Scarcity in the intensive care unit: Principles of justice for rationing ICU beds

Swenson, Michael

doi:10.1016/0002-9343(92)90753-x

Cited by 37 publications

(18 citation statements)

References 24 publications

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“…Our …ndings on the reduction in available capacity due to revisits could have implications for the implementation of rapid response teams. Finally, a related stream of literature examines the identi…cation of low-severity patients for early discharge from the ICU (see Martin et al 2005 andSwenson 1992). Our analysis shows that low severity patients di¤er from high severity patients in their implications for the likelihood of bounce-back, and usage of capacity.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Future medical research is needed to build more sophisticated models of patient recovery that enable the hospital to customize the discharge decision to the medical pro…le of a patient while considering ICU occupancy (e.g. see Martin et al 2005 andSwenson 1992). In particular, various dimensions of patient recovery and quality of care both inside the ICU and after discharge need to be examined.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

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An Econometric Analysis of Patient Flows in the Cardiac Intensive Care Unit

Terwiesch

2012

M&SOM

204

135

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This paper explores the rationing of bed capacity in a cardiac intensive care unit (ICU). We find that the length of stay for patients admitted to the ICU is influenced by the occupancy level of the ICU. In particular, a patient is likely to be discharged early when the occupancy in the ICU is high. This in turn leads to an increased likelihood of the patient having to be readmitted to the ICU at a later time. Such "bounce-backs" have implications for the overall ICU effective capacity-an early discharge immediately frees up capacity, but at the risk of a (potentially much higher) capacity requirement when the patient needs to be readmitted. We analyze these capacity implications, shedding light on the question of whether an ICU should apply an aggressive discharge strategy or if it should follow the old quality slogan and "do it right the first time. " By comparing the total capacity usage for patients who were discharged early versus those who were not, we show that an aggressive discharge policy applied to patients with lower clinical severity levels frees up capacity in the ICU. However, we find that an increased number of readmissions of patients with high clinical severity levels occur when the ICU is capacity constrained, thereby effectively reducing peak bed capacity. Christian TerwieschThe Wharton School, University of Pennsylvania terwiesch@wharton.upenn.eduThis paper explores the rationing of bed capacity in a cardiac intensive care unit (ICU). We …nd that the length of stay for patients admitted to the ICU is in ‡uenced by the occupancy level of the ICU. In particular, a patient is likely to be discharged early when the occupancy in the ICU is high. This in turn leads to an increased likelihood of the patient having to be readmitted to the ICU at a later time. Such "bounce-backs" have implications for the overall ICU e¤ective capacity -an early discharge immediately frees up capacity, but at the risk of a (potentially much higher) capacity requirement when the patient needs to be readmitted. We analyze these capacity implications, shedding light on the question if an ICU should apply an aggressive discharge strategy or if it should follow the old quality slogan and "do it right the …rst time." By comparing the total capacity usage for patients who were discharged early versus those who were not, we show that an aggressive discharge policy applied to patients with lower clinical severity levels frees up capacity in the ICU. However, we …nd that an increased number of readmissions of patients with high clinical severity levels occur when the ICU is capacity constrained, thereby e¤ectively reducing peak bed capacity.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Conclusion and Future Researchmentioning

confidence: 99%

An Econometric Analysis of Patient Flows in the Cardiac Intensive Care Unit

Terwiesch

2012

M&SOM

204

135

View full text Add to dashboard Cite

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“…If there are not enough beds available, space must be allocated by transferring current patients to units with lower levels of staffing and care. In Swenson (1992) and related works, the authors examine how to allocate ICU beds from a qualitative perspective that is not based on analysis of patient data but rather on philosophical notions of 'fairness'. The authors propose a 5-class ranking system for patients based on the amount of care required by the patient as well as his risk of complications.…”

Section: Related Literaturementioning

confidence: 99%

“…Certainly, the general consensus of the medical community is that patients should be discharged in order of 'least critical first' (see, for instance, Swenson (1992)). However, what determines criticality is left wide open to interpretation and is highly dependent on the experience and training of an individual physician.…”

Section: Clinical Relevancementioning

confidence: 99%

Optimizing Intensive Care Unit Discharge Decisions with Patient Readmissions

Chan¹,

Farias

Bambos

et al. 2012

Operations Research

134

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This work examines the impact of discharge decisions under uncertainty in a capacity-constrained high risk setting: the intensive care unit (ICU). New arrivals to an ICU are typically very high priority patients and, should the ICU be full upon their arrival, discharging a patient currently residing in the ICU may be required to accommodate a newly admitted patient. Patients so discharged risk physiologic deterioration which might ultimately require readmission; models of these risks are currently unavailable to providers. These readmissions in turn impose an additional load on the capacity-limited ICU resources.We study the impact of several different ICU discharge strategies on patient mortality and total readmission load. We focus on discharge rules that prioritize patients based on some measure of criticality assuming the availability of a model of readmission risk. We use empirical data from over 5000 actual ICU patient flows to calibrate our model. The empirical study suggests that a predictive model of the readmission risks associated with discharge decisions, in tandem with simple index policies of the type proposed can provide very meaningful throughput gains in actual ICUs while at the same time maintaining, or even improving upon, mortality rates. We explicitly provide a discharge policy that accomplishes this. In addition to our empirical work, we conduct a rigorous performance analysis for the family of discharge policies we consider.We show that our policy is optimal in certain regimes, and is otherwise guaranteed to incur readmission related costs no larger than a factor of (ρ + 1) of an optimal discharge strategy, whereρ is a certain natural measure of system utilization.

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“…Applying Rawls' s concept of justice provides a similar answer. 8 After surgery, the 2 children needing ICU beds would be characterized as having a relatively high risk of life-threatening complications. This would place them at a higher priority for bed space than children whose likelihood of survival is so low that additional intensive care may be considered futile or of minimal benefit.…”

Section: Dr Wightman Respondsmentioning

confidence: 99%