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

Song, Hummy; Tucker, Anita L.; Graue, Ryan; Moravick, Sarah; Yang, Julius

doi:10.2139/ssrn.3186726

Cited by 10 publications

(2 citation statements)

References 2 publications

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“…Via an instrumental variable (IV) approach, Song et al. (2018) empirically show that off‐service placement can lead to a 22.8% increase in patient LOS on average. Similar results are found in other hospital settings (Dong et al.…”

Section: Beyond the Single‐pool Model And Future Researchmentioning

confidence: 99%

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Recent Modeling and Analytical Advances in Hospital Inpatient Flow Management

Dai

Shi

2021

Production and Operations Management

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I npatient flow management plays a critical role in care delivery, patient outcomes, and hospital operational and financial costs. Modeling and performance analysis of inpatient flow present unique features and challenges that differ from operations in other service industries. In this study, we review recent modeling and analytical advances in the setting of inpatient flow management, with a particular focus on service time models motivated from the observations of inpatient discharges. We first compare two new service time models developed to capture the time-of-day inpatient flow dynamics, and reveal interesting connections between the two models. We then review analytical methods developed to analyze systems with the new service time models. Based on one method, which is amenable to a one-dimensional exact analysis under certain conditions, we further introduce its approximations that have explicit analytical forms and enable efficient computations in large systems. In particular, we showcase how to leverage a powerful tool, Stein's method framework, in the hospital setting for steady-state approximations and characterizing error bounds. We conclude this study by a literature review on other important aspects in inpatient flow management and propose future research directions, from both the modeling and analytical perspectives.

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Section: Beyond the Single‐pool Model And Future Researchmentioning

confidence: 99%

“…Recently, Song et al. (2018) take an empirical approach to examine the impact of such overflow practice on patient length of stay, readmission risk, and other outcomes; these empirical estimates could provide an estimate for the overflow penalty cost. In addition, Thompson et al.…”

Section: Beyond the Single‐pool Model And Future Researchmentioning

confidence: 99%

Recent Modeling and Analytical Advances in Hospital Inpatient Flow Management

Dai

Shi

2021

Production and Operations Management

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Influence of bedspacing on outcomes of hospitalised medicine service patients: a retrospective cohort study

et al. 2020

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BackgroundSpecialty wards cohort hospitalised patients to improve outcomes and lower costs. When demand exceeds capacity, patients overflow and are “bedspaced” to alternate wards. Some studies have demonstrated that bedspacing among medicine service patients is associated with adverse patient-centred outcomes, however, results have been inconsistent and have primarily been performed within national health systems. The objective of this study was to assess the association of bedspacing with patient-centred outcomes among United States patients admitted to general medicine services.MethodsWe performed a retrospective cohort study of internal medicine, family medicine and geriatric service patients who were bedspaced vs cohorted for the entirety of their hospital stay within three large, urban United States hospitals (quaternary referral centre, tertiary referral centre and community hospital, with different patient demographics and case-mixes) in 2014 and 2015. We performed quantile regression to determine differences in length of stay (LOS) between bedspaced vs cohorted patients and logistic regression for in-hospital mortality and discharge to home.ResultsAmong 18 802 patients in 33 wards, 6119 (33%) patients were bedspaced. Bedspaced patients had significantly longer LOS compared with cohorted patients at the 25th (0.1 days, 95% CI: 0.05 to 0.2, p=0.001), 50th (0.2 days, 95% CI: 0.1 to 0.3, p=0.003) and 75th (0.3 days, 95% CI: 0.2 to 0.5, p<0.001) percentiles; and no statistically significant differences in odds of mortality (OR=0.9, 95% CI: 0.6 to 1.3, p=0.5) or discharge to home (OR=0.9, 95% CI: 0.9 to 1.0, p=0.06) in adjusted analyses.ConclusionBedspacing is associated with adverse patient-centred outcomes. Future work is needed to confirm these findings, understand mechanisms contributing to adverse outcomes and identify factors that mitigate these adverse effects in order to provide high-value, patient-centred care to hospitalised patients.

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Dynamic Assignment of Patients to Primary and Secondary Inpatient Units: Is Patience a Virtue?

2016

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The views expressed in the HKS Faculty Research Working Paper Series are those of the author(s) and do not necessarily reflect those of the John F. Kennedy School of Government or of Harvard University. Faculty Research Working Papers have not undergone formal review and approval. Such papers are included in this series to elicit feedback and to encourage debate on important public policy challenges. Copyright belongs to the author(s). Papers may be downloaded for personal use only.

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

Cited by 10 publications

References 2 publications

Recent Modeling and Analytical Advances in Hospital Inpatient Flow Management

Recent Modeling and Analytical Advances in Hospital Inpatient Flow Management

Influence of bedspacing on outcomes of hospitalised medicine service patients: a retrospective cohort study

Dynamic Assignment of Patients to Primary and Secondary Inpatient Units: Is Patience a Virtue?

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