge him.  Do I now have an 11-day LOS on my record?  Doesn’t seem quite fair.  Fortunately, there’s an excellent option that you have ready access to.

If you’re not admitting a patient, when you have an encounter, there’s really only two things you can do – you can keep the patient for another day, or you can discharge them.  So, what we can look at it is how likely am I to discharge a patient when I have the opportunity to do so?  This leads to a simple formula:

Discharges/Opportunities to discharge

What is an opportunity to discharge?  It’s a visit that isn’t an admission.  So, that means the equation looks more like:

Discharges/(daily visits + discharges)

So, if I have 16 patients on my service at the start of the day, do 2 admissions, and discharge 5 patients, it yields the following:

5/16 = 0.3125

(Note that the two patients I admitted during the day don’t count as part of the denominator because they weren’t an opportunity to discharge.)

So basically, I discharged 31% of the patients that I had an opportunity to discharge.  If you want to turn this into an individual LOS for me as a doc, you can just invert the fraction.  So, 5/16 becomes 16/5 = LOS of 3.2 days.

This can be used best over longer periods of time.  Maybe for the week, I’ve had 112 opportunities, and I’ve done 28 discharges.  So, 28/112 = 0.25, which yields a LOS of 4.0 days.  You can obviously use this over as long a period of time as you want.

The beauty of this metric is that it lets me do several things.  It lets me track data over time, and generate an individual LOS for each hospitalist that I can use to evaluate the team.  Some docs will be higher, and some docs will be lower – and that’s OK.  But it does let me see outliers who may need some further discussions regarding the appropriateness of their discharges (either too early or too late). I can then even use readmission data to get a sense of whether these outlier LOS are leading to changes in the readmission rate.

I can also use this data while scheduling.  Have you ever noticed that some weeks the hospital is super full, and other weeks it’s less busy?  This may be based on your staffing.  If you have lots of docs with long individual LOS on the service for the week, fewer patients will be discharged, and the census will grow.  If you have more docs with lower LOS on service, the census will likely go down.  By the end of the week everyone will be very busy, or less busy based on who is working.  Instead, you can use this data to help you choose who is working each week, and make sure you balance your longer LOS docs with shorter LOS docs, so the hospital doesn’t get overwhelmed with patients and a census that is too high.

You could even use short term variation in LOS to see if your docs need help.  If my typical LOS is 3.5, but over the last few days it’s been 4.5, maybe there’s something afoot.  Maybe my patients are very ill, or I’m doing too many admissions, or there’s something else going on that is interfering with my work.  This can be an early warning indicator that something is wrong and allow you to intervene in a timely manner to help the team.

While it’s very simple, and easy to calculate, the potential benefits of using this bit of data to manage your practice are enormous. 

Next time we’ll talk a little about the financial side of things and look at E&M distributions.