Frequent utilization of the emergency department (ED) for non-emergent care remains a chronic challenge for health plans looking to improve costs and quality. Studies show that as much as 5% of the overall patient population seen in the ED accounts for as much as 18% of all annual ED visits. In addition, nearly 20% of ED complaints stem from mood disorders, and another 10% relate to alcohol use.
As retail clinics and urgent care centers grow in number, patients have many more opportunities to avoid emergency department visits than ever before. To assess and attempt to curb avoidable ED usage, health plans must first identify emergent and non-emergent ED use among the members they serve. Data analytics and predictive analysis play a key role in this endeavor.
We recently spoke with Chris Young, senior product manager at MedeAnalytics, who commented on the opportunity to limit avoidable ED visits: “Emergency room visits make up a significant portion of the rising costs of healthcare,” he said. “It’s a universal problem plaguing the industry. But by analyzing ED utilization with our platform, health plans can identify and categorize ED use to determine if ED visits among their members are potentially avoidable. With that information, payers can develop outreach plans to educate members and influence their usage of the ED.”
By analyzing their data, health plans can work to understand the causes that drive their members to the ED. While uncertainty and variation in acuity can make ED use difficult to analyze, health plans can use the right algorithms and predictive analysis to better understand their members and gain holistic insight into emergency department costs and utilization.
For example, they can use analytics to identify the primary drivers of ED utilization and drill down into the data to identify which visits are potentially non-emergent, which are treatable by primary care, and which are preventable or avoidable. By identifying the most common related diagnoses, associated providers, and individual members, the health plan can take meaningful action.
In one instance, an accountable care organization (ACO) ran a utilization report using MedeAnalytics Healthcare Economics. It revealed high ED utilization and its associated high costs of care. A closer look at the data uncovered a pattern of high utilization of a pediatric emergency room within a concentrated geographic area. With additional investigation, the ACO determined the root causes of this high utilization which stemmed from limited pediatrician office hours and a lack of urgent care facilities that treat children. The ACO worked with local pediatricians and urgent care centers to expand treatment hours and services—ultimately reducing non-emergent ED visits and associated costs.
“With its data in hand, this ACO was able to take meaningful action to decrease ED utilization,” said Young. “Without such data, efforts to reduce avoidable ED use are often guided by guesswork and don’t produce measurable results.”
Learn more about how our Healthcare Economics analytics can help your organization address avoidable ED visits, or contact us to schedule a demo.
Sources:
“Reducing Frequent Visits to the Emergency Department: A Systematic Review of Interventions,” NCBI, April 13, 2015.
“Avoidable Emergency Department Visits: A Starting Point,” International Journal for Quality in Health Care, October 2017.
Get our take on industry trends
4 tactics to harness data analytics for patient access engagement and efficiency
As healthcare consumers and regulatory bodies push for more transparency in medical services and transactions, provider organizations are applying greater…
Read on...Proactively predicting ER visit trends with augmented analytics to improve revenues, asset utilization and patient outcomes
Mission critical emergency departments (EDs) are the most valuable revenue generating asset for hospitals. While visits decreased during the pandemic,…
Read on...Best practice tools to build an integrated approach to multimorbidity
The traditional model of treating single diseases no longer works. Data collected from 2016 to 2019 indicated that 32.9% of…
Read on...