Over the past quarter century, the live release rate (LRR) has become the dominant indicator of animal shelter performance in the United States and increasingly abroad. The benchmark most often cited — saving at least 90% of animals entering a facility — has been widely adopted as the operational definition of “no-kill.” This metric has played an important historical role in shifting expectations toward lifesaving and accountability.
However, reliance on a single outcome percentage as the primary measure of success risks oversimplifying a complex biological, logistical, and ethical system. As the field of shelter medicine and animal welfare science matures, evidence suggests that outcome metrics alone cannot adequately represent operational efficiency, animal welfare conditions, or long-term sustainability.
A more comprehensive evaluation requires attention not only to what happens to animals at exit, but to how they move through the system — and what occurs during their time in care.
Outcome Metrics and Their Limits
Outcome measures such as LRR capture the proportion of animals leaving a shelter alive through adoption, transfer, or return to owner. They are valuable for assessing lifesaving impact and for communicating performance to the public.
Yet outcome metrics are inherently retrospective. They provide limited insight into the processes that generate those outcomes.
Two shelters may report identical LRRs while operating under markedly different conditions. One may maintain efficient throughput, stable capacity, and low stress environments. Another may accumulate a growing population of long-stay animals, operating near or beyond humane capacity while temporarily sustaining high live outcomes.
In such cases, the outcome percentage alone obscures critical differences in welfare and operational risk.
Length of Stay as a Central System Variable
Length of stay (LOS) is increasingly recognized as a key determinant of shelter capacity, disease transmission risk, staffing demands, and animal welfare. Time in care is not a neutral variable; it drives resource consumption and biological stress.
Research across veterinary and shelter medicine literature indicates that prolonged confinement is associated with increased susceptibility to infectious disease, behavioral deterioration, and reduced adoptability. The relationship between LOS and welfare outcomes parallels findings in hospital operations research, where extended stays constrain capacity and degrade system performance.
Thus, LOS functions as a throughput parameter governing the stability of the entire system.
Measurement Distortions in Traditional LOS Calculations
A critical methodological issue arises in how LOS is typically calculated. Many shelters compute average LOS using only animals whose stays ended during a reporting period. This approach excludes animals present at the start of the period (left truncation) and those still in care at the end (right censoring).
These exclusions disproportionately remove long-stay animals from analysis — precisely those most likely to experience welfare challenges and contribute to crowding.
A recent peer-reviewed study employing survival analysis techniques, including Kaplan–Meier estimators and Cox proportional hazards models, demonstrates that incorporating all animals present during a period produces markedly different interpretations of shelter dynamics. When censoring is properly addressed, trends that appear unfavorable under traditional methods may reverse, and vice versa.
This finding has significant implications for decision-making. Leaders relying on biased LOS estimates may misjudge whether conditions are improving or deteriorating.
The Hidden Population of Long-Stay Animals
Long-stay animals represent both a welfare concern and an operational risk. Extended confinement can lead to chronic stress, immune suppression, and behavioral changes that further prolong stay duration — creating a feedback loop.
Studies of shelter dog behavior have shown that specific stress-related behaviors correlate strongly with increased time to adoption. As stays lengthen, animals may become less adoptable, increasing the likelihood of continued accumulation.
Traditional outcome metrics do not reveal the size or trajectory of this population.
Capacity as a Flow Problem
Animal shelters operate as dynamic intake-and-outcome systems. Stability depends on balancing incoming animals with the capacity to produce timely, humane outcomes.
If intake exceeds throughput capacity, animals accumulate, regardless of outcome percentages. Overcrowding elevates disease risk, reduces care quality, and increases staff burnout. High LRRs may persist temporarily but become increasingly difficult to sustain.
Operations research in healthcare has long recognized that throughput and length of stay determine effective capacity. Similar principles apply to animal sheltering.
The Limitations of the “No-Kill” Threshold
The 90% benchmark provides a clear and motivating target, but it does not measure:
- crowding levels
- welfare conditions during stays
- disease incidence
- staff sustainability
- hidden backlog
A shelter could theoretically meet the threshold while operating beyond humane limits if long-stay animals accumulate without exiting.
This observation does not diminish the moral imperative of lifesaving. Rather, it underscores the need for additional metrics to ensure that lifesaving efforts remain humane and sustainable.
Toward a More Comprehensive Measurement Framework
A balanced evaluation of shelter performance should integrate outcome metrics with flow-based indicators, including:
- Median and distributional LOS measures that include animals still in care
- Tracking of long-stay populations (e.g., upper percentiles)
- Stratification by species, age, size, and medical needs
- Intake-to-capacity alignment
Such measures provide a more accurate picture of operational health and welfare conditions.
Implications for Policy and Oversight
Policymakers, funders, and oversight bodies should consider revising reporting standards to include flow metrics alongside outcome percentages. Transparent reporting of LOS distributions and long-stay populations would enhance accountability and public trust.
Funding criteria tied exclusively to outcome metrics may inadvertently encourage short-term optimization at the expense of long-term stability. Incorporating capacity and welfare indicators could better align incentives with humane outcomes.
Conclusion
The lifesaving advances associated with the “no-kill” movement represent a historic achievement in animal welfare. Yet as the field evolves, its measurement tools must also evolve.
Outcome percentages tell us what happened. Flow metrics reveal what is happening.
Responsible stewardship of animals requires both.
A comprehensive framework that integrates outcomes, throughput, and welfare conditions offers a more truthful and actionable understanding of shelter performance — one capable of sustaining progress rather than merely reporting it.
References (Selected)
Mavrovouniotis, M. L. (2026). Use of Kaplan–Meier and Cox regressions in the distribution of length of stay in animal shelters. PLOS ONE.
Protopopova, A., et al. (2014). In-kennel behavior predicts length of stay in shelter dogs. PLOS ONE.
van der Leij, W. J. R., et al. (2023). Intake, stay, and outcome metrics in shelter populations. PLOS ONE.
Miller, L., & Hurley, K. (2018). Infectious Disease Management in Animal Shelters.
Campbell, D. T. (1976). Assessing the impact of planned social change.
Goodhart, C. A. E. (1975). Problems of monetary management: The U.K. experience.
This article was partially composed using AI technology
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