ICU Admission Control: An Empirical Study of Capacity Allocation and Its Implication on Patient Outcomes

Kim, Song Hee; Chan, Carri W.; Olivares, Marcelo; Escobar, Gabriel J.

doi:10.2139/ssrn.2062518

Cited by 34 publications

(56 citation statements)

References 70 publications

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“…It was necessary to assemble a multihospital department-based data set for our analysis. There are, however, other less severe but more frequent indicators of quality deterioration, such as readmission to the hospital, operating theater or intensive care, patient falls, medication errors, and patient complaints, which are routinely collected by hospitals (KC and Terwiesch 2012, Kim et al 2013, Long and Mathews 2013. Although they are rarely associated with patient deaths, these events are indicative of poor clinical quality and are likely to be affected by occupancy levels.…”

Section: Resultsmentioning

confidence: 99%

“…consequences for clinical quality and therefore recommend also investigating effects on clinical outcomes such as mortality rates Terwiesch 2009, 2012;Long and Mathews 2013;Berry Jaeker and Tucker 2012;Kim et al 2013). KC and Terwiesch (2009), for example, complemented a throughput analysis of a sample of cardiothoracic patient records from a U.S. hospital with a study on the effect of workload on mortality.…”

Section: Related Literaturementioning

confidence: 99%

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Stress on the Ward: Evidence of Safety Tipping Points in Hospitals

2015

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D o hospitals experience safety tipping points as utilization increases, and if so, what are the implications for hospital operations management? We argue that safety tipping points occur when managerial escalation policies are exhausted and workload variability buffers are depleted. Front-line clinical staff is forced to ration resources and, at the same time, becomes more error prone as a result of elevated stress hormone levels. We confirm the existence of safety tipping points for in-hospital mortality using the discharge records of 82,280 patients across six high-mortality-risk conditions from 256 clinical departments of 83 German hospitals. Focusing on survival during the first seven days following admission, we estimate a mortality tipping point at an occupancy level of 92.5%. Among the 17% of patients in our sample who experienced occupancy above the tipping point during the first seven days of their hospital stay, high occupancy accounted for one in seven deaths. The existence of a safety tipping point has important implications for hospital management. First, flexible capacity expansion is more cost-effective for safety improvement than rigid capacity, because it will only be used when occupancy reaches the tipping point. In the context of our sample, flexible staffing saves more than 40% of the cost of a fully staffed capacity expansion, while achieving the same reduction in mortality. Second, reducing the variability of demand by pooling capacity in hospital clusters can greatly increase safety in a hospital system, because it reduces the likelihood that a patient will experience occupancy levels beyond the tipping point. Pooling the capacity of nearby hospitals in our sample reduces the number of deaths due to high occupancy by 34%.

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Section: Resultsmentioning

confidence: 99%

Section: Related Literaturementioning

confidence: 99%

Stress on the Ward: Evidence of Safety Tipping Points in Hospitals

2015

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“…Due to the fact that ICU is the best place for critically ill patients [4] to receive early interventions, many policies have been suggested to increase ICU bed availability [5,7,26]. Most common policies, starting from the three policies within the scope of this study that a single hospital can implement on short notice without incurring high costs, include:…”

Section: Icu Management Policiesmentioning

confidence: 99%

“…Early transfer out of ICU is responsible for 22 to 42 % of ICU readmissions [28] and 39 % of discharge mortality [34]. 2 Boarding in Ward (ICU Admission Control): Under this policy, when ICU is full, critical patients waiting for ICU admission are admitted to the general ward instead [4,14,26]. It has been shown that admitted critical patients in ICU have better outcomes compared to those admitted to wards [14].…”

Section: Icu Management Policiesmentioning

confidence: 99%

“…Daly et al (2001) concluded that to avoid post-ICU death caused by inappropriate discharge, a 16 % increase in the number of ICU beds in UK is necessary [34]. Yet, Kim et al (2014) estimated that adding each bed to ICU costs $0.8 million per year [26]. It has been mentioned that investments in ICU beds also resulted in higher fixed costs, excess capacity, and long-term inefficiencies [37].…”

Section: Icu Management Policiesmentioning

confidence: 99%

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Sustaining critical care: using evidence-based simulation to evaluate ICU management policies

Mahmoudian-Dehkordi

Sadat

2016

Health Care Manag Sci

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Intensive Care Units (ICU) are costly yet critical hospital departments that should be available to care for patients needing highly specialized critical care. Shortage of ICU beds in many regions of the world and the constant fire-fighting to make these beds available through various ICU management policies motivated this study. The paper discusses the application of a generic system dynamics model of emergency patient flow in a typical hospital, populated with empirical evidence found in the medical and hospital administration literature, to explore the dynamics of intended and unintended consequences of such ICU management policies under a natural disaster crisis scenario. ICU management policies that can be implemented by a single hospital on short notice, namely premature transfer from ICU, boarding in ward, and general ward admission control, along with their possible combinations, are modeled and their impact on managerial and health outcome measures are investigated. The main insight out of the study is that the general ward admission control policy outperforms the rest of ICU management policies under such crisis scenarios with regards to reducing total mortality, which is counter intuitive for hospital administrators as this policy is not very effective at alleviating the symptoms of the problem, namely high ED and ICU occupancy rates that are closely monitored by hospital management particularly in times of crisis. A multivariate sensitivity analysis on parameters with diverse range of values in the literature found the superiority of the general ward admission control to hold true in every scenario.

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Work after work: The impact of new service delivery models on work hours

Bavafa

Terwiesch

2019

J of Ops Management

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In many professional service organizations (PSOs), a single server such as a physician or lawyer delivers services to customers across multiple channels. In these settings, there exists a risk that work obligations encroach on the personal lives of the servers. We empirically examine this concern in the primary care setting of physicians providing care to patients following the introduction of a new service delivery channel, e‐visits. Our data cover an 8.5‐year timespan and include 3.3 million patient encounters, including about one million e‐visits. We find that e‐visit adoption nearly doubles the number of hours containing work (defined as office visits or e‐visits) each week. Of the additional hours containing such work, only 49% are in weekday business hours; the rest are in weekday evenings or early mornings (37%) and on weekends (14%). We also show that increases in office or e‐visit workloads lead to more post‐workday activity in the e‐visit channel. We conclude the analysis by examining the impact of these workloads on e‐visit work content, as measured by the number of words and amount of time spent on each e‐visit; we estimate precise but practically small effects of workload on these work content outcomes.

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ICU Admission Control: An Empirical Study of Capacity Allocation and Its Implication on Patient Outcomes

Cited by 34 publications

References 70 publications

Stress on the Ward: Evidence of Safety Tipping Points in Hospitals

Stress on the Ward: Evidence of Safety Tipping Points in Hospitals

Sustaining critical care: using evidence-based simulation to evaluate ICU management policies

Work after work: The impact of new service delivery models on work hours

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