A new study led by Duke University Health System and SAS, a Cary. N.C.-based analytics vendor, has found that for newborns in the neonatal intensive care unit (NICU), longer hospital length of stays are correlated with lower costs and more positive outcomes.
The common belief regarding healthcare spending and health outcomes in the U.S. has been that shorter hospital stays equate to cost savings. But for this study, just published in the Journal of Perinatology, researchers 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 (NRN). “Using this model, we debunked what has been a pervasive tenet in healthcare—the belief that if you relentlessly drive down length of stay, you will universally decrease costs,” said one of the study’s lead authors, Chris DeRienzo, M.D., a neonatologist and chief quality officer at Mission Health System, in Asheville, N.C.
“Our evidence shows that’s just not true,” he added. “We found 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. However, comparable annual costs are actually $3 million less.”
David Tanaka, M.D., a neonatologist at Duke Children’s Hospital, and study co-lead author, first approached SAS about his interest in simulation modeling in 2012. SAS’ Emily Lada, a principal operations research specialist, later built the model as part of a research project using SAS Simulation Studio 14.1. 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 NRN.
Discrete event simulation modeling with advanced analytics aims to give organizations a fast, effective and non-intrusive means to perform “what-if” experiments without disrupting their real-world systems, according to SAS officials. Workflow-oriented industries like manufacturing, retail and finance have used discrete event modeling for decades to gauge how different scenarios might affect business operations. Now, a growing number of health systems are adopting the technology, which DeRienzo called “the Rosetta stone” for performance and quality improvement in healthcare settings.
“I think healthcare in 10 years will necessarily look very different from healthcare now, and we’re right in the middle of that transition,” said DeRienzo. “This project is just one example of how we can use innovative analytics tools to improve not only the ways we provide care but the actual care we provide. Analytics has a tremendous role to play in facilitating that transformation—not just in the NICU but across the clinical spectrum.”
Key findings of this study show that, in the composite best virtual NICU:
- Overall average length of stay (ALOS) was three days longer (27 days versus 24 days). ALOS was 20 days longer (86 days versus 66 days) for infants of 28 weeks or less gestational age.
- Average cost per patient was actually lower ($16,400 versus $19,700 overall and $56,800 versus $76,700 for infants of 28 weeks or less gestational age).
- Mortality was more than 75 percent less.
- Related disorders of prematurity were dramatically lower:
- Incidence of necrotizing enterocolitis (a rare but devastating intestinal disease among premature babies) were 91 percent lower.
- Cases of sepsis (a life-threatening bloodstream infection) were nearly 97 percent fewer.
- Incidence of intraventricular hemorrhage (a bleed inside the brain) were 59 percent lower, hinting at even greater lifetime cost savings for this patient population based on known long-term neurodevelopmental impacts of even low-grade IVH.
“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 Tanaka. “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.”
Duke’s current NICU simulation tool requires a data scientist to run the models. However, a general user interface currently under development at SAS will make the tool independently accessible to everyday users like medical directors, nurse managers, and hospital administrators. Future iterations of the study’s discrete event simulation model will also be applicable to any NICU in the U.S., officials said.