Hospital administrators have long assumed that shorter hospital stays equal cost savings, but a new study from analytics firm SAS and the Duke University Health system is challenging that notion, at least for neonatal intensive care units.
Published in the Journal of Perinatology, the research applied a discrete event simulation model of the Duke NICU to predict outcomes and costs using pre-existing study data from the National Institutes of Health Neonatal Research Network.
Results showed that in a composite NICU with the best possible outcomes, the length of stay actually averages three days longer than in a unit with poor outcomes -- with comparable annual costs at $3 million less.
Among the other key findings: The average length of stay for infants of 28 weeks or less of gestational age was 20 days longer than that of older infants -- 86 days versus 66 days. But the average cost per patient was actually lower, $56,800 for those younger infants versus $76,700 for all others.
Additionally, mortality was more than 75 percent less, and related disorders of prematurity were dramatically lower. Incidents of necrotizing enterocolitis, a rare but devastating intestinal disease among premature babies, were 91 percent lower, while cases of sepsis, a life-threatening bloodstream infection, were nearly 97 percent fewer.
Incidents of intraventricular hemorrhage, or bleeding inside the brain, were 59 percent lower, hinting at even greater lifetime cost savings for this patient population based on the known long-term neurodevelopmental impacts of even low-grade IVH, the researchers said.
"The findings suggest that being single-mindedly focused on this one measure (average length of stay), executives might actually be missing the boat in reducing costs and improving outcomes," said study co-lead author David Tanaka, MD, a neonatologist at Duke Children's Hospital, in a statement. "It's more critically important to focus on quality outcomes -- not just because it's the right thing to do, but also because this is tangible evidence to the CFO that it's financially the right thing to do."
Tanaka, the impetus behind Duke's NICU event simulation model's development, first approached analytics firm SAS about his interest in simulation modeling in 2012. SAS' Emily Lada, a principal operations research specialist, later built the model free of charge as part of a research project; the model was validated earlier this year in a study published by the Health Informatics Journal. That study used the simulation tool to predict and plan for NICU staffing needs.
For the current study, researchers replaced the model's standard probability distributions with composite distributions representing the best and worst neonatal outcomes published by the Neonatal Research Unit.
The result, according to researchers, is a fast, effective and non-intrusive means to perform "what-if" experiments without disrupting their real-world systems.