|*How will this kitten group affect the overall shelter’s LOS?|
While we have discussed length of stay (LOS) in a few different contexts already, we have yet to talk about the myriad of ways it can be calculated and what information each of those calculations lends to managing an animal populations. Similar to calculations for human patients in a hospital, LOS in its most simplistic definition is the intake date minus the outcome date, and again related to hospital computing, if a group finds itself lucky enough to have a relinquished animal come in and leave within the same day, I always advise groups to count that animal’s LOS as one day. Individual animals have personal lengths of stay and groups of animals contribute to average lengths of stay. It is within this latter aggregate group that the power of the LOS statistic shines through.
The first step in gathering meaningful information from aggregate LOS is to define cohorts of animals you are interested in analyzing. Presented below are some suggestions for analysis and descriptions of what benefits the data offer. All the calculation proposals below can also be subdivided into animal groups such as all dogs, all cats, all animals, just puppies, just kittens, etc.
- Intake Cohorts: Calculating an average length of stay for animals grouped together by the month (or week, or day, etc) they came in to the shelter. Tracking LOS in this manner will give you insight to any seasonal variations in your shelter’s operations and how your population management handled things. Does the January Intake Cohort move through quickly compared to the July Intake Cohort? Using historical LOS data from last year’s Intake Cohorts, shelter managers can make decisions about enlisting additional resources such as foster homes, staffing, or volunteers to help alleviate anticipated increases in LOS during particular time periods. One limitation to using this calculation is that you might not get stable data until many months (or weeks, or days, etc) after the intake month under consideration has passed. If your group routinely moves animals through within 15-20 days, then this will not be such a problem, but if your shelter does not, then it may take a while for all members of this cohort to have an outcome, and have their data contribute to the calculation. For example, if the shelter manager was calculating the February Intake Cohort’s LOS, he or she might have to wait until April to do so as those animals that came into the shelter in late February will need time to pass through the system.
- Outcome Cohorts: Calculating an average length of stay for animals grouped together by the month (or week, or day, etc) they left the shelter. This can show insight into the health of a shelter’s adoption and/or transfer program. And, opposite of the Intake Cohort limitation mentioned above, Outcome Cohorts can be calculated immediately for their specified time period. For example, if a shelter manager was calculating the February Outcome Cohort’s LOS, he or she can do so on March 1.
- Current Cohort: Calculating the average length of stay for all animals at your facility at this moment in time, regardless of intake date. This is probably as close to real-time shelter data as a shelter manager can get! Again, this particular calculation can give insight into the shape of your adoption/transfer program, but can also give a shelter manager clues about the overall well-being and health of the population. Animals that are ill or need extended care will increase this calculation, whereas a healthy population will move through the system quickly and therefore have a shorter LOS.
- Stage/Location Cohorts: It is also useful to calculate a LOS statistic for animals in specific stages or locations within a shelter system. Much like the calculation for Current Cohorts, monitoring the data from a Stage/Location Cohort will ensure that bottlenecks for whatever reason are noticed and addressed before they affect the greater population. Examples of possible stages and locations to monitor include:Intake Type Cohorts: Calculating LOS for intake types such as owner guardian surrenders, strays, transfer animals, or emergency response intakes, can give a shelter manager understanding of the burden that these subcategories of animals place on the global shelter system. For example, if a shelter takes in a large transfer group from another shelter or even a hoarding situation, it will be useful to track both the transfer group’s LOS, as well as all other animal’s LOS. If we see a rise in the LOS for all other animals (compared to data for this group from pervious months or time period), that is an indication that perhaps the transfer group was too burdensome or overwhelming for this shelter’s operations as it affected the data for these other animals in the shelter’s care at that time. From this, shelter managers can create operation protocols for dealing with such burdens so that the rest of the population is not affected.
- Adoption Rooms
- Foster Stays
- Rehabilitation Rooms
- Outcome Type Cohorts: Calculating LOS for outcome types such as adoption, transfer out, euthanasia, etc. This will inform shelter staff as to the efficiency of daily operations, as well as the health and well-being of their population. For example, if a shelter euthanizes animals, it is imperative to watch this LOS so that efficiency is managed. Although euthanasia is not always a predictable outcome and shelters would like to give all animals as much of a chance as possible, if Outcome Euthanasia LOS increases, it might be indicative of unnecessarily delaying inevitable outcomes.
The second step in monitoring LOS statistics is to set goals or benchmarks for each of the categories of data a shelter is tracking. I would recommend monitoring data for a year before determining baseline statistics. Although one year seems long, you must account for seasonal fluctuations and therefore need the entire year to see a complete picture of your shelter. Once baseline is established, go ahead and set goals for each category. This will help focus operations and will certainly drive decisions made around the shelter. And again, based on any seasonal fluctuations recorded in your baseline data, it would be good practice to set fluctuating benchmarks to accommodate the ups and downs. All of us shelter workers know all too well what the warmer months (i.e., “kitten season”) can do to a shelter’s numbers, so it is acceptable to adjust your expectations at this time based on what your baseline is telling you.
What types of LOS does your shelter track? Has knowing your LOS been beneficial to your organization and staff? Does your shelter set goals or benchmarks? What happens if you do not hit your benchmark?
*Photo courtesy of Chris Tanaka