Elizabeth M Viglianti1, Sean M Bagshaw2, Rinaldo Bellomo3,4, Joanne McPeake5,6, Xiao Qing Wang7, Sarah Seelye8, Theodore J Iwashyna7,8,9. 1. Department of Internal Medicine Division of Pulmonary and Critical Care, University of Michigan, 2800 Plymouth Road NCRC Building 14, G100-35, Ann Arbor, MI, 48109, USA. eviglian@med.umich.edu. 2. Department of Critical Care Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada. 3. Department of Epidemiology and Preventive Medicine, Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, VIC, Australia. 4. Department of Intensive Care, Alfred Hospital, Melbourne, VIC, Australia. 5. School of Medicine, Dentistry and Nursing, University of Glasgow, Glasgow, Scotland, UK. 6. Intensive Care Unit, Glasgow Royal Infirmary, NHS Greater Glasgow and Clyde, Glasgow, Scotland, UK. 7. Department of Internal Medicine Division of Pulmonary and Critical Care, University of Michigan, 2800 Plymouth Road NCRC Building 14, G100-35, Ann Arbor, MI, 48109, USA. 8. Veterans Affairs Center for Clinical Management Research, HSR&D Center for Innovation, Ann Arbor, MI, USA. 9. Institute for Social Research, Ann Arbor, MI, USA.
Abstract
PURPOSE: Patients with persistent critical illness may account for up to half of all intensive care unit (ICU) bed-days. It is unknown if there is hospital variation in the development of persistent critical illness and if hospital performance affects the incidence of persistent critical illness. METHODS: This is a retrospective analysis of Veterans admitted to the Veterans Administration (VA) ICUs from 2015 to 2017. Hospital performance was defined by the risk- and reliability-adjusted 30-day mortality. Persistent critical illness was defined as an ICU length of stay of at least 11 days. We used 2-level multilevel logistic regression models to assess variation in risk- and reliability-adjusted probabilities in the development of persistent critical illness. RESULTS: In the analysis of 100 hospitals which encompassed 153,512 hospitalizations, 4.9% (N = 7640/153,512) developed persistent critical illness. There was variation in the development of persistent critical illness despite controlling for patient characteristics (intraclass correlation: 0.067, 95% CI 0.049-0.091). Hospitals with higher risk- and reliability-adjusted 30-day mortality had higher probabilities of developing persistent critical illness (predicted probability: 0.057, 95% CI 0.051-0.063, p < 0.01) compared to those with lower risk- and reliability-adjusted 30-day mortality (predicted probability: 0.046, 95% CI 0.041-0.051, p < 0.01). The median odds ratio was 1.4 (95% CI 1.33-1.49) implying that, for two patients with the same physiology on admission at two different VA hospitals, the patient admitted to the hospital with higher adjusted mortality would have 40% greater odds of developing persistent critical illness. CONCLUSION: Hospitals with higher risk- and reliability-adjusted 30-day mortality have a higher probability of developing persistent critical illness. Understanding the drivers of this variation may identify modifiable factors contributing to the development of persistent critical illness.
PURPOSE:Patients with persistent critical illness may account for up to half of all intensive care unit (ICU) bed-days. It is unknown if there is hospital variation in the development of persistent critical illness and if hospital performance affects the incidence of persistent critical illness. METHODS: This is a retrospective analysis of Veterans admitted to the Veterans Administration (VA) ICUs from 2015 to 2017. Hospital performance was defined by the risk- and reliability-adjusted 30-day mortality. Persistent critical illness was defined as an ICU length of stay of at least 11 days. We used 2-level multilevel logistic regression models to assess variation in risk- and reliability-adjusted probabilities in the development of persistent critical illness. RESULTS: In the analysis of 100 hospitals which encompassed 153,512 hospitalizations, 4.9% (N = 7640/153,512) developed persistent critical illness. There was variation in the development of persistent critical illness despite controlling for patient characteristics (intraclass correlation: 0.067, 95% CI 0.049-0.091). Hospitals with higher risk- and reliability-adjusted 30-day mortality had higher probabilities of developing persistent critical illness (predicted probability: 0.057, 95% CI 0.051-0.063, p < 0.01) compared to those with lower risk- and reliability-adjusted 30-day mortality (predicted probability: 0.046, 95% CI 0.041-0.051, p < 0.01). The median odds ratio was 1.4 (95% CI 1.33-1.49) implying that, for two patients with the same physiology on admission at two different VA hospitals, the patient admitted to the hospital with higher adjusted mortality would have 40% greater odds of developing persistent critical illness. CONCLUSION: Hospitals with higher risk- and reliability-adjusted 30-day mortality have a higher probability of developing persistent critical illness. Understanding the drivers of this variation may identify modifiable factors contributing to the development of persistent critical illness.
Authors: Anil N Makam; Oanh Kieu Nguyen; Lei Xuan; Michael E Miller; James S Goodwin; Ethan A Halm Journal: JAMA Intern Med Date: 2018-03-01 Impact factor: 21.873
Authors: Marta L Render; James Deddens; Ron Freyberg; Peter Almenoff; Alfred F Connors; Douglas Wagner; Timothy P Hofer Journal: Crit Care Med Date: 2008-04 Impact factor: 7.598
Authors: Jai N Darvall; Tristan Boonstra; Jen Norman; Donal Murphy; Michael Bailey; Theodore J Iwashyna; Sean M Bagshaw; Rinaldo Bellomo Journal: Crit Care Resusc Date: 2019-06 Impact factor: 2.159
Authors: David F Gaieski; J Matthew Edwards; Michael J Kallan; Mark E Mikkelsen; Munish Goyal; Brendan G Carr Journal: Am J Respir Crit Care Med Date: 2014-09-15 Impact factor: 21.405
Authors: Xiao Qing Wang; Brenda M Vincent; Wyndy L Wiitala; Kaitlyn A Luginbill; Elizabeth M Viglianti; Hallie C Prescott; Theodore J Iwashyna Journal: BMC Med Res Methodol Date: 2019-05-08 Impact factor: 4.615
Authors: Louise Rose; Laura Istanboulian; Laura Allum; Lisa Burry; Craig Dale; Nicholas Hart; Kalliopi Kydonaki; Pam Ramsay; Natalie Pattison; Bronwen Connolly Journal: Crit Care Explor Date: 2019-04-17
Authors: John Muscedere; Braden Waters; Aditya Varambally; Sean M Bagshaw; J Gordon Boyd; David Maslove; Stephanie Sibley; Kenneth Rockwood Journal: Intensive Care Med Date: 2017-07-04 Impact factor: 17.440
Authors: Sean M Bagshaw; Danny J Zuege; Henry T Stelfox; Dawn Opgenorth; Tracy Wasylak; Nancy Fraser; Thanh X Nguyen Journal: Crit Care Med Date: 2022-03-01 Impact factor: 9.296
Authors: Michael C Blayney; Neil I Stewart; Callum T Kaye; Kathryn Puxty; Robert Chan Seem; Lorraine Donaldson; Catriona Haddow; Ros Hall; Caroline Martin; Martin Paton; Nazir I Lone; Joanne McPeake Journal: Br J Anaesth Date: 2022-03-24 Impact factor: 11.719
Authors: Jai N Darvall; Rinaldo Bellomo; Michael Bailey; Paul J Young; Kenneth Rockwood; David Pilcher Journal: Intensive Care Med Date: 2022-02-04 Impact factor: 41.787