Early outcomes following implementation of confusion assessment method (CAM)-ICU and a delirium management protocol to guide quality improvement

2015 ◽  
Vol 28 (1) ◽  
pp. 46
Author(s):  
J. Breeding ◽  
N. Baker ◽  
H. Buscher ◽  
C. Frost ◽  
N. Glenister ◽  
...  
BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S229-S229
Author(s):  
Nurul Yahya ◽  
Karim Saad

AimsBy way of Quality Improvement, this project aims to identify awareness levels, deliver a brief training and thus increasing the confidence of Memory Assessment Clinicians in detecting delirium.BackgroundPeople with dementia are at greater risk of delirium, and the acute confusion associated with delirium may be mistaken as part of their dementia. Despite having an estimated prevalence in care homes of 14.2% in the UK, delirium is under-recognised. Memory Assessment Clinicians may have low confidence in identifying and have low awareness of delirium despite being tasked with a triage and diagnostic role in dementia assessment. NICE has recently updated the guidelines on Delirium in March 2019 with recommendations on prevention and treatment of Delirium.MethodWe delivered a survey pertaining: (a)Awareness of Delirium NICE Guidelines(b)Confidence in spotting DeliriumWe used convenience sample of Memory Assessment Clinicians in Coventry. Overall, this survey was uptake by 17 clinicians. The pre training survey was done in early October 2019 and the post training survey was done shortly after the training, at the end of October 2019.A brief training comprising NICE Guidelines and using Confusion Assessment Method (CAM) was delivered. The survey is repeated post training and differences in result of level of confidence is done to measure changes. The survey assessed knowledge, beliefs, practices and confidence level regarding delirium detection.ResultPre training:17 clinicians took part in the survey. 59% was aware that there is a delirium NICE guidelines. 12% felt strongly agree, 41% agree and 47% felt neutral in their confidence of detecting delirium.Post training:10 clinicians took part in the survey. 50% felt strongly agree and 50% agree that they are confident in detecting delirium.Overall, the mean difference is 2 and the p value is 0.92034. we used Mann- Whitney Test to measure the difference in pre and post training which showed not significant at p < 0.05.Participants felt that the training was useful and relevant to practice.ConclusionThis study showed our clinicians have a good basic knowledge in detecting delirium. As a result of this study, we have created ‘Delirium checklist’ and Confusion Assessment Method (CAM) to be used during duty work. We also feel that the majority of delirium cases referred to us comes from the community base, thus our next step of the project will be to involve educational work with the community care home.


2020 ◽  
Vol 40 (4) ◽  
pp. 42-52
Author(s):  
Denise M. Kresevic ◽  
Donna Miller ◽  
Carole W. Fuseck ◽  
Mia Wade ◽  
Laura Whitney ◽  
...  

Background Delirium is a complex syndrome prevalent in the intensive care unit. It has been associated with significant morbidity including distress, longer hospital stays, prolonged cognitive impairment, and increased mortality. Objective To describe a nurse-led interdisciplinary quality improvement initiative to increase nurses’ knowledge of delirium, documentation of delirium assessment, and patient mobility. Methods Sixty-seven nurses in medical and surgical intensive care units were required to attend an interactive education program on delirium assessment and management. Scores on tests taken before and after the education program were used to evaluate knowledge. Medical records and bedside rounds were used to validate Confusion Assessment Method for the Intensive Care Unit documentation and interventions. Descriptive statistics were used to describe changes over time. A delirium resource team composed of nurses, physicians, and therapists provided didactic education paired with simulation training and bedside coaching. Mobility screening tests and computer templates guided assessments and interventions. Results Documentation of the Confusion Assessment Method improved from less than 50% to consistently 99%. Mobilization in the surgical intensive care unit increased from 90% to 98% after intervention. Days of delirium significantly decreased from 51% before intervention to 31% after intervention (χ12=7.01, P = .008). Conclusions The success of this quality improvement project to enhance recognition of delirium and increase mobility (critical components of the pain assessment, breathing, sedation choice, delirium, early mobility, and family education bundle) was contingent on nursing leaders hip, interdisciplinary team collaboration, and interactive education.


2020 ◽  
Vol 49 (4) ◽  
pp. 672-678 ◽  
Author(s):  
Emma Vardy ◽  
Niamh Collins ◽  
Umang Grover ◽  
Rebecca Thompson ◽  
Alexandra Bagnall ◽  
...  

Abstract Background delirium is a common condition associated with hospital admission. Detection and diagnosis is important to identify the underlying precipitating cause and implement effective management and treatment. Quality improvement (QI) methodology has been applied in limited publications. There are even fewer publications of the role of development of the electronic health record (EHR) to enhance implementation. Methods we used QI methodology to improve delirium detection in the emergency department (ED). Plan Do Study Act (PDSA) cycles could be broadly categorised into technology, training and education and leadership. As part of the technology PDSA an electronic delirium pathway was developed as part of an NHS England digital systems improvement initiative (NHS England Global Digital Exemplar). The electronic pathway incorporated the 4AT screening tool, the Confusion Assessment Method, the TIME delirium management bundle, investigation order sets and automated coding of delirium as a health issue. Results development of the EHR combined with education initiatives had benefit in terms of the number of people assessed for delirium on admission to the ED and the total number of people diagnosed with delirium across the organisation. The implementation of a delirium pathway as part of the EHR improved the use of 4AT in those 65 years and over from baseline of 3% completion in October 2017 to 43% in January 2018. Conclusion we showed that enhancement of the digital record can improve delirium assessment and diagnosis. Furthermore, the implementation of a delirium pathway is enhanced by staff education.


2007 ◽  
Vol 20 (2-3) ◽  
pp. 135-139
Author(s):  
B. Dittrich ◽  
G. Gatterer ◽  
T. Frühwald ◽  
U. Sommeregger

Zusammenfassung: Das Delir (“akuter Verwirrtheitszustand”) bezeichnet eine psychische Störung, die plötzlich auftritt, durch eine rasche Fluktuation von Bewusstseinslage und Aufmerksamkeitsleistung gekennzeichnet ist und eine organische Ursache hat. Dieses Störungsbild nimmt bei Patienten im höheren Lebensalter deutlich an Häufigkeit zu und verursacht durch verlängerte Krankenhausaufenthalte und ungünstige Krankheitsverläufe erhebliche Kosten im Gesundheitssystem. Daher erscheint eine möglichst frühe Erkennung deliranter Zustandsbilder gerade im Rahmen der Geriatrie von großer Bedeutung. Zu diesem Zweck wurde eine deutsche Version der international weit verbreiteten Confusion Assessment Method entwickelt, die für die Bedürfnisse einer Abteilung für Akutgeriatrie modifiziert wurde. Dargestellt werden die Entwicklung und erste Erfahrungen mit diesem Instrument.


2020 ◽  
Author(s):  
Dong-Liang Mu ◽  
Pan-Pan Ding ◽  
Shu-Zhe Zhou ◽  
Mei-Jing Liu ◽  
Xin-Yu Sun ◽  
...  

2021 ◽  
Vol 29 (Supplement_1) ◽  
pp. i31-i32
Author(s):  
D Semple ◽  
M M Howlett ◽  
J D Strawbridge ◽  
C V Breatnach ◽  
J C Hayden

Abstract Introduction Paediatric Delirium (PD) is a neuropsychiatric complication that occurs during the management of children in the critical care environment (Paediatric Intensive Care (PICU) and Neonatal Intensive Care (NICU). Delirium can be classified as hypoactive (decreased responsiveness and withdrawal), hyperactive (agitation and restlessness), and mixed (combined) (1). PD can be assessed using a number of assessment tools. PD has been historically underdiagnosed or misdiagnosed, having many overlapping symptoms with other syndrome such as pain and iatrogenic withdrawal syndrome (2). An appreciation of the extent of PD would help clinicians and policy makers drive interventions to improve recognition, prevention and management of PD in clinical practice. Aim To estimate the pooled prevalence of PD using validated assessment tools, and to identify risk factors including patient-related, critical-care related and pharmacological factors. Methods A systematic search of PubMed, EMBASE and CINAHL databases was undertaken. Eligible articles included observational studies or trials that estimated a prevalence of PD in a NICU/PICU population using a validated PD assessment tool. Validated tools are the paediatric Confusion Assessment Method-ICU (pCAM-ICU), the Cornell Assessment of Pediatric Delirium (CAPD), the PreSchool Confusion Assessment Method for the ICU (psCAM-ICU), pCAM-ICU severity scale (sspCAM-ICU), and the Sophia Observation Withdrawal Symptoms scale Paediatric Delirium scale (SOS-PD) (1). Only full text studies were included. No language restrictions were applied. Two reviewers independently screened records. Data was extracted using a pre-piloted form and independently verified by another reviewer. Quality was assessed using tools from the National Institutes of Health. A pooled prevalence was calculated from the studies that estimated PD prevalence using the most commonly applied tool, the CAPD (1). Results Data from 23 observational studies describing prevalence and risk factors for PD in critically ill children were included (Figure 1). Variability in study design and outcome reporting was found. Study quality was generally good. Using the validated tools prevalence ranged from 10–66% of patients. Hypoactive delirium was the most prevalent sub-class identified. Using the 13 studies that used the CAPD tool, a pooled prevalence of 35% (27%-43% 95%CI) was calculated. Younger ages, particularly less than two years old, sicker patients, particularly those undergoing mechanical and respiratory ventilatory support were more at risk for PD. Restraints, the number of sedative medications, including the cumulative use of benzodiazepines and opioids were identified as risk factors for the development of PD. PD was associated with longer durations of mechanical ventilation, longer stays and increased costs. Data on association with increased mortality risk is limited and conflicting. Conclusion PD affects one third of critical care admissions and is resource intense. Routine assessment in clinical practice may facilitate earlier detection and management strategies. Modifiable risk factors such as the class and number of sedative and analgesic medications used may contribute to the development of PD. Early mobility and lessening use of these medications present strategies to prevent PD occurrence. Longitudinal prospective multi-institutional studies to further investigate the presentations of the different delirium subtypes and modifiable risk factors that potentially contribute to the development of PD, are required. References 1. Semple D (2020) A systematic review and pooled prevalence of PD, including identification of the risk factors for the development of delirium in critically ill children. doi: 10.17605/OSF.IO/5KFZ8 2. Ista E, te Beest H, van Rosmalen J, de Hoog M, Tibboel D, van Beusekom B, et al. Sophia Observation withdrawal Symptoms-Paediatric Delirium scale: A tool for early screening of delirium in the PICU. Australian Critical Care. 2018;31(5):266–73


Author(s):  
Andrea Kirfel ◽  
Jan Menzenbach ◽  
Vera Guttenthaler ◽  
Johanna Feggeler ◽  
Andreas Mayr ◽  
...  

Abstract Background Postoperative delirium (POD) is a relevant and underdiagnosed complication after cardiac surgery that is associated with increased intensive care unit (ICU) and hospital length of stay (LOS). The aim of this subgroup study was to compare the frequency of tested POD versus the coded International Statistical Classification of Diseases and Related Health Problems (ICD) diagnosis of POD and to evaluate the influence of POD on LOS in ICU and hospital. Methods 254 elective cardiac surgery patients (mean age, 70.5 ± 6.4 years) at the University Hospital Bonn between September 2018 and October 2019 were evaluated. The endpoint tested POD was considered positive, if one of the tests Confusion Assessment Method for ICU (CAM-ICU) or Confusion Assessment Method (CAM), 4 'A's Test (4AT) or Delirium Observation Scale (DOS) was positive on one day. Results POD occurred in 127 patients (50.0%). LOS in ICU and hospital were significantly different based on presence (ICU 165.0 ± 362.7 h; Hospital 26.5 ± 26.1 days) or absence (ICU 64.5 ± 79.4 h; Hospital 14.6 ± 6.7 days) of POD (p < 0.001). The multiple linear regression showed POD as an independent predictor for a prolonged LOS in ICU (48%; 95%CI 31–67%) and in hospital (64%; 95%CI 27–110%) (p < 0.001). The frequency of POD in the study participants that was coded with the ICD F05.0 and F05.8 by hospital staff was considerably lower than tests revealed by the study personnel. Conclusion Approximately 50% of elderly patients who underwent cardiac surgery developed POD, which is associated with an increased ICU and hospital LOS. Furthermore, POD is highly underdiagnosed in clinical routine.


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