The Hidden Cost of Hemolyzed Blood Samples in the Emergency Department

Michael P Phelan1, Christopher Ramos2, Laura E Walker3

  • 1Emergency Services Institute, Cleveland Clinic Health System, Cleveland, OH, USA.

Insights

Poor-quality blood samples in the emergency department (ED) lead to significant costs. Hemolyzed potassium samples increase patient length of stay by 1 hour, costing millions annually.

Area of Science:

  • Clinical Chemistry
  • Healthcare Economics
  • Laboratory Quality Management

Background:

  • Poor-quality preanalytic blood samples, specifically hemolyzed potassium samples, are a common issue in emergency departments (EDs).
  • These suboptimal samples can lead to extended patient stays, irrespective of clinical severity or disposition.
  • Quantifying the direct financial impact of these preanalytic errors is crucial for healthcare cost analysis.

Purpose of the Study:

  • To quantify the direct financial expenses associated with poor-quality preanalytic blood samples collected in the ED.
  • To estimate the cost impact of hemolyzed samples on healthcare resource utilization.

Main Methods:

  • Developed a cost model using a range of direct expenses per bed-hour, informed by literature and inflation-adjusted values.
  • Incorporated a range of hemolysis incidence rates based on previously reported data.
  • Calculated the estimated annual cost impact for an ED with a specified number of annual visits and routine chemistry draw rates.

Main Results:

  • An ED with 100,000 annual visits, a 40% routine chemistry draw rate, and a 10% hemolysis incidence experiences direct costs of approximately $4 million per year.
  • This significant cost is primarily driven by an average 1-hour increase in length of stay for patients with hemolyzed blood samples.
  • The findings highlight the substantial financial burden of avoidable extended ED stays due to sample quality issues.

Conclusions:

  • The financial burden of poor-quality blood samples can be effectively estimated using cost per bed-hour and sample failure rates.
  • This methodology can be applied to identify and quantify the financial implications of other quality control issues in laboratory diagnostics.
  • Addressing preanalytic sample quality is essential for optimizing healthcare costs and improving patient flow in the ED.
Abstract