Literature DB >> 25867907

Patient Mortality Is Associated With Staff Resources and Workload in the ICU: A Multicenter Observational Study.

Antoine Neuraz1, Claude Guérin, Cécile Payet, Stéphanie Polazzi, Frédéric Aubrun, Frédéric Dailler, Jean-Jacques Lehot, Vincent Piriou, Jean Neidecker, Thomas Rimmelé, Anne-Marie Schott, Antoine Duclos.   

Abstract

OBJECTIVE: Matching healthcare staff resources to patient needs in the ICU is a key factor for quality of care. We aimed to assess the impact of the staffing-to-patient ratio and workload on ICU mortality.
DESIGN: We performed a multicenter longitudinal study using routinely collected hospital data.
SETTING: Information pertaining to every patient in eight ICUs from four university hospitals from January to December 2013 was analyzed. PATIENTS: A total of 5,718 inpatient stays were included.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: We used a shift-by-shift varying measure of the patient-to-caregiver ratio in combination with workload to establish their relationships with ICU mortality over time, excluding patients with decision to forego life-sustaining therapy. Using a multilevel Poisson regression, we quantified ICU mortality-relative risk, adjusted for patient turnover, severity, and staffing levels. The risk of death was increased by 3.5 (95% CI, 1.3-9.1) when the patient-to-nurse ratio was greater than 2.5, and it was increased by 2.0 (95% CI, 1.3-3.2) when the patient-to-physician ratio exceeded 14. The highest ratios occurred more frequently during the weekend for nurse staffing and during the night for physicians (p < 0.001). High patient turnover (adjusted relative risk, 5.6 [2.0-15.0]) and the volume of life-sustaining procedures performed by staff (adjusted relative risk, 5.9 [4.3-7.9]) were also associated with increased mortality.
CONCLUSIONS: This study proposes evidence-based thresholds for patient-to-caregiver ratios, above which patient safety may be endangered in the ICU. Real-time monitoring of staffing levels and workload is feasible for adjusting caregivers' resources to patients' needs.

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Mesh:

Year:  2015        PMID: 25867907     DOI: 10.1097/CCM.0000000000001015

Source DB:  PubMed          Journal:  Crit Care Med        ISSN: 0090-3493            Impact factor:   7.598


  57 in total

1.  Mortality audit of medical patients at armed forces hospitals.

Authors:  K V S Hari Kumar; N S Ajai Chandra
Journal:  Med J Armed Forces India       Date:  2016-11-30

2.  Out of the ICU shifting as a significant workload.

Authors:  H Merdji; R Clere-Jehl; A Dargent; P Andreu; A Large; F Lefebvre; M Schenck; J Helms; J P Quenot; F Meziani
Journal:  Intensive Care Med       Date:  2018-06-13       Impact factor: 17.440

Review 3.  Telemedicine/Virtual ICU: Where Are We and Where Are We Going?

Authors:  Chiedozie Udeh; Belinda Udeh; Nadeem Rahman; Christina Canfield; Jack Campbell; J Steven Hata
Journal:  Methodist Debakey Cardiovasc J       Date:  2018 Apr-Jun

4.  Near-simultaneous intensive care unit (ICU) admissions and all-cause mortality: a cohort study.

Authors:  Markos G Kashiouris; Curtis N Sessler; Rehan Qayyum; Venu Velagapudi; Christos Stefanou; Rahul Kashyap; Niall Crowley; Craig Daniels; Kianoush Kashani
Journal:  Intensive Care Med       Date:  2019-09-17       Impact factor: 17.440

5.  Survey of Annual Staffing Workloads for Adult Critical Care Physicians Working in the United States.

Authors:  Jonathan E Sevransky; Z Jessie Chai; George A Cotsonis; J Perren Cobb; Stephen M Pastores
Journal:  Ann Am Thorac Soc       Date:  2016-05

Review 6.  Big Data and Data Science in Critical Care.

Authors:  L Nelson Sanchez-Pinto; Yuan Luo; Matthew M Churpek
Journal:  Chest       Date:  2018-05-09       Impact factor: 9.410

Review 7.  [Evaluation of care conditions in intensive care units : Results of an online questionnaire of critical care nurses].

Authors:  M Isfort
Journal:  Med Klin Intensivmed Notfmed       Date:  2017-05-02       Impact factor: 0.840

8.  Risk Factors for 1-Year Mortality and Hospital Utilization Patterns in Critical Care Survivors: A Retrospective, Observational, Population-Based Data Linkage Study.

Authors:  Tamas Szakmany; Angharad M Walters; Richard Pugh; Ceri Battle; Damon M Berridge; Ronan A Lyons
Journal:  Crit Care Med       Date:  2019-01       Impact factor: 7.598

9.  Intensive Care Unit Structure Variation and Implications for Early Mobilization Practices. An International Survey.

Authors:  Rita N Bakhru; David J McWilliams; Douglas J Wiebe; Vicki J Spuhler; William D Schweickert
Journal:  Ann Am Thorac Soc       Date:  2016-09

10.  Trends in Survival After In-Hospital Cardiac Arrest During Nights and Weekends.

Authors:  Uchenna R Ofoma; Suresh Basnet; Andrea Berger; H Lester Kirchner; Saket Girotra
Journal:  J Am Coll Cardiol       Date:  2018-01-30       Impact factor: 24.094

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