scholarly journals Factors Influencing CAM-ICU Documentation and Inappropriate “Unable to Assess” Responses

2021 ◽  
Vol 30 (6) ◽  
pp. e99-e107
Author(s):  
Omar M. Awan ◽  
Russell G. Buhr ◽  
Biren B. Kamdar
Keyword(s):  
Night Shift ◽  
Geographic Location ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Assessment Tools ◽  
Physical Restraints ◽  
Data Set ◽  
Delirium Assessment ◽  
Workplace Factors ◽  
Electronic Health

Background Detecting delirium with standardized assessment tools such as the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) is important, but such detection is frequently hampered by poor documentation and inappropriate “unable to assess” responses (in noncomatose patients). Objective To identify patient, clinical, and workplace factors that may impede or facilitate appropriate delirium assessment through use of the CAM-ICU, specifically documentation and inappropriate “unable to assess” responses. Methods An electronic health record–based data set was used to quantify CAM-ICU documentation and inappropriate “unable to assess” responses during 24 months. Associated patient (eg, age), clinical (eg, diagnosis), and workplace (eg, geographic location within the ICU, shift) factors were evaluated with multivariable regression. Results Of 28 586 CAM-ICU documentation opportunities, 66% were documented; 16% of documentations in alert or lightly sedated patients had inappropriate “unable to assess” responses. Night shift was associated with lower CAM-ICU documentation rates (P = .001), whereas physical restraints and location on side B (rather than side A) of the ICU were associated with higher documentation rates (P < .05 for both). Age older than 80 years, non-White race, intubation, and physical restraints were associated with more inappropriate “unable to assess” responses (all P < .05), as was infusion of propofol, midazolam, dexmedetomidine, or fentanyl (all P < .05). Conclusion Data from electronic health records can identify patient, clinical, and workplace factors associated with CAM-ICU documentation and inappropriate “unable to assess” responses, which can help target quality improvement efforts related to delirium assessment.

scholarly journals What delirium detection tools are used in routine clinical practice in the United Kingdom? Survey results from 91% of acute healthcare organisations

2021 ◽  
Author(s):  
Zoë Tieges ◽  
Jacqueline Lowrey ◽  
Alasdair M. J. MacLullich
Keyword(s):  
United Kingdom ◽  
Clinical Practice ◽  
Real World ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Assessment Tools ◽  
Clinical Population ◽  
Detection Methods ◽  
Delirium Assessment ◽  
The United Kingdom

Abstract Purpose Our aim was to collect information on delirium assessment processes and pathways in non-intensive care settings in the United Kingdom (UK). Methods We sent a Freedom of Information request to 169 UK National Health Service (NHS) hospitals, trusts and health boards (units) in July 2020 to obtain data on usage of delirium assessment tools in clinical practice and delirium pathways or guidelines. Results We received responses from 154/169 units (91% response rate). Of these, 146/154 (95%) units reported use of formal delirium assessment processes and 131/154 (85%) units had guidelines or pathways in place. The 4’A’s Test (4AT) was the most widely used tool, with 117/146 (80%) units reporting use. The Confusion Assessment Method was used in 65/146 (45%) units, and the Single Question to identify Delirium (SQiD) in 52/146 (36%) units. Conclusions Our findings show that the 4AT is the most commonly used tool in the UK, with 80% of units reporting use. This study adds to our knowledge of real-world uptake of delirium detection methods at scale. Future studies should evaluate real-world implementation of delirium assessment tools further via (1) tool completion rates and (2) rates of positive scores against the expected of prevalence delirium in the clinical population concerned.

scholarly journals What delirium detection tools are used in routine clinical practice in the UK? A Freedom of Information investigation of UK hospitals

2021 ◽  
Author(s):  
Zoë Tieges ◽  
Jacqueline Lowrey ◽  
Alasdair M. J. MacLullich
Keyword(s):  
Clinical Practice ◽  
Response Rate ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Assessment Tools ◽  
Detection Methods ◽  
Freedom Of Information ◽  
Delirium Assessment ◽  
Information Request ◽  
The Uk

ABSTRACTPurposeOur aim was to collect information on delirium assessment processes and pathways in non-intensive care settings in the UK.MethodsWe sent a Freedom of Information request to 169 UK NHS hospitals, trusts and health boards (units) in July 2020 to obtain data on usage of delirium assessment tools in clinical practice and delirium pathways or guidelines.ResultsWe received responses from 154 units (91% response rate). 146 (95%) units reported use of formal delirium assessment processes and 131 (85%) units had guidelines or pathways in place. The 4AT was the most widely used tool, with 117 (80%) units reporting use. The Confusion Assessment Method was used in 652 (45%) units, and the SQiD in 52 (36%) units.ConclusionsOur findings show that the 4AT is the most commonly-used tool in the UK, with 80% of units reporting implementation. This study adds to our knowledge of real-world implementation of delirium detection methods at scale.

Delirium in Critically Ill Patients

2017 ◽  
Author(s):  
Mark van den Boogaard ◽  
Paul Rood
Keyword(s):  
Intensive Care ◽  
Critically Ill ◽  
Hearing Aids ◽  
Critically Ill Patients ◽  
Early Mobilization ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Assessment Tools ◽  
Delirium Assessment ◽  
Nighttime Sleep

This chapter addresses delirium in critically ill patients in the intensive care unit (ICU), especially the mixed subtype (alternating hyperactivity and hypoactivity). The Confusion Assessment Method for the ICU and the Intensive Care Delirium Screening Checklist are discussed as useful delirium assessment tools in this setting. Several neurotransmitter pathways have been implicated in delirium, including cholinergic, GABAergic, and serotonergic pathways; cytokines and glucocorticoids also appear relevant. Risk factors for delirium in the ICU include older age, prior cognitive impairment, worse illness severity, recent delirium or coma, mechanical ventilation, admission category (especially trauma or neurological/neurosurgical admission), infection, metabolic acidosis, morphine and sedative administration, urea concentration, respiratory failure, and admission urgency. Prevention and treatment of delirium are discussed, including nonpharmacological interventions (frequent reorientation, providing eyeglasses and hearing aids if needed, promoting nighttime sleep, and early mobilization) and judicious use of opiate, sedative, and antipsychotic medications.

scholarly journals A Systematic Review and Pooled Prevalence of Paediatric Delirium in Critically Ill Children

2021 ◽  
Vol 29 (Supplement_1) ◽  
pp. i31-i32
Author(s):  
D Semple ◽  
M M Howlett ◽  
J D Strawbridge ◽  
C V Breatnach ◽  
J C Hayden
Keyword(s):  
Risk Factors ◽  
Critical Care ◽  
Critically Ill ◽  
Observational Studies ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Assessment Tools ◽  
Critically Ill Children ◽  
Confusion Assessment ◽  
Pooled Prevalence

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

Delirium classification by the diagnostic and statistical manual – a moving target

2015 ◽  
Vol 27 (6) ◽  
pp. 881-882 ◽  
Author(s):  
Karin J. Neufeld
Keyword(s):  
Rating Scale ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Classification Systems ◽  
Diagnostic Systems ◽  
Delirium Assessment ◽  
Diagnostic And Statistical Manual ◽  
Dsm 5 ◽  
Medical Inpatients ◽  
Dsm Iv

The following paper, entitled “A Comparison of Delirium Diagnosis in Elderly Medical Inpatients using the CAM, DRS-R98, DSM-IV and DSM-5 Criteria” by Adamis and colleagues, reports the results of a single delirium assessment of 200 medical inpatients, aged 70 years and older. The aim was to compare the prevalence of delirium using two different diagnostic classification systems (DSM-5 and DSM-IV) and two commonly used research tools (Confusion Assessment Method and the Delirium Rating Scale-Revised ‘98). This editorial focuses on the comparison of the two versions of the DSM. The authors conclude that, while both diagnostic systems identify a core concept of delirium, the DSM-IV criteria are the most inclusive of the four approaches and the DSM-5, the most restrictive, identifying a prevalence of 19.5% and 13%, respectively in this sample. Furthermore, they conclude that these two systems do not appear to detect the same patients: only 14 of 26 (54%) individuals identified as delirious by the more exclusive DSM-5 criteria were also identified as such by DSM-IV.

scholarly journals An educational strategy for the implementation of a delirium assessment tool

2021 ◽  
Vol 6 (1) ◽  
pp. 015-020
Author(s):  
Bonaga Beatriz ◽  
Taravilla Elena Ruiz-Escribano ◽  
Carrilero-López Carmen ◽  
Castillo-Lag María Dolores ◽  
Boehm Leanne M ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Health Care Professionals ◽  
Assessment Tool ◽  
Daily Practice ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Assessment Tools ◽  
Critically Ill Patient ◽  
Daily Routine

Background: Delirium is an acute syndrome of organ dysfunction with long-term consequences which commonly occurs in the Intensive Care Unit (ICU). The incidence of delirium ranges from 30% - 50% in low severity ICU patients and up to 80% in mechanically ventilated patients. This condition is frequently under-recognized and daily routine screening is a key strategy to early intervention. The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and the Intensive Care Delirium Screening Checklist (ICDSC) are the most recommended assessment tools for detecting delirium in the critical ill patient. Objective: The main objective of this study is to educate ICU staff about delirium. In addition, nurses were trained to use the CAM-ICU as a standard screening tool. The intervention was evaluated through a survey aimed at ICU staff. Methods: An educational intervention was started in 2014 in our ICU. An educational package for ICU staff consisted of a didactic brochure and explanatory videos. One-on-one teaching, case based scenarios and didactic teaching were strategies used in the implementation process. The entire intervention was evaluated by means of a survey directed to the professionals. Results: The structure of the didactic brochure was simple in order to have an easy understanding of the CAM-ICU tool. We also created 10-minute videos. According to the results of the satisfaction survey (N=62), disorganized thinking was the most difficult feature of CAM-ICU to interpret. When in doubt, consultation between co-workers was the primary resource selected by unit staff. Conclusion: This initiative achieved the objective of training health care professionals in the application of the CAM-ICU tool with a good level of satisfaction from them. Therefore, ICU staff consider delirium management in the broader picture of critically ill patient care as a major activity of daily practice.

Assessment of Delirium in the Intensive Care Unit: Nursing Practices And Perceptions

2008 ◽  
Vol 17 (6) ◽  
pp. 555-565 ◽  
Author(s):  
John W. Devlin ◽  
Jeffrey J. Fong ◽  
Elizabeth P. Howard ◽  
Yoanna Skrobik ◽  
Nina McCoy ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Intensive Care Units ◽  
Confusion Assessment Method ◽  
Assessment Method ◽  
Delirium Assessment ◽  
Web Based ◽  
Altered Level ◽  
Invasive Device ◽  
Few Data

Background Despite practice guidelines promoting delirium assessment in intensive care, few data exist regarding current delirium assessment practices among nurses and how these practices compare with those for sedation assessment. Objectives To identify current practices and perceptions of intensive care nurses regarding delirium assessment and to compare practices for assessing delirium with practices for assessing sedation. Methods A paper/Web-based survey was administered to 601 staff nurses working in 16 intensive care units at 5 acute care hospitals with sedation guidelines specifying delirium assessment in the Boston, Massachusetts area. Results Overall, 331 nurses (55%) responded. Only 3% ranked delirium as the most important condition to evaluate, compared with altered level of consciousness (44%), presence of pain (23%), or improper placement of an invasive device (21%). Delirium assessment was less common than sedation assessment (47% vs 98%, P < .001) and was more common among nurses who worked in medical intensive care units (55% vs 40%, P = .03) and at academic centers (53% vs 13%, P < .001). Preferred methods for assessing delirium included assessing ability to follow commands (78%), checking for agitation-related events (71%), the Confusion Assessment Method for the Intensive Care Unit (36%), the Intensive Care Delirium Screening Checklist (11%), and psychiatric consultation (9%). Barriers to assessment included intubation (38%), complexity of the tool for assessing delirium (34%), and sedation level (13%). Conclusions Practice and perceptions of delirium assessment vary widely among critical care nurses despite the presence of institutional sedation guidelines that promote delirium assessment.

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