The high cost of low-acuity ICU outliers

Deborah Dahl1, Greg G Wojtal, Michael J Breslow

  • 1Banner Health, Phoenix, USA. deb.dahl@bannerhealth.com

Insights

High-acuity patients drive intensive care unit (ICU) costs, but low-risk patients who stay longer incur disproportionately high costs and mortality. Identifying and managing these outliers is key to improving patient outcomes and reducing healthcare expenses.

Area of Science:

  • Health Economics
  • Critical Care Medicine
  • Healthcare Management

Background:

  • Direct variable costs in intensive care units (ICUs) significantly impact overall hospital expenditures.
  • Understanding cost drivers and length of stay (LOS) is crucial for optimizing ICU resource allocation.

Purpose of the Study:

  • To analyze the direct variable costs and length of stay (LOS) for patients in four Phoenix-area hospital ICUs.
  • To identify patient factors, including acuity and risk level, associated with prolonged ICU stays and high costs.

Main Methods:

  • Direct variable costs were calculated daily for all ICU patients.
  • Patient acuity was assessed using the APACHE risk prediction methodology.
  • Length of stay (LOS) outliers were defined as patients with ICU stays exceeding six days.

Main Results:

  • Average daily ICU costs ranged from $1,436 to $1,759.
  • Patients with higher acuity and longer LOS incurred higher daily costs.
  • A significant portion of ICU costs (56.7%) were attributed to LOS outliers (16.2% of patients).
  • Low-risk patients who became LOS outliers (11.1% of low-risk group) accounted for 25.3% of ICU costs and had fivefold higher costs and mortality.

Conclusions:

  • Severity of illness is a key determinant of ICU resource consumption and LOS.
  • A substantial number of long-stay ICU patients are initially low-risk, indicating a critical, under-recognized issue.
  • Focusing on low-risk LOS outliers presents an opportunity to improve patient outcomes and reduce healthcare costs.

Related Concept Videos

What Are Outliers?01:12

What Are Outliers?

Outliers are observed data points that are far from the least squares line. They have unusual values and need to be examined carefully. Though an outlier may result from erroneous data, at other times, it may hold valuable information about the population under study and should be included in the data. Hence, it is crucial to examine what causes a data point to be an outlier.
The z score is used to find outliers or unusual values. It should be noted that any values beyond -2 and +2 are...
Outliers and Influential Points01:08

Outliers and Influential Points

An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500), while others may indicate that something unusual is happening. Outliers are present far from the least squares line in the vertical direction. They have large "errors," where the "error" or residual is the vertical...
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
Healthcare Associated Infections II: Preventive Measures01:22

Healthcare Associated Infections II: Preventive Measures

Essential infection prevention measures are based on the knowledge of the infection chain, the modes of transmission in healthcare settings, and the use of the best practices in all healthcare settings. Compulsory public reporting of healthcare-associated infection rates is needed to allow individuals and the community to make informed choices regarding selecting a healthcare facility.
The best practices for preventing healthcare-associated infections include hand hygiene, patient risk...
Healthcare Associated Infections I: Iatrogenic, Exogenic and Endogenic01:26

Healthcare Associated Infections I: Iatrogenic, Exogenic and Endogenic

Healthcare-associated infections (HAIs) occur in a healthcare facility while a person receives care for another ailment. This category also includes work-related infections among healthcare staff.
HAIs significantly increase the cost of health care. Extended stays in healthcare institutions, increased disability, increased costs of medications, including specialized antibiotics, and prolonged recovery times add to the patient's expenses and the healthcare institution and funding bodies. Common...