Association between timing of intensive care unit admission and outcomes for emergency department patients with community-acquired pneumonia*

Renaud, Bertrand; Santin, A.; Coma, Eva; Camus, Nicolas; Pelt, Dave Van; Hayon, Jan; Gurguí, Mercé; Roupie, É.; Hervé, Jérôme; Fine, Michael J.; Brun‐Buisson, Christian; Labarère, José

doi:10.1097/ccm.0b013e3181b02dbb

Cited by 132 publications

(110 citation statements)

References 34 publications

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“…As described in Section 3.2, we can relate this delay-growth function directly to our empirical study by appropriately defining N * . This bears similarities to some of the medical literature which examines the increase in workload of delayed versus not delayed patients (Chalfin et al 2007, Renaud et al 2009). Moreover, we consider the case where the service times are exponentially distributed.…”

Section: An Upperbound For a Step Functionsupporting

confidence: 62%

“…As we show at a granular level in this paper, this is not a tenable assumption. In addition, there have been various condition specific studies in the medical community demonstrating that delays can result in an increase in mortality (de Luca et al 2004, Chan et al 2008, Buist et al 2002, Yankovic et al 2010) and/or extend patient Length-of-stay (LOS) (Chalfin et al 2007, Renaud et al 2009, Rivers et al 2001). …”

Section: Standard Queueing Models Fall Shortmentioning

confidence: 99%

“…The definition of delay varies across different medical conditions and scenarios. Renaud et al (2009) compares the outcomes of pneumonia patients who are transferred to the ICU within 1 day (non-delayed) versus 3 days (delayed) of presenting symptoms. They find that the median hospital LOS and 28-day mortality rate is nearly twice as high for delayed patients.…”

Section: Related Literaturementioning

confidence: 99%

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The Impact of Delays on Service Times in the Intensive Care Unit

Chan¹,

Farias

Escobar

2017

Management Science

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Mainstream queueing models are frequently employed in modeling healthcare delivery in a number of settings, and further used in making operational decisions for the same. The vast majority of these queueing models assume that the service requirements of a job are independent of the state of the queue upon its arrival. In a healthcare setting, this assumption is equivalent to ignoring the effects of delay experienced by a patient awaiting care. However, it is only natural to conjecture that 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. At a very coarse level, prior research confirms these natural conjectures. This work sets out to understand these delay issues from an operational perspective. In particular, using data of nearly 6,000 Emergency Department (ED) visits, we use an instrumental variable approach to empirically measure how congestion in the Intensive Care Unit (ICU) can lead to delays in boarding from the ED to the ICU and measure the impact on the patient's ICU LOS.Capturing these empirically observed effects in a queueing model is challenging as the effect introduces potentially long range correlations in service and inter-arrival times. As such, we consider the problem of how to incorporate these measured delay effects into a queueing model and characterize approximations to various quantities of interest when the service time of a job is adversely impacted by the delay experienced by that job. Our findings suggest that this delay effect can be substantial and ignoring it when using queueing models to model healthcare delivery systems may result in significant under-provisioning.

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Section: An Upperbound For a Step Functionsupporting

confidence: 62%

Section: Standard Queueing Models Fall Shortmentioning

confidence: 99%

Section: Related Literaturementioning

confidence: 99%

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The Impact of Delays on Service Times in the Intensive Care Unit

Chan¹,

Farias

Escobar

2017

Management Science

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“…[21][22][23] At many hospitals, critical care beds are a scarce resource such that most hospitals have a policy for the ''triage'' of patients to critical care beds. 24, 25 Lundberg and colleagues' study demonstrated that patients who developed septic shock on the medical wards experienced delays in receipt of intravenous fluids, inotropic agents and transfer to a critical care setting.…”

Section: Discussionmentioning

confidence: 99%

Does sepsis treatment differ between primary and overflow intensive care units?

Vishnupriya

Falade

Workneh

et al. 2012

Journal of Hospital Medicine

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BACKGROUND:Sepsis is a major cause of death in hospitalized patients. Early goal‐directed therapy is the standard of care. When primary intensive care units (ICUs) are full, sepsis patients are cared for in overflow ICUs.OBJECTIVE:To determine if process‐of‐care measures in the care of sepsis patients differed between primary and overflow ICUs at our institution.DESIGN:We conducted a retrospective study of all adult patients admitted with sepsis between July 2009 and February 2010 to either the primary ICU or the overflow ICU.MEASUREMENTS:Baseline patient characteristics and multiple process‐of‐care measures, including diagnostic and therapeutic interventions.RESULTS:There were 141 patients admitted with sepsis to our hospital; 100 were cared for in the primary ICU and 41 in the overflow ICU. Baseline acute physiology and chronic health evaluation (APACHE II) scores were similar. Patients received similar processes‐of‐care in the primary ICU and overflow ICU with the exception of deep vein thrombosis (DVT) and gastrointestinal (GI) prophylaxis within 24 hours of admission, which were better adhered to in the primary ICU (74% vs 49%, P = 0.004, and 68% vs 44%, P = 0.012, respectively). There were no significant differences in hospital and ICU length of stay between the 2 units (9.68 days vs 9.73 days, P = 0.98, and 4.78 days vs 4.92 days, P = 0.97, respectively).CONCLUSIONS:Patients with sepsis admitted to the primary ICU and overflow ICU at our institution were managed similarly. Overflowing sepsis patients to non‐primary intensive care units may not affect guideline‐concordant care delivery or length of stay. Journal of Hospital Medicine 2012; © 2012 Society of Hospital Medicine

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“…For example, when the medical ICU is full, the odds of cardiac arrest outside the ICU nearly double [5]. Delays in moving patients to the ICU from the emergency room [6,7] and from the floor [8][9][10][11][12][13] have demonstrated harm to patients. Gillies' work extends this to the perioperative space.…”

mentioning

confidence: 99%