Frailty Knowledge, Use of Screening Tools, and Educational Challenges in Emergency Departments in Ireland: A Multisite Survey.

BACKGROUND: Recognizing frailty and providing evidenced-based management in busy emergency departments is challenging. Understanding the knowledge and educational needs of ED staff is important to design training that might improve patient outcomes. OBJECTIVE: This study aimed to explore frailty knowledge of ED staff, use of frailty screening instruments in Irish emergency departments, and educational challenges in the emergency department. METHODS: A multisite survey of ED staff (different specialties) was conducted between April and September 2021. An anonymous online survey was distributed via email. Free-text sections were analyzed using content analysis. RESULTS: In total, 168 staff (nursing, medical and allied health) participated, representing 9 of 26 Irish emergency departments (35%). Most respondents were nurses (n = 78, 46%). Less than half of respondents had received frailty identification training (n = 81, 48%). One-fifth of emergency doctors and nurses (20%) were unsure how to define frailty. Major barriers to ED frailty screening were resource deficits, insufficient diagnostic pathways from the emergency departments, and lack of education on suitable instruments. CONCLUSIONS: Most of the ED staff surveyed relied on clinical judgment rather than formal training in frailty identification. A high proportion reported poor knowledge and low confidence in recognizing frailty. Dedicated staff with frailty management expertise, bespoke education initiatives, and clearly defined frailty screening pathways may help address the issues identified.

Diagnostic Accuracy of Frailty Screening Instruments Validated for Use among Older Adults Attending Emergency Departments: A Systematic Review and Meta-Analysis.

Early identification of frailty can prevent functional decline. Although multiple frailty screens exist for use in Emergency Departments (EDs), few are validated against diagnostic standards such as comprehensive geriatric assessment. To examine the diagnostic accuracy of ED screens for frailty, scientific databases were searched for prospective diagnostic accuracy test studies from January 2000 to September 2022. Studies were assessed for risk of bias using QUADAS-C. Psychometric properties were extracted and analysed using R. Six studies involving 1,663 participants describing seven frailty screening instruments (PRISMA-7, CFS, VIP, FRESH, BPQ, TRST, and ISAR), representing 13 unique data points, were included. The mean age of participants ranged from 76 to 86 years. The proportion that was female ranged from 45 to 60%. The pooled prevalence rate of frailty was high at 59%. The pooled estimate for sensitivity was 0.85 (95% CI: 0.76-0.91) versus 0.77 (95% CI: 0.62-0.88) for specificity. Pooled accuracy based on area under the ROC curve was 0.89 (95% CI: 0.86-0.90). Although few studies were found, limiting the ability to conduct a meta-analysis of individual instruments, available frailty screens can accurately diagnose frailty in older adults attending the ED. As specificity was comparatively low, additional assessment may be required to identify those requiring inpatient management or onward community referral. Further study is therefore required.

The Diagnostic Accuracy and Clinimetric Properties of Screening Instruments to Identify Frail Older Adults Attending Emergency Departments: A Protocol for a Mixed Methods Systematic Review and Meta-Analysis.

BACKGROUND: Prompt and efficient identification and stratification of patients who are frail is important, as this cohort are at high risk of adverse healthcare outcomes. Numerous frailty screening tools have been developed to support their identification across different settings, yet relatively few have emerged for use in emergency departments (EDs). This protocol provides details for a systematic review aiming to synthesize the accumulated evidence regarding the diagnostic accuracy and clinimetric properties of frailty screening instruments to identify frail older adults in EDs. METHODS: Six electronic databases will be searched from January 2000 to March 2021. Eligible studies will include adults aged ≥60 years screened in EDs with any available screening instrument to identify frailty (even if not originally designed for this purpose). Studies, including case-control, longitudinal, and cohort studies, will be included, where instruments are compared to a reference standard to explore diagnostic accuracy. Predictive accuracy for a selection of outcomes, including mortality, institutionalization, and readmission, will be assessed. Clinical and methodological heterogeneity will be examined, and a random effects meta-analysis performed if appropriate. CONCLUSION: Understanding whether frailty screening on presentation to EDs is accurate in identifying frailty, and predicting these outcomes is important for decision-making and targeting appropriate management.

Enhancing acute stroke services: a quality improvement project.

BACKGROUND: In a busy stroke centre in Ireland, care for acute stroke was provided by a mixture of general physicians. In acute ischaemic stroke, speed is essential for good outcomes. AIM: To improve acute stroke services and decrease door-to-needle (DTN) time to less than 60 min by December 2016 in patients with acute ischaemic stroke who are eligible for intravenous thrombolysis.Design: A quality improvement (QI) project was undertaken in a 438 bed, acute, university hospital. METHODS: Mixture of qualitative and quantitative data collected. A process map and driver diagram were created. Interventions tested with Plan-Do-Study-Act cycles. Times compared between July and December 2015, January and July 2016, July and December 2016, when a new stroke team and pathway were introduced. RESULTS: Between July and December 2015, the total number of ischaemic strokes was 216. 17 were thrombolysed (7.8%). Median door-to-CT (DTCT) time was 36 min (range 21-88). Median DTN time was 99 min (range 52-239). Between July and December 2016, there were 214 ischaemic strokes. 29 were thrombolysed (13.5%). 9 were seen directly by the stroke team during normal hours. With stroke team involvement, median DTCT time was 34 min (range 14-60) and DTN time was 43.5 min (range 24-65). CONCLUSIONS: This project led to a significant and sustained improvement in acute stroke care in our hospital with the use of quality improvement techniques. A comprehensive protocol, recurrent and ongoing staff education, and good communication helped to mitigate delays and further enhance care provided to patients presenting with stroke. The approach described may be valuable to the improvement of other services.'

Validation of a consensus method for identifying delirium from hospital records.

BACKGROUND: Delirium is increasingly considered to be an important determinant of trajectories of cognitive decline. Therefore, analyses of existing cohort studies measuring cognitive outcomes could benefit from methods to ascertain a retrospective delirium diagnosis. This study aimed to develop and validate such a method for delirium detection using routine medical records in UK and Ireland. METHODS: A point prevalence study of delirium provided the reference-standard ratings for delirium diagnosis. Blinded to study results, clinical vignettes were compiled from participants' medical records in a standardised manner, describing any relevant delirium symptoms recorded in the whole case record for the period leading up to case-ascertainment. An expert panel rated each vignette as unlikely, possible, or probable delirium and disagreements were resolved by consensus. RESULTS: From 95 case records, 424 vignettes were abstracted by 5 trained clinicians. There were 29 delirium cases according to the reference standard. Median age of subjects was 76.6 years (interquartile range 54.6 to 82.5). Against the original study DSM-IV diagnosis, the chart abstraction method gave a positive likelihood ratio (LR) of 7.8 (95% CI 5.7-12.0) and the negative LR of 0.45 (95% CI 0.40-0.47) for probable delirium (sensitivity 0.58 (95% CI 0.53-0.62); specificity 0.93 (95% CI 0.90-0.95); AUC 0.86 (95% CI 0.82-0.89)). The method diagnosed possible delirium with positive LR 3.5 (95% CI 2.9-4.3) and negative LR 0.15 (95% CI 0.11-0.21) (sensitivity 0.89 (95% CI 0.85-0.91); specificity 0.75 (95% CI 0.71-0.79); AUC 0.86 (95% CI 0.80-0.89)). CONCLUSIONS: This chart abstraction method can retrospectively diagnose delirium in hospitalised patients with good accuracy. This has potential for retrospectively identifying delirium in cohort studies where routine medical records are available. This example of record linkage between hospitalisations and epidemiological data may lead to further insights into the inter-relationship between acute illness, as an exposure, for a range of chronic health outcomes.

Analysis of compound weighing precision in drug discovery.

Early drug discovery laboratories often call for the precise weighing of 1- to 5-mg solids into 4- to 5-g glass vials. For the balance used in this study (Mettler Toledo XP205), the manufacturer rates its accuracy at ±0.01 mg over the working range of 1 mg to 220 g and its precision or repeatability at 0.015 mg for 10-g weights. The manufacturer ratings were confirmed using standard steel weights, but these calibrators do not well represent the weighing precision of drug compound. For example, when pre-taring a 4- to 5-g vial on the balance and then weighing 1- to 5-mg calibration weights, although no bias was observed, precision dropped appreciably. When measuring solid sample in the range of 1 to 5 mg, deviation of the measured weight from the actual (true) weight was even worse, in the range of ±20% to 50%. Balance settings and environmental factors exert a strong influence on weighing precision. Although most environmental factors, such as air draughts, temperature, vibrations, and levelness, can be optimized to the extent practical in laboratory settings, problems due to static electricity are often overlooked. By controlling static electricity, we demonstrate how we optimized the process to where measurements were within ±10% of actual weight when weighing solid sample in the range of 2 to 5 mg and ±20% when weighing 1 mg into a 4- to 5-g vial. Our weighing process and method to calculate actual weight are given in detail.