Quality measurement at intensive care units: which indicators should we use?

Vos, Maartje de; Graafmans, Wilco C.; Keesman, Els; Westert, Gert P.; Voort, Peter H. J. van der

doi:10.1016/j.jcrc.2007.01.002

Cited by 134 publications

(110 citation statements)

References 56 publications

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“…Of 68 potential complications, a final list was constructed by the subcommittee based on the following prerequisites: (1) existing evidence in the literature that the complication relates to patient damage, (2) complication must be either severe or frequent, (3) the complication must be clearly defined and measurable, and (4) the complication must be preventable by taking appropriate measures. The final list was approved by all Dutch Society for Intensive Care Medicine members and included in the NICE registration 16, 17…”

Section: Methodsmentioning

confidence: 99%

“…To determine the effect of CRM implementation on complication incidence, we used a predetermined set of 18 complications obtained from the NICE database 16, 17. Data were collected during the baseline year preceding the 3‐month CRM training phase (August 2009 to end of July 2010), the implementation year following the training phase (November 2010 to end of October 2011), and the post‐implementation year (November 2011 to end of October 2012).…”

Section: Methodsmentioning

confidence: 99%

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Crew Resource Management in the Intensive Care Unit: a prospective 3‐year cohort study

Haerkens

Kox

Lemson

et al. 2015

Acta Anaesthesiol Scand

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BackgroundHuman factors account for the majority of adverse events in both aviation and medicine. Human factors awareness training entitled “Crew Resource Management (CRM)” is associated with improved aviation safety. We determined whether implementation of CRM impacts outcome in critically ill patients.MethodsWe performed a prospective 3‐year cohort study in a 32‐bed ICU, admitting 2500–3000 patients yearly. At the end of the baseline year, all personnel received CRM training, followed by 1 year of implementation. The third year was defined as the clinical effect year. All 7271 patients admitted to the ICU in the study period were included.The primary outcome measure was ICU complication rate. Secondary outcome measures were ICU and hospital length of stay, and standardized mortality ratio.ResultsOccurrence of serious complications was 67.1/1000 patients and 66.4/1000 patients during the baseline and implementation year respectively, decreasing to 50.9/1000 patients in the post‐implementation year (P = 0.03). Adjusted odds ratios for occurrence of complications were 0.92 (95% CI 0.71‐1.19, P = 0.52) and 0.66 (95% CI 0.51‐0.87, P = 0.003) in the implementation and post‐implementation year. The incidence of cardiac arrests was 9.2/1000 patients and 8.3/1000 patients during the baseline and implementation year, decreasing to 3.5/1000 patients (P = 0.04) in the post‐implementation year, while cardiopulmonary resuscitation success rate increased from 19% to 55% and 67% (P = 0.02). Standardized mortality ratio decreased from 0.72 (95% CI 0.63‐0.81) in the baseline year to 0.60 (95% CI 0.53‐0.67) in the post‐implementation year (P = 0.04).ConclusionOur data indicate an association between CRM implementation and reduction in serious complications and lower mortality in critically ill patients.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Crew Resource Management in the Intensive Care Unit: a prospective 3‐year cohort study

Haerkens

Kox

Lemson

et al. 2015

Acta Anaesthesiol Scand

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“…Th e Centers for Medicare & Medicaid Services evaluated ICU readmissions as a candidate ICU quality indicator 1 based on evidence that readmissions are associated with increased mortality and cost [2][3][4][5][6][7][8][9][10][11][12] and because they are presumed to result from "premature" ICU discharge, 13 bed shortages, 14,15 or poorly orchestrated handoff s. 10,16 However, other reports show that while patients discharged when ICUs are more strained have increased odds of ICU readmission, the risk of death is no higher, suggesting that decisions preceding ICU readmissions may not cause the excess mortality with which they are associated. [17][18][19] Additionally, the performance of ICUs on ICU readmissions is not correlated with performance on other measures of ICU quality, such as mortality or process measures.…”

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confidence: 99%

Assessing the Utility of ICU Readmissions as a Quality Metric

Brown

Ratcliffe

Halpern

2015

Chest

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BACKGROUND: ICU readmissions are associated with increased mortality and costs; however, it is unclear whether these outcomes are caused by readmissions or by residual confounding by illness severity. An assessment of temporal changes in ICU readmission in response to a specific policy change could help disentangle these possibilities. We sought to determine whether ICU readmission rates changed aft er 2003 Accreditation Council for Graduate Medical Education Resident Duty Hours reform ("reform") and whether there were temporally corresponding changes in other ICU outcomes.

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“…The approach by Donabedian combines several issues, related to the organizational structure, processes, and outcomes, in a comprehensive clinical model. In particular, the health system is split into four conceptual components: mission, structural capacity, processes and outcomes, all interacting with the macro context [2,5,7,14]. From this division in different areas the evaluation of reference indicators and/or parameters, is a technique widely used in healthcare.…”

Section: Quality Measurements In Health Systemsmentioning

confidence: 99%

Evaluation of indices for the measurement of quality in health systems

Clemente

Papi

Pontecorvi

et al. 2016

Int. J. Metrol. Qual. Eng.

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Abstract. In recent decades different numeric indicators and methods have been used to qualify structured index that express health service components quality performance. The first step of this work is the definition of a model of the system under examination in order to define its measurable constituent entities (dimensions). Among the common measured clinical parameters, a robust metrics, characterizing the constituent entities and the best opportunity tools for the characterization of the results, have been identified. The last step is multimodal analysis of the results. Using this approach the paper presents an application in the evolution of the cardiological intensive care unit (ICU). Particularly, the attention of this paper is focused on the evolving of the medical team.

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Quality measurement at intensive care units: which indicators should we use?

Cited by 134 publications

References 56 publications

Crew Resource Management in the Intensive Care Unit: a prospective 3‐year cohort study

Crew Resource Management in the Intensive Care Unit: a prospective 3‐year cohort study

Assessing the Utility of ICU Readmissions as a Quality Metric

Evaluation of indices for the measurement of quality in health systems

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