Use of ventilator associated pneumonia bundle and statistical process control chart to decrease VAP rate in Syria

Alsadat, Reem; Al-bardan, Hussam; Mazloum, Mona N; Shamah, Asem A; Eltayeb, Mohamed F E; Marie, Ali; Dakkak, Abdulrahman; Naes, Ola; Esber, Faten; Betelmal, Ibrahim; Kherallah, Mazen

doi:10.4103/2231-0770.110736

Cited by 20 publications

(9 citation statements)

References 20 publications

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“…More precisely, it has been estimated that hospital mortality rates due to HAP and VAP vary from 20% to 70% based on the definition, study population, and the type of hospital or ICU ( 2 ). According to the literature, the general rate of VAP is 13.6 per 1000 ventilator days ( 3 ). Every year, millions of people suffer from poisoning and mortality due to poisoning, which has dramatically increased within the recent years ( 4 ).…”

Section: Introductionmentioning

confidence: 99%

Central Nervous System Depressants Poisoning and Ventilator Associated Pneumonia: An Underrated Risk Factor at the Toxicological Intensive Care Unit

Hashemian

Talaie

Akbarpour

et al. 2016

Iran Red Crescent Med J

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Background:Ventilator-Associated Pneumonia (VAP) is the main cause of nosocomial infection at intensive care units (ICUs), which causes high mortality and morbidity.Objectives:The objective of the present survey was to identify the VAP risk and prognostic factors among poisoned patients, who were admitted to the toxicological ICU (TICU), especially central nervous system (CNS) depressants due to their prevalence and importance.Patients and Methods:A case-control study was conducted at the Loghman Hakim hospital between March 2013 and March 2014. Among 300 poisoned patients with mechanical ventilator ≥ 48 hours, 150 patients, who had developed microbiologically-confirmed VAP were considered as the VAP group and 150 without VAP were defined as the control group. The following data were collected; age, gender, type of poisoning, glasgow coma score, Acute physiology and chronic health evaluation (APACHE) II score, length of hospital stay, previous antibiotic use, microbial culture of the trachea, body temperature, leukocyte count, and patients’ outcome. Based on the type of poisoning, patients were divided into three groups including: opioid, CNS depressants and others. All data were expressed as means (SD) for continuous variables and frequencies for categorical variables. Logistic regression was used to determine the relationship between risk factors and VAP.Results:The mean age of the patients was 33.9 ± 14.3 years. The probable VAP incidence and mortality were 22% and 18.6%, respectively. The rate of CNS depressant versus opioid use (odds ratio, 3.74; P < 0.027), APACHE II (odds ratio, 1.28; P < 0.000) and length of hospital stay (odds ratio, 2.15; P < 0.000) were the independent risk factors for VAP. While, the APACHE II score (odds ratio, 1.12; P < 0.044) and length of hospital stay (odds ratio, 2.15; P < 0.000) were the independent predictors of VAP mortality among these patients. The most common microorganisms in VAP cases were Methicillin-Resistant Staphylococcus aureus (MRSA) and Acinetobacter sp. (56.7% and 12.7%, respectively).Conclusions:Central nervous system depressant was an important risk factor for VAP among poisoned patients. Hypoventilation due to CNS depression can lead to VAP. The APACHE II and length of hospital stay were shown as independent predictors of VAP and mortality among these patients.

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Section: Introductionmentioning

confidence: 99%

Central Nervous System Depressants Poisoning and Ventilator Associated Pneumonia: An Underrated Risk Factor at the Toxicological Intensive Care Unit

Hashemian

Talaie

Akbarpour

et al. 2016

Iran Red Crescent Med J

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“…The need for improvement in the delivery of important care processes in ICUs has been demonstrated internationally [ 1 – 3 ], highlighting a gap between evidence and practice on a wide scale [ 4 ]. Improvement initiatives designed to address this [ 5 ] can lead to improved health outcomes for patients [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Testing the implementation of an electronic process-of-care checklist for use during morning medical rounds in a tertiary intensive care unit: a prospective before–after study

Conroy

Elliott

Burrell

2015

Ann. Intensive Care

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BackgroundTo improve the delivery of important care processes in the ICU, morning ward round checklists have been implemented in a number of intensive care units (ICUs) internationally. Good quality evidence supporting their use as clinical support tools is lacking. With increased use of technology in clinical settings, integration of such tools into current work practices can be a challenge and requires evaluation. Having completed preliminary work revealing variations in practice and evidence supporting the construct validity of a process-of-care checklist, the need to develop, test and further validate an e(lectronic)-checklist in an ICU was identified.MethodsA prospective, before–after study was conducted in a 19-bed general ICU within a tertiary hospital. Data collection occurred during baseline and intervention periods for 6 weeks each, with education and training conducted over a 4-week period prior to intervention. The e-checklist was used at baseline by ICU research nurses conducting post-ward round audits. During intervention, senior medical staff completed the e-checklist after patient assessments during the morning ward rounds, and research staff conducted post-ward round audits for validity testing (via concordance measurement). To examine changes in compliance over time, checklist-level data were analysed using generalised estimating equations that factored in confounding variables, and statistical process control charts were used to evaluate unit-level data. Established measures of concordance were used to evaluate e-checklist validity.ResultsCompliance with each care component improved significantly over time; the largest improvement was for pain management (42% increase; adjusted odds ratio = 23, p < 0.001), followed by glucose management (22% increase, p < 0.001) and head-of-bed elevation (19% increase, p < 0.001), both with odds ratios greater than 10. Most detected omissions were corrected by the following day. Control charts illustrated reduced variability in care compliance over time. There was good concordance between physician and auditor e-checklist responses; seven out of nine cares had kappa values above 0.8.ConclusionImprovements in the delivery of essential daily care processes were evidenced after the introduction of an e-checklist to the morning ward rounds in an ICU. High levels of agreement between physician and independent audit responses lend support to the validity of the e-checklist.Electronic supplementary materialThe online version of this article (doi:10.1186/s13613-015-0060-1) contains supplementary material, which is available to authorized users.

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“…In brief, the research studies included both clinical- and medical-related performance measures. Among them, the following were included: the presence or absence of specific adverse postoperative outcomes [ 34 ]; the rate of surgical site infections and 30-day mortality rates [ 35 ]; the infection rates of ventilator-associated pneumonia (VAP) [ 36 ]; the number of hospital-associated infections [ 37 , 38 ]; and inpatient death, intensive care stay, reoperation, and severe complications within 30 days after surgery [ 39 ]. …”

Section: Introductionmentioning

confidence: 99%

Using the Laney p’ Control Chart for Monitoring COVID-19 Cases in Jordan

Arafeh

2022

Journal of Healthcare Engineering

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In this research, we examine the use of the Laney p’ control chart and the application of test rules to assess governmental interventions throughout the COVID-19 pandemic and understand how certain activities and events that took place affected the infection rate. Data for the infection rate (IR) were collected between October 31, 2020, and March 19, 2022. The IR was calculated by dividing the number of confirmed cases by the number of PCR (polymerase chain reaction) tests performed. The IR data were subsequently plotted on the Laney p’ control charts using the Minitab software. The charts thereby allowed us to study the effects on infection rates of the government’s moves to restrict the movements and activities of the population, as well as the results of easing these restrictions. The restrictive measures proved to be effective in decreasing the infection rate, whereas relaxing these measures had the opposite effect. Typically, test signals are considered as an indication of a change in a process, although in some situations we have observed that slight changes are not accompanied by a signal. Regardless, the analysis shows cases where using test rules rapidly detected patterns and changes in IR, and allowing remedial action to be taken without delay. In this study, we use the Laney p’ control chart to monitor the COVID-19 IR and compare its performance with that of the EWMA control chart. In addition, we analyze the performance of various test rules in detecting IR changes. Comparing the Laney p’ control chart with the EWMA control chart, the data showed that in most cases, the Laney p’ control chart was able to identify the change of IR faster. Comparing the performance of different tests in detecting changes in the IR, one can see that no particular test outperformed the others in all cases. We also recommend analyzing the data points in both single-stage and multistage analyses in accordance with this new perspective rather than the traditional one used in process improvement projects. Accordingly, the single-stage analysis gives a complete picture of how the infection rate is changing overall, whereas the multistage analysis is more sensitive to small changes.

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Use of ventilator associated pneumonia bundle and statistical process control chart to decrease VAP rate in Syria

Cited by 20 publications

References 20 publications

Central Nervous System Depressants Poisoning and Ventilator Associated Pneumonia: An Underrated Risk Factor at the Toxicological Intensive Care Unit

Central Nervous System Depressants Poisoning and Ventilator Associated Pneumonia: An Underrated Risk Factor at the Toxicological Intensive Care Unit

Testing the implementation of an electronic process-of-care checklist for use during morning medical rounds in a tertiary intensive care unit: a prospective before–after study

Using the Laney p’ Control Chart for Monitoring COVID-19 Cases in Jordan

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