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ICU Occupancy and Mechanical Ventilator Use in the United States*
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OBJECTIVES: Detailed data on occupancy and use of mechanical ventilators in U. S. ICU over time and across unit types are lacking. We sought to describe the hourly bed occupancy and use of ventilators in U.S. ICUs to improve future planning of both the routine and disaster provision of intensive care. DESIGN: Retrospective cohort study. We calculated mean hourly bed occupancy in each ICU and hourly bed occupancy for patients on mechanical ventilators. We assessed trends in overall occupancy over the 3 years. We also assessed occupancy and mechanical ventilation rates across different types and sizes of ICUs. SETTING: Ninety-seven U.S. ICUs participating in Project IMPACT from 2005 to 2007. PATIENTS: A total of 226,942 consecutive admissions to ICUs. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Over the 3 years studied, total ICU occupancy ranged from 57.4% to 82.1% and the number of beds filled with mechanically ventilated patients ranged from 20.7% to 38.9%. There was no change in occupancy across years and no increase in occupancy during influenza seasons. Mean hourly occupancy across ICUs was 68.2% ± 21.3% (SD) and was substantially higher in ICUs with fewer beds (mean, 75.8% ± 16.5% for 5-14 beds vs 60.9% ± 22.1% for 20+ beds, p = 0.001) and in academic hospitals (78.7% ± 15.9% vs 65.3% ± 21.3% for community not-for-profit hospitals, p < 0.001). More than half of ICUs (53.6%) had 4+ beds available more than half the time. The mean percentage of ICU patients receiving mechanical ventilation in any given hour was 39.5% (± 15.2%), and a mean of 29.0% (± 15.9%) of ICU beds were filled with a patient on a ventilator. CONCLUSIONS: Occupancy of U.S. ICUs was stable over time, but there is uneven distribution across different types and sizes of units. Only three of 10 beds were filled at any time with mechanically ventilated patients, suggesting substantial surge capacity throughout the system to care for acutely critically ill patients.
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“However, the mechanically ventilated population (40%) was fairly representative of the national average of ICU beds receiving mechanical ventilation.34”
From Feasibility of a virtual reality intervention in the intensive care unit (2021) · cites this paper as [34]
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Halpern, N. A., & Pastores, S. M. (2009) · Critical Care Medicine · doi:10.1097/ccm.0b013e3181b090d0 · Cited by 818
Variation in critical care services across North America and Western Europe*
Wunsch, H., Angus, D. C., Harrison, D. A., Collange, O., Fowler, R., Hoste, E. A. J., de Keizer, N. F., Kersten, A., Linde‐Zwirble, W. T., Sandiumenge, A., et al. (2008) · Critical Care Medicine · doi:10.1097/ccm.0b013e318186aec8 · Cited by 626
Self-citationThe epidemiology of mechanical ventilation use in the United States*
Wunsch, H., Linde‐Zwirble, W. T., Angus, D. C., Hartman, M. E., Milbrandt, E. B., & Kahn, J. M. (2010) · Critical Care Medicine · doi:10.1097/ccm.0b013e3181ef4460 · Cited by 541
Self-citationHospital Volume and the Outcomes of Mechanical Ventilation
Kahn, J. M., Goss, C. H., Heagerty, P. J., Kramer, A. A., O'Brien, C. R., & Rubenfeld, G. D. (2006) · New England Journal of Medicine · doi:10.1056/nejmsa053993 · Cited by 507
Self-citationAngus, D. C., Shorr, A. F., White, A., Dremsizov, T. T., Schmitz, R. J., & Kelley, M. A. (2006) · Critical Care Medicine · doi:10.1097/01.ccm.0000206105.05626.15 · Cited by 437
Aylwin, C. J., König, T. C., Brennan, N. W., Shirley, P. J., Davies, G., Walsh, M., & Brohi, K. (2006) · The Lancet · doi:10.1016/s0140-6736(06)69896-6 · Cited by 419
Higgins, T. L., Teres, D., Copes, W. S., Nathanson, B. H., Stark, M., & Kramer, A. A. (2007) · Critical Care Medicine · doi:10.1097/01.ccm.0000257337.63529.9f · Cited by 333
Self-citationRationing critical care beds: A systematic review*
Sinuff, T., Kahnamoui, K., Cook, D. J., Luce, J. M., & Levy, M. M. (2004) · Critical Care Medicine · doi:10.1097/01.ccm.0000130175.38521.9f · Cited by 271
Comparison of Medical Admissions to Intensive Care Units in the United States and United Kingdom
Wunsch, H., Angus, D. C., Harrison, D. A., Linde‐Zwirble, W. T., & Rowan, K. (2011) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201012-1961oc · Cited by 256
Self-citationRationing of Intensive Care Unit Services
Strauss, M. J. (1986) · JAMA · doi:10.1001/jama.255.9.1143 · Cited by 245
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Items 101–200 of 286
The Urge to Build More Intensive Care Unit Beds and Ventilators: Intuitive but Errant
Halpern, S. D., & Miller, F. G. (2020) · Annals of Internal Medicine · doi:10.7326/m20-2071 · Cited by 13
Self-citationAdvanced Modes of Mechanical Ventilation: Introduction for the Critical Care Pharmacist
Cawley, M. J. (2017) · Journal of Pharmacy Practice · doi:10.1177/0897190017734766 · Cited by 12
Mechanical ventilation strategy for pulmonary rehabilitation based on patient-ventilator interaction
Hao, L., Li, X., Shi, Y., Cai, M., Ren, S., Xie, F., Li, Y., Wang, N., Wang, Y., Luo, Z., et al. (2021) · Science China Technological Sciences · doi:10.1007/s11431-020-1778-8 · Cited by 12
Passive Leg Raise: Feasibility and Safety of the Maneuver in Patients With Undifferentiated Shock
Toppen, W., Montoya, E. A., Ong, S. L., Markovic, D., Kao, Y.-H., Xu, X., Chiem, A. T., Cannesson, M. P., Berlin, D., & Barjaktarević, I. (2018) · Journal of Intensive Care Medicine · doi:10.1177/0885066618820492 · Cited by 12
Kim, G.-H., Kim, J.-W., Kim, K. H., Kang, H., Moon, J. Y., Shin, Y. M., & Park, S. (2023) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2023.107673 · Cited by 11
Bogdanov, C., Hohenstein, S., Brederlau, J., Groesdonk, H. V., Bollmann, A., & Kuhlen, R. (2024) · Journal of Clinical Medicine · doi:10.3390/jcm13123393 · Cited by 11
Knapik, P., Knapik, M., Trejnowska, E., Kłaczek, B., Śmietanka, K., Cieśla, D., Krzych, Ł. J., & Kucewicz-Czech, E. M. (2019) · Archives of Medical Science · doi:10.5114/aoms.2019.84401 · Cited by 11
Provancha-Romeo, A. F., Hoffman, A. L., Malcolm, M. P., Coatsworth, J. D., Laxton, L. R., Freeman, K. M., & Schmid, A. A. (2019) · Work · doi:10.3233/wor-192920 · Cited by 11
Gunther, I., Pradhan, D. R., Lubinsky, A. S., Urquhart, A., Thompson, J. A., & Reynolds, S. S. (2021) · Dimensions of Critical Care Nursing · doi:10.1097/dcc.0000000000000462 · Cited by 16
Chen, Z., Russo, N. W., Miller, M. M., Murphy, R. X., & Burmeister, D. B. (2021) · Journal of the American College of Emergency Physicians Open · doi:10.1002/emp2.12406 · Cited by 11
Pediatric Ventilator-Associated Events Before and After a Multicenter Quality Improvement Initiative
Wu, A., Madhavan, G., Deakins, K., Evans, D. L., Hayward, A., Pugh, C., Stutts, A., Mustin, L., Staubach, K. C., Sisson, P., et al. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.46545 · Cited by 11
Conséquences de la ventilation mécanique sur le diaphragme
Jung, B., Gleeton, D., Daurat, A., Conseil, M., Mahul, M., Rao, G. R., Matecki, S., Lacampagne, A., & Jaber, S. (2014) · Revue des Maladies Respiratoires · doi:10.1016/j.rmr.2014.08.013 · Cited by 11
Medical emergency team may reduce obstetric intensive care unit admissions
Baek, M. S., Son, J., Huh, J. W., Lim, C., Koh, Y., Won, H., Shim, J., & Hong, S. (2016) · Journal of obstetrics and gynaecology research · doi:10.1111/jog.13177 · Cited by 11
Ha, T. S., Oh, D. K., Lee, H., Chang, Y., Jeong, I. S., Sim, Y. S., Hong, S., Park, S., Park, S. Y., & Park, S. Y. (2024) · Acute and Critical Care · doi:10.4266/acc.2024.00052 · Cited by 14
Evaluating skeletal muscle wasting and weakness in models of critical illness
Bongetti, A. J., Caldow, M. K., Abdelhamid, Y. A., & Lynch, G. S. (2025) · Clinical Science · doi:10.1042/cs20255458 · Cited by 14
Barbash, I. J., Le, T. Q., Pike, F., Barnato, A. E., Angus, D. C., & Kahn, J. M. (2016) · Annals of the American Thoracic Society · doi:10.1513/annalsats.201509-645oc · Cited by 10
Monitoring Lung Mechanics during Mechanical Ventilation using Machine Learning Algorithms
Hezarjaribi, N., Dutta, R., Xing, T., Murdoch, G. K., Mazrouee, S., Mortazavi, B. J., & Ghasemzadeh, H. G. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8512483 · Cited by 10
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Vacas, S., & Cannesson, M. P. (2019) · Journal of Cardiothoracic and Vascular Anesthesia · doi:10.1053/j.jvca.2019.03.045 · Cited by 10
Yang, R. (2020) · medRxiv · doi:10.1101/2020.06.07.20124933 · Cited by 11
Ettenberger, M., Libreros, R. C., Chávez-Chavéz, J., Cordoba-Silva, J. G., Betancourt-Zapata, W., Maya, R., Fandiño-Vergara, L. A., Valderrama, M., Silva-Fajardo, I., & Hernández‐Zambrano, S. M. (2024) · Journal of Intensive Medicine · doi:10.1016/j.jointm.2024.01.006 · Cited by 14
The importance of initial response during outbreaks: A perspective from observations on COVID-19
Yeo, Y. Y., & Ganem, B. (2020) · Infection Control and Hospital Epidemiology · doi:10.1017/ice.2020.150 · Cited by 9
Karamolegkos, N., Albanese, A., & Chbat, N. W. (2021) · IEEE Open Journal of Engineering in Medicine and Biology · doi:10.1109/ojemb.2021.3128629 · Cited by 9
Role of Family Members in Pain Management in Adult Critical Care
Gosselin, É., & Richard-Lalonde, M. (2019) · AACN Advanced Critical Care · doi:10.4037/aacnacc2019275 · Cited by 9
The pharmacist’s role in implementation of the ABCDEF bundle into clinical practice
Schmidt, L. E., Patel, S. R., & Stollings, J. L. (2020) · American Journal of Health-System Pharmacy · doi:10.1093/ajhp/zxaa247 · Cited by 9
Habr, B., Saliba, Y., Hajal, J., Smayra, V., Riachy, M. A., & Farès, N. (2020) · Life Sciences · doi:10.1016/j.lfs.2020.118366 · Cited by 10
O’Gara, B., Serra, A. L., Englert, J. A., Sachdev, A., Owens, R. L., Chang, S. Y., Park, P. K., Talmor, D. S., Sverud, I., Sackey, P., et al. (2025) · Trials · doi:10.1186/s13063-025-08791-0 · Cited by 8
Louie, J. M., Lonardo, N. W., Mone, M. C., Stevens, V. W., Deka, R., Shipley, W., & Barton, R. G. (2018) · Pharmacy · doi:10.3390/pharmacy6030093 · Cited by 8
Dang, T., Roberts, D., Murray, A., & Wiggermann, N. E. (2022) · International Journal of Industrial Ergonomics · doi:10.1016/j.ergon.2022.103372 · Cited by 8
Harlan, E. A., Venkatesh, S., Morrison, J., Cooke, C. R., Iwashyna, T. J., Ford, D. W., Moscovice, I., Sjoding, M. W., & Valley, T. S. (2024) · Annals of the American Thoracic Society · doi:10.1513/annalsats.202308-684oc · Cited by 8
Weaning‐associated interventions for ventilated intensive care patients: A scoping review
Sterr, F., Bauernfeind, L., Knop, M., Rester, C., Metzing, S., & Palm, R. (2024) · Nursing in Critical Care · doi:10.1111/nicc.13143 · Cited by 9
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Bojkovic, K., Rodgers, J. L., Vichare, R., Nandi, A., Mansour, N., Saleem, F., Abıdın, Z. U., Vanthenapalli, S., Cheng, F., & Panguluri, S. K. (2021) · Scientific Reports · doi:10.1038/s41598-021-02550-2 · Cited by 8
Huang, M., Chen, C., Horng, M., Li, C.-I., Hsu, I.-L., Su, C.-M., Sun, Y., & Lai, C. (2022) · Anesthesiology · doi:10.1097/aln.0000000000004378 · Cited by 9
Chen, X., Li, J., Liu, G., Chen, X., Huang, S., Li, H., Liu, S., Li, D., Yang, H., Zheng, H., et al. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12041499 · Cited by 9
Health and Economic Impacts of Lockdown Policies in the Early Stage of COVID-19 in the United States
Boloori, A., & Saghafian, S. (2023) · Service Science · doi:10.1287/serv.2023.0321 · Cited by 8
Ali, B. A., Lefering, R. L., Moral, M. F., & Otano, T. B. (2017) · Scandinavian Journal of Trauma Resuscitation and Emergency Medicine · doi:10.1186/s13049-017-0453-2 · Cited by 8
Lee, H., Choi, S., Jang, E. J., Lee, J., Kim, D., Yoo, S., Oh, S., & Ryu, H. G. (2019) · Journal of Korean Medical Science · doi:10.3346/jkms.2019.34.e212 · Cited by 8
Mechanical ventilation in Spain, 1998–2016: Epidemiology and outcomes
Peñuelas, Ó., Frutos–Vivar, F., Muriel, A., Mancebo, J., García-Jiménez, A., de Pablo, R., Valledor, M., Ferrer, M., León, M., Quiroga, J. M., et al. (2020) · Medicina Intensiva (English Edition) · doi:10.1016/j.medine.2020.11.001 · Cited by 8
Sessler, C. N. (2014) · CHEST Journal · doi:10.1378/chest.13-2746 · Cited by 8
Sheng, B., Li, S., Wang, H., Guo, Z., & Zhang, Z. (2024) · Medicine · doi:10.1097/md.0000000000035818 · Cited by 9
Ren, S., Wang, X., Hao, L., Yang, F., Niu, J., Cai, M., Shi, Y., Wang, T., & Luo, Z. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.121621 · Cited by 7
Petrinec, A. B., Hughes, J. W., Zullo, M. D., Wilk, C., & George, R. L. (2021) · JMIR Research Protocols · doi:10.2196/30813 · Cited by 7
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Jia, Y., McDermid, J. A., & Habli, I. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-77211-6_46 · Cited by 7
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Seymour, C. W., Alotaik, O., Wallace, D. J., Elhabashy, A. E., Chhatwal, J., Rea, T. D., Angus, D. C., Nichol, G., & Kahn, J. M. (2015) · Critical Care Medicine · doi:10.1097/ccm.0000000000001133 · Cited by 7
Oud, L., & Garza, J. (2020) · Journal of Critical Care · doi:10.1016/j.jcrc.2020.10.019 · Cited by 7
Extubation of the potentially difficult airway in the intensive care unit
Joffe, A., & Barnes, C. R. (2022) · Current Opinion in Anaesthesiology · doi:10.1097/aco.0000000000001119 · Cited by 7
Sterr, F., Hechinger, M., Bauernfeind, L., Rester, C., Palm, R., & Metzing, S. (2025) · Critical Care · doi:10.1186/s13054-025-05326-6 · Cited by 6
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Alkhateeb, T., Semler, M. W., Girard, T. D., Ely, E. W., & Stollings, J. L. (2023) · Journal of Intensive Care Medicine · doi:10.1177/08850666231213337 · Cited by 6
Huang, K., Lin, C., Chi, S.-H., Hsu, Y., & Xu, J.-L. (2024) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2024.1456771 · Cited by 6
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MacLeod, J. B. A., Kirton, O. C., & Maerz, L. L. (2016) · Trauma Surgery & Acute Care Open · doi:10.1136/tsaco-2016-000058 · Cited by 6
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Yin, C., Liu, R., Caterino, J. M., & Zhang, P. (2022) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3534678.3539413 · Cited by 7
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Bravo, F., Rudin, C. D., Shaposhnik, Y., & Yuan, Y. (2023) · Stochastic Systems · doi:10.1287/stsy.2022.0018 · Cited by 5
Characteristics and outcomes of prehospital and emergency department surgical airways
Mathews, A. C., McLeod, K., Lacy, A. J., High, K., Brywczynski, J. J., McKinney, J. J., Wrenn, J. O., Jones, I. D., & Stubblefield, W. B. (2024) · Journal of the American College of Emergency Physicians Open · doi:10.1002/emp2.13136 · Cited by 5
Hughes, N. G. J., Jia, Y., Sujan, M. A., Lawton, T., Habli, I., & McDermid, J. A. (2024) · Applied Ergonomics · doi:10.1016/j.apergo.2024.104275 · Cited by 5
Latronico, N. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.734257237.793558849 · Cited by 5
Sottile, P. D., Smith, B. J., Moss, M., & Albers, D. J. (2023) · medRxiv · doi:10.1101/2023.11.28.23299134 · Cited by 5
Lin, M.-Y., Chi, H.-Y., & Chao, W. (2024) · Digital Health · doi:10.1177/20552076241289732 · Cited by 4
Racial Bias in Pain Measurement Frequency in ICU and its Impact on Early Readmission
Jetley, G., & Zhang, H. (2024) · Production and Operations Management · doi:10.1177/10591478241235003 · Cited by 4
Solaiman, O., Elhassan, T. A. M., Fakih, R. O. E., Mannan, A., Duhailib, Z. A., Mahdali, A. A., Alzahrani, H. A., Jamil, M. G., Chaudhri, N. A., Elhazmi, A., et al. (2024) · Hematology/Oncology and Stem Cell Therapy · doi:10.56875/2589-0646.1114 · Cited by 4
Lin, Z., Huang, X., & Shan, X. (2022) · Annals of Palliative Medicine · doi:10.21037/apm-22-646 · Cited by 4
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Haghpanah, F., Lin, G., Klein, E. Y., & Program, F. T. C. M.-H. (2023) · Royal Society Open Science · doi:10.1098/rsos.230277 · Cited by 2
Siddiqui, S., & Ramakrishnan, P. (2018) · Indian Journal of Anaesthesia · doi:10.4103/ija.ija_428_18 · Cited by 4
Methods for Reinforcement Learning in Clinical Decision Support
Prasad, N. (2020) · Cited by 4
Heiderscheit, A. (2021) · IntechOpen eBooks · doi:10.5772/intechopen.95889 · Cited by 4
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Boloori, A., & Saghafian, S. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3681610 · Cited by 4
Roberts, M. D., Seymour, H. D., & Dimitrov, A. G. (2020) · medRxiv · doi:10.1101/2020.12.05.20222968 · Cited by 4
Ha, T. S., Oh, D. K., Lee, H.-J., Chang, Y., Jeong, I. S., Sim, Y. S., Hong, S.-K., Park, S., Suh, G. Y., & Park, S. Y. (2024) · Tuberculosis and Respiratory Diseases · doi:10.4046/trd.2024.0039 · Cited by 3
Virtual reality for delirium prevention in mechanically ventilated ICU patients: a narrative review
Li, J., Su, M., Zhao, Y., Zhu, Y., Hu, Y., Zhao, H., & Li, L. (2025) · Frontiers in Medicine · doi:10.3389/fmed.2025.1686453 · Cited by 3
Prognostic value of hematocrit levels among critically ill patients with acute kidney injury
Zhou, Y., Zheng, M., Chen, C.-S., Sun, D., Chen, X., Sun, M., Wang, Y., Liu, Y., Pan, J., & Zheng, C.-F. (2019) · European Journal of Inflammation · doi:10.1177/2058739219846820 · Cited by 4
Chen, K., Wallace, S. K., & Nates, J. L. (2018) · Springer eBooks · doi:10.1007/978-3-319-74698-2_5-1 · Cited by 3
Vaughn, L., & Salas, A. S. (2022) · The Canadian Journal of Critical Care Nursing · doi:10.5737/23688653-3311420 · Cited by 9
Othman, F. M., Ismaiel, Y. T., Alkhathran, S., Alshamrani, A., Alghamdi, M., & Ismaeil, T. (2020) · Journal of Natural Science Biology and Medicine · doi:10.4103/jnsbm.jnsbm_188_19 · Cited by 3
Signal quality indices for state space electrophysiological signal processing and vice versa
Oster, J., & Clifford, G. D. (2015) · Cambridge University Press eBooks · doi:10.1017/cbo9781139941433.016 · Cited by 3
Remote Proactive Physiologic Monitoring in the ICU
Ramnath, V. R., & Malhotra, A. (2019) · Springer eBooks · doi:10.1007/978-3-030-11569-2_2 · Cited by 3
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Bravo, F., Rudin, C. D., Shaposhnik, Y., & Yuan, Y. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3384148 · Cited by 3
van Diepen, A., Bakkes, T. H. G. F., De Bie, A. J. R., Turco, S., Bouwman, R. A., Woerlee, P. H., & Mischi, M. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.15684 · Cited by 3
Kolmar, A. R., Bravo, D., Fonseca, R. A., Kramer, M. A., Wang, J., Guilliams, K. P., & Fuller, B. M. (2025) · Critical Care Explorations · doi:10.1097/cce.0000000000001255 · Cited by 3
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Fabry, B., Bonakdar, N., Kuster, C., Bartl, J., Krischke, F., & Francis, R. (2025) · Intensive Care Medicine Experimental · doi:10.1186/s40635-025-00846-5 · Cited by 2
Murata, K., Shimoyama, K., & Tsuruya, T. (2024) · BMC Pulmonary Medicine · doi:10.1186/s12890-024-02914-0 · Cited by 2
Mahmoud, N. M. S., Hammad, A. R. M., Okaily, N. I., & Afify, M. F. (2024) · International Journal of Pediatrics and Adolescent Medicine · doi:10.4103/ijpam.ijpam_61_24 · Cited by 2
Heizmann, J., Gross, C., Yap, C. R., Walling, M. A., Reid, M., Hsu, A. T., Crandall, M. L., & Ra, J. (2024) · American Journal of Medicine Open · doi:10.1016/j.ajmo.2024.100080 · Cited by 2
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Cao, L., Zhu, Y., Zhou, H., Tan, S., & Gong, W. (2025) · International Conference on Computer Supported Cooperative Work in Design (CSCWD) · doi:10.1109/cscwd64889.2025.11033588 · Cited by 2
Schorr, C., & Angelo, M. (2018) · Critical Care Medicine · doi:10.1097/ccm.0000000000003233 · Cited by 2
Delayed Discharge From the Intensive Care Unit Is Associated With Longer Hospital Lengths of Stay
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Metadata
- Authors
- Wunsch, H., Wagner, J., Herlim, M., Chong, D. H., Kramer, A. A., & Halpern, S. D.
- Affiliations
- Columbia University (US)
- University of Pennsylvania (US)
- Leonard Davis Institute of Health Economics (US)
- Venue
- Critical Care Medicine
- Published
- 2013-12
- Volume
- 41
- Issue
- 12
- Pages
- 2712-2719
- ISSN
- 0090-3493 (ISSN-L)
- PMC
- PMC3840149
- OpenAlex
- W2050845046
- Cited by
- 287
- References
- 36
- Citations by year
- 2026: 17 · 2025: 27 · 2024: 34 · 2023: 25 · 2022: 24 · 2021: 27 · 2020: 39 · 2019: 24 · 2018: 17 · 2017: 13 · 2016: 11 · 2015: 17 · 2014: 9 · 2013: 1
- FWCI
- 19.76
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Critical Care Medicine (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Agency for Healthcare Research and Quality (K08HS018406)
- National Institute on Aging (K08AG038477)
- National Center for Research Resources (UL1RR024156)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Healthcare Operations and Scheduling Optimization
- Health Sciences › Medicine › Emergency Medicine › Emergency and Acute Care Studies
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Respiratory Support and Mechanisms
- Keywords
- ICU bed occupancy, mechanical ventilation, intensive care unit, surge capacity, academic vs community hospitals, influenza season, disaster preparedness, project impact, critically ill patients
- MeSH terms
- Academic Medical Centers, Adult, Aged, Bed Occupancy, Female, Hospitals, Community, Hospitals, Voluntary, Humans, Intensive Care Units, Length of Stay, Male, Middle Aged, Respiration, Artificial, Retrospective Studies, Time Factors, United States
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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