Concordance in mSEGA Tool to Frailty Diagnosis between Medical Doctors and Nurses

Introduction: It is currently considered that screening for frailty in elderly subjects is a major public health issue. Methods: a cross-sectional pilot study involving elderly subjects (over 75 years of age) admitted at the emergency department of the hospital of Troyes, France in the period from August 24th to August 30th, 2017 was conducted. The patients were screened for frailty using the modified SEGA (Short Emergency Geriatric Assessment) (part A) grid (mSEGA), correlated with the subjective opinion of the triage nurse and the senior physician. Results: 100 patients were included during the pilot study period, the mean age was 84.34 years (range: 75–97), 56 patients (56%) were female, and the average CHARLSON score was 4.28 (range: 0–11). The patients’ previous medical histories were remarkable for cardiovascular diseases. The main reason for hospital admission was fall (26 subjects, 26%). Hospitalization was required for 52 subjects (52%). The average mSEGA score was 6.3 +/−3.59. The completion time for the SEGAm (part A) score was about 5 minutes. According to Cohen’s kappa, the concordance between the subjective opinion of the triage nurse and the mSEGA grid was average, while the concordance between the subjective opinions of the senior physicians was good. Conclusion: The mSEGA score appears to be well-suited and useful in the emergency department. It is easy to use, allows an overall evaluation of the patient, and is not time-consuming.

An analysis of individual and department triage variances to identify, quantify, and improve markers of triage nurse accuracy

An analysis of individual and department triage variances to identify, quantify, and improve markers of nurse triage accuracy. Rebecca Cotton, Richard Drew, Matthew Douma, Domhnall O’Dochartaigh, Candice Keddie, Karen Muncaster, Christopher Picard Background: Canadian Emergency Departments (ED) use the five-point Canadian Triage Acuity Scale (CTAS) to sort and prioritize patients according to acuity. CTAS scores are used to make decisions on patient flow, staffing complement, and funding. Despite this, there is a paucity of literature describing how CTAS data can be audited, and how the data can inform quality improvement/assurance (QI/QA). Implementation: Triage data downloaded from Tableau were analyzed using Microsoft Excel and IBM SPSS 26. Staff were informed of the audit using email and social media, and invited to discuss the results with educators and administrators. Staff identified for intervention were approached individually with the administrative plan. Anonymized versions of the work plan were posted on the departmental audit board. Nurses triaging greater than 50% department average were offered the option to triage less frequently, while nurses triaging less than 50% the department average were preferentially placed in triage. Nurses triaging fewer than 100 patients per year were informed they would be relieved of triage responsibility unless their rates increased above threshold. Nurses “down-triaging” patients at rates greater than 2 SD were informed that if their practice remained outside 2 SD at repeat audit they would be relieved of triage responsibility until they voluntarily completed CTAS refresher training. Nurses with average assigned CTAS scores > 2 SD department average had 20 visits randomly audited per month for error/appropriateness. Evaluation Method: Computer-assisted analysis of complete triage records was conducted for August 2019 to August 2020 at the Misericordia Hospital Emergency. Complete triage entries of every patient triaged by all triage trained nurses in the department were examined. Nurse’s with practice variation two deviations from department mean were identified and received additional detailed audits. Items examined for error were: FTE adjusted triage frequency; average CTAS score assigned; triage score manual override “down/up-triage” rate; proportion of absent Numeric Pain Scores (NPS) for patients with primary presenting complaints of pain; and vital signs modifier error rates. Initial department averages were used for benchmarking individual nurses; zone averages were used to benchmark department performance. Nurses were interviewed, audit results and action plans were posted. Repeat audits were performed on a three-month basis and benchmarked to initial measures, and a staff awareness campaign was enacted to improve NPS scoring. Data were extracted using text-parsing algorithms programmed into Microsoft Excel and analyzed using IBM SPSS 26. Data were normally distributed and descriptive statistics were calculated using means and standard deviations. T-testing was used for comparisons, and all testing was two-tailed with a pre-defined significance set at 0.05. Results: After the 3rd quarterly audit and associated interventions, global improvements were appreciated in triage nurse practice. There was a 68% reduction in the need for administrative action (n=51, n=18) with reduced variance in individual nurse triage rates and a 50% reduction in nurses who triaged >50% more patients than their peers. 50% fewer nurses had a mean triage rate >.02 above or below department average, there was an 86% reduction in high risk vital sign error rates, a 78% reduction in ”down-triage” rates, and a 6.5% improvement in documentation of numerical pain scores. Advice and Lessons Learned:1) Triage data analytics can rapidly identify staff with significant deviations from the average,making auditing and QI/QA activities more efficient and effective. 2) Having a concrete performance management framework and dissemination plan in place areessential for auditing to have a significant impact on triage consistency and quality over time. 3) Future QI/QA work should consider expanding computer-assisted text parsing to identifypatients at risk for mis-triage for reasons other than vital sign derangement, which will allowfor broader ED rollout across the Edmonton Zone and beyond.

Management of Systemic Sclerosis Patients in the COVID-19 Era: The Experience of an Expert Specialist Reference Center

Objective: COVID-19 pandemic represents a serious health emergency that severely compromised our Public Health system, resulting in a rapid and forced reorganization and involved the management of chronic diseases too. The Scleroderma Unit of Modena and Reggio Emilia follows more than 600 patients suffering from systemic sclerosis (SSc) and recently became the referral center (HUB) in Emilia-Romagna for this rare connective tissue disease. The aim of the present study was to evaluate the extent by which the lockdown and the pandemic has impacted the activity of admissions to Scleroderma Unit of Modena and Reggio Emilia. Methods: Our daily clinical activity is characterized by outpatient visits, videocapillaroscopy exam, ulcers treatment, therapeutic infusions in day hospital regimen, multidisciplinary visits following our dedicated SSc care pathway, and clinical trials. Our activity has been quickly rescheduled to ensure the proper assistance to our SSc patients during the COVID-19 pressure. Results: The use of telemedicine has certainly assured a robust continuity of health care. Furthermore, telephone pre-triage, nurse/medical triage, proper physical distancing and use of PPE/DPI allowed us to re-organize and continue SSc daily activity. Specifically, therapeutic infusions in day hospital regimen and outpatient visits, including ulcers treatment, was guaranteed and maximized. Conclusion: The management of scleroderma patients by an expert specialist reference center is crucial in order to ensure continuity of care and pursue the best SSc practice.

Agreement and predictive value of the Rockwood Clinical Frailty Scale at emergency department triage

AimTo determine the agreement and predictive value of emergency department (ED) triage nurse scoring of frailty using the Rockwood Clinical Frailty Scale (CFS) when compared with inpatient medical assessment using the same scale.MethodsProspective, dual-centre UK-based study over a 1-year period (1 April 2017 to 31 March 2018) of CFS recorded digitally at nursing triage on ED arrival and on hospital admission by a medical doctor. Inclusion criteria were emergency medical admission in those aged ≥65 staying at least one night in hospital with a CFS completed in both ED and at hospital admission. Agreement between ED triage nurse and inpatient hospital physician was assessed using a weighted Kappa statistic and Spearman’s correlation coefficient. The ability of the ED to diagnose frailty (defined by a CFS ≥5) was assessed using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and receiver operating characteristic (ROC) curves. At both time points the ability of the CFS to predict inpatient mortality was also assessed.ResultsFrom 29 211 admissions aged ≥65 who stayed at least one night in hospital, 12 385 (42.3%) were referred from the ED. Of the ED referrals, 8568 cases (69.2%) were included with paired CFS performed. Median age was 84 (IQR 77 to 89) with an inpatient mortality of 6%. Median CFS in ED was 4 (3 to 5) and on hospital admission 5 (4 to 6). Agreement between the ED CFS and admission CFS was weak (Kappa 0.21, 95% CI 0.19 to 0.22, rs 0.366). The area under the ROC curve (AUC) was 0.67 (95% CI 0.66 to 0.68) for the ED CFS ability to predict an admission CFS ≥5. To predict inpatient mortality the ED CFS AUC was 0.56 (0.53 to 0.59) and admission CFS AUC 0.70 (0.68 to 0.73).ConclusionAgreement between ED CFS and inpatient CFS was found to be weak. In addition the ability of ED CFS to predict clinically important outcomes was limited. NPV and PPV for ED CFS cut-off value of ≥5 were found to be low. Further work is required on the feasibility, clinical impact and appropriate tools for screening of frailty in EDs.

Optimization of the triage nurse's time by decreasing time spent on non-nursing functions.

293 Background: Triage nurses are an essential part of the multidisciplinary management of the oncology patient. Because of the nature of their role, they spend a significant amount of time performing non-nursing functions, resulting in a delay in patient care and decreased job satisfaction. This study will examine whether implementing a central phone triage system and commensurate process improvements in a large oncology practice will decrease the amount of time that the triage nurses spend on non-nursing functions. Methods: Nine triage nurses at our practice participated in a survey to obtain baseline data. The survey focused on data regarding the non-nursing issues that are encountered during the work day. We then developed a survey for the nurses to determine how much time per 8-hour work day, was spent on the identified non-nursing functions. A new telephone operator system was evaluated for suitability and then implemented. With the new system, the central operator answers all phone calls coming into the practice, and directs them to appropriate department via a messaging system, thus eliminating phone calls to the triage nurses’ direct extensions. Two months after the implementation of this new system, we recollected data to measure the time spent on the previously identified non-nursing functions. A job satisfaction survey was collected pre- and post-study. Results: The initial data collected showed that triage nurses spent approximately 60 minutes per day on non-nursing functions. These functions included the following: the amount of time listening to and taking off patient messages, pre-cert issues, order clarifications and social work issues. The data collected after implementing a new telephone system showed that this time dropped to approximately 12 minutes per day, a 78% reduction in non-nursing calls received by nurses. Additionally, there was a 7% increase in the triage nurse job satisfaction. Conclusions: After implementing a new telephone operator system, the nurses at this large oncology practice were able to better optimize their time taking care of patient related nursing functions. This improved their work flow, increased their time performing direct patient care related functions, and increased their overall job satisfaction. During this process, we also learned the importance of taking triage nurses input to improve their job function. Further research is recommended to better define the role of the phone triage nurse with the multidisciplinary care team of complex hematology/oncology patients.

Ability of triage nurses to predict, at the time of triage, the eventual disposition of patients attending the emergency department (ED): a systematic literature review and meta-analysis

IntroductionExit block is the most significant cause of poor patient flow and crowding in the emergency department (ED). One proposed strategy to reduce exit block is early admission predictions by triage nurses to allow proactive bed management. We report a systematic review and meta-analysis of the accuracy of nurse prediction of admission at triage.MethodologyWe searched MEDLINE, Cochrane, Embase, CINAHL and grey literature, up to and including February 2019. Our criteria were as follows: prospective studies analysing the accuracy of triage nurse intuition—after gathering standard triage information—for predicting disposition for adult ED patients. We analysed the results of this test—nurse prediction of disposition—in a diagnostic test analysis review style, assessing methodology with the Quality Assessment of Diagnostic Accuracy Studies 2 checklist. We generated sensitivity, specificity and likelihood ratios (LRs). We used LRs and pretest probability of admission (baseline admission rate) to find positive and negative post-test probabilities.ResultsWe reviewed 10 articles. Of these, seven had meta-analysable data (12 282 participants). The studies varied in participant selection and admission rate, but the majority were of moderate quality and exclusion of each in sensitivity analyses made little difference. Sensitivity was 72% and specificity was 83%. Pretest probability of admission was 29%. Positive and negative post-test probabilities of admission were 63% and 12%, respectively.ConclusionTriage nurse prediction of disposition is not accurate enough to expedite admission for ED patients on a one-to-one basis. Future research should explore the benefit, and best method, of predicting total demand.