Healthcare

In hospitals, Step Down Units (SDUs) provide an intermediate level of care between the Intensive Care Units (ICUs) and the general medical-surgical wards. Because SDUs are less richly staffed than ICUs, they are less costly to operate; however, they also are unable to provide the level of care required by the sickest patients. There is an ongoing debate in the medical community as to whether and how SDUs should be used. On one hand, an SDU alleviates ICU congestion by providing a safe environment for post-ICU patients before they are stable enough to be transferred to the general wards.

In order for a patient to be discharged from a hospital unit, a physician must first perform a physical examination and review the pertinent medical information to determine that the patient is stable enough to be transferred to a lower level of care or be discharged home. Requiring an inspection of a patient's "readiness for discharge" introduces an interesting dynamic where patients may occupy a bed longer than medically necessary.

Rationale

Hospitals are increasingly using critical care outreach teams (CCOTs) to respond to patients deteriorating outside intensive care units (ICUs). CCOT staffing is variable across hospitals and optimal team composition is unknown.

Objectives

To assess whether adding a critical care medicine trained physician assistant (CCM-PA) to a critical care outreach team (CCOT) impacts clinical and process outcomes.

Methods

Mainstream queueing models are frequently employed in modeling healthcare delivery in a number of settings, and further are used in making operational decisions for the same. The vast majority of these queueing models ignore the effects of delay experienced by a patient awaiting care. However, long delays may have adverse effects on patient outcomes and can potentially lead to longer lengths of stay (LOS) when the patient ultimately does receive care. This work sets out to understand these delay issues from an operational perspective.

We consider a system of parallel queues where arriving service tasks are buffered, according to type. Available service resources are dynamically configured and allocated to the queues to process the tasks. At each point in time, a scheduler chooses a service configuration across the queues, in response to queue backlogs. Switching from one service configuration to another incurs a setup time, during which idling occurs and service bandwidth is lost. Such setup times are inherent in manufacturing and computer systems.

Objectives: To employ automated bed data to examine whether ICU occupancy influences ICU admission decisions and patient outcomes.

Design: Retrospective study using an instrumental variable to remove biases from unobserved differences in illness severity for patients admitted to ICU.

Setting: Fifteen hospitals in an integrated healthcare delivery system in California.

Patients: Seventy thousand one hundred thirty-three episodes involving patients admitted via emergency departments to a medical service over a 1-year period between 2008 and 2009.

In hospitals, Step Down Units (SDUs) provide an intermediate level of care between the Intensive Care Units (ICUs) and the general medical-surgical wards. Because SDUs are less richly staffed than ICUs, they are less costly to operate; however, they also are unable to provide the level of care required by the sickest patients. There is an ongoing debate in the medical community as to whether and how SDUs should be used. On one hand, an SDU alleviates ICU congestion by providing a safe environment for post-ICU patients before they are stable enough to be transferred to the general wards.

This paper examines the role of a hospital Step-Down Unit (SDU) on patient flows and patient outcomes. An SDU provides an intermediate level of care for semi-critically ill patients who are not sick enough to require intensive care but not stable enough to be treated in the general medical/surgical ward (ward). Using data from 10 hospitals from a single hospital network, we use an instrumental variable approach to estimate the impact on patient outcomes of routing patients to the SDU following Intensive Care Unit (ICU) discharge.