Impact of outlier status on critical care patient outcomes: Does boarding medical intensive care unit patients make a difference?

Ahmad, Danish; Moeller, Katherine; Chowdhury, Jared; Yoo, Erika J.

doi:10.1016/j.jcrc.2017.10.004

Cited by 4 publications

(2 citation statements)

References 40 publications

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“…Other studies investigating the safety of overflow have found possible harm boarding surgical patients in non-surgical ICUs,(33) though not seen in a medical ICU patient population. (34) While our findings are limited due to the low subgroup numbers, it may be that these patients also are receiving the same quality and level of care that they would experience in a Medical ICU. This illustrates a potential opportunity to have improved coordination and collaboration between ICUs to facilitate overflow to offload the ED during times of MICU capacity strain, without compromising quality of care.…”

Section: Discussionmentioning

confidence: 88%

Effect of Emergency Department and ICU Occupancy on Admission Decisions and Outcomes for Critically Ill Patients*

Mathews

Durst

Vargas-Torres

et al. 2018

Critical Care Medicine

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Section: Discussionmentioning

confidence: 88%

Effect of Emergency Department and ICU Occupancy on Admission Decisions and Outcomes for Critically Ill Patients*

Mathews

Durst

Vargas-Torres

et al. 2018

Critical Care Medicine

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“…One study found that boarding duration did not affect LOS or mortality in stroke patients (Al-Khathaami et al, 2014). Another study showed that in the ICU, boarding in units other than the one to which the patient was assigned was not associated with increased mortality or LOS (Ahmad et al, 2018), suggesting that placement of a patient's bed relative to the location of their primary care team is not significant.…”

Section: Effects Of Ed Congestionmentioning

confidence: 99%

Thematic Issues in Analysis and Visualization of Emergency Department Patient Flow

Bauchwitz

Lynn

Weyhrauch

et al. 2018

Proceedings of the International Symposium on Human Factors and

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Emergency Department (ED) congestion is a significant problem affecting clinical outcomes, patient satisfaction and hospital costs. Identifying and resolving bottlenecks in the flow of patients from the ED to eventual admission or discharge has the potential to reduce wait times, improve care for individual patients, and increase the volume of patients treated at the hospital over time. Our objective was to review methods commonly used to measure, analyze, and visualize patient flow, characterize drawbacks to these methods, and identify areas in which analysis and visualization can be improved to make bottlenecks easier to identify and resolve. Sixty-five articles obtained from PubMed and Google Scholar searches were reviewed to identify: (1) variables used to measure ED throughput; (2) downstream effects of ED congestion; (3) factors contributing to ED congestion; (4) techniques used to predict or respond to ED congestion; and (5) tools used to visualize data on ED throughput. Hospital resource availability, patient demographics, and environmental factors have all been used to predict contributors to ED congestion. Unfortunately, the hospital practices most critical to ED congestion are unlikely to change as they involve increasing the number of beds and providers or modifying protocols with EMS, insurance, and other care facilities. Therefore, interventions addressing optimization of ED resource allocation and visualization of ED data are the best avenue to yield more efficient ED operation.

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Capacity Pooling in Hospitals: The Hidden Consequences of Off-Service Placement

et al. 2020

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Hospital managers struggle with the day-to-day variability in patient admissions to different clinical services, each of which typically has a fixed allocation of hospital beds. In response, many hospitals engage in capacity pooling by assigning patients from a service whose designated beds are fully occupied to an available bed in a unit designated for a different service. This “off-service placement” occurs frequently, yet its impact on patient and operational measures has not been rigorously quantified. This is, in part, because of the challenge of properly accounting for the endogenous selection of off-service patients. We use an instrumental variable approach to quantify the causal effects of off-service placement of hospitalized medical/surgical patients, having accounted for the endogeneity issues. Using data from a large academic medical center with 19.6% of medical/surgical patients placed off service on average, we find that off-service placement is associated with a 22.8% increase in remaining hospital length of stay (LOS) and a 13.1% increase in the likelihood of hospital readmission within 30 days. We find no significant effect on in-hospital mortality or clinical trigger (rapid response) activation. We identify longer distances to the service’s home unit as a key mechanism that drives the effect on LOS. In contrast, a mismatch in nursing specialization does not seem to explain this effect. By quantifying the effects of off-service placement on patient and operational outcomes, we enable clinicians and hospital managers to make better-informed short-term decisions about off-service placement and longer-term decisions about capacity allocation. This paper was accepted by Stefan Scholtes, healthcare management.

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Impact of outlier status on critical care patient outcomes: Does boarding medical intensive care unit patients make a difference?

Cited by 4 publications

References 40 publications

Effect of Emergency Department and ICU Occupancy on Admission Decisions and Outcomes for Critically Ill Patients*

Effect of Emergency Department and ICU Occupancy on Admission Decisions and Outcomes for Critically Ill Patients*

Thematic Issues in Analysis and Visualization of Emergency Department Patient Flow

Capacity Pooling in Hospitals: The Hidden Consequences of Off-Service Placement

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