Using Data Analytics to Optimize ED Staffing

Project reduces percent of patients who leave without being seen

Data analysis for nursing workflows

Emergency department (ED) patients who leave without being seen (LWBS) put their health at risk and affect a hospital’s reputation. LWBS also can have financial and legal consequences and result in poor patient experience. The national LWBS average stands at 2%, according to a 2021 article in the Western Journal of Emergency Medicine.

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 In 2019, a team of nurses at Cleveland Clinic Medina Hospital embarked on a project to reduce incidence of LWBS and ensure staff productivity using predictive analytics.

“We pulled data on when the ED was busiest and how many patients were leaving without being seen during those times,” says Danielle Razavi, MSN, RN, Assistant Nurse Manager of the ED during the project. “That helped us make decisions on staffing and where we could flex or add shifts without exceeding our budget.”

Shifting staff assignments

At the start of the project, Razavi and the ED nurse manager requested two years of data from the hospital’s business analytics team on patient arrivals by hour and day of the week, as well as percentage of LWBS with patient arrivals. They noticed that the ED’s busiest days were Mondays and Tuesdays and busiest times were from the middle of the day until late afternoon on all days.

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The nurse manager presented the information to the Shared Governance Committee for input and to help create a plan to optimize staffing and drive ED productivity. The plan included three primary components:

  • Shift RN staff from Saturday to Tuesday. The two-year trend indicated that Saturdays tend to be slow and have a low census in the ED. The team closed four of its 19 rooms on Saturday, which allowed them to remove one nurse from the schedule and add a nurse on Tuesdays.
  • Assign ancillary staff in triage. Previously, one paramedic began working in the ED at 7 a.m. and one at 11 a.m., both helping out with the most serious cases. However, there was overlap in the afternoons. Now, one of the paramedics works triage beginning at 11 a.m., which helps decrease patient wait times and bottlenecks.
  • Move a free-charge RN from Tuesday to secondary triage on Monday. Formerly, staffing included a free-charge nurse who did not have patient assignments, but managed the floor, assisted with discharges and supported other nurses as needed. Rather than assign a free-charge nurse on Tuesdays, that position moved to an 11 a.m. to 11 p.m. triage shift on Mondays.

Patient LWBS declines

Each of the interventions has contributed to a progressive reduction in LWBS. When one RN position moved from Saturday to Tuesday, LWBS decreased from 1.42% to .97%. After assigning paramedics to triage, LWBS decreased to .56%, and when a secondary triage nurse was added on Mondays it decreased to .42%.

Overall, the hospital’s ED experienced a 70% reduction in LWBS from baseline after completing its predictive analytics project. The staffing changes not only made the ED more productive, but also adhered to the existing budget.

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“As the saying goes, numbers don’t lie,” says Razavi, who now serves as Nurse Manager in the hospital’s ICU. “Once you take a look at data and trends, don’t be afraid to make changes.”