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BackgroundThe impact of a pandemic on unplanned hospital attendance has not been extensively examined. The aim of this study is to report the nationwide consequences of the COVID-19 pandemic on unplanned hospital attendances in Denmark for 7 weeks after a ‘shelter at home’ order was issued.MethodsWe merged data from national registries (Civil Registration System and Patient Registry) to conduct a study of unplanned (excluding outpatient visits and elective surgery) hospital-based healthcare and mortality of all Danes. Using data for 7 weeks after the ‘shelter at home’ order, the incidence rate of unplanned hospital attendances per week in 2020 was compared with corresponding weeks in 2017–2019. The main outcome was hospital attendances per week as incidence rate ratios. Secondary outcomes were general population mortality and risk of death in-hospital, reported as weekly mortality rate ratios (MRRs).ResultsFrom 2 438 286 attendances in the study period, overall unplanned attendances decreased by up to 21%; attendances excluding COVID-19 were reduced by 31%; non-psychiatric by 31% and psychiatric by 30%. Out of the five most common diagnoses expected to remain stable, only schizophrenia and myocardial infarction remained stable, while chronic obstructive pulmonary disease exacerbation, hip fracture and urinary tract infection fell significantly. The nationwide general population MRR rose in six of the recorded weeks, while MRR excluding patients who were COVID-19 positive only increased in two.ConclusionThe COVID-19 pandemic and a governmental national ‘shelter at home’ order was associated with a marked reduction in unplanned hospital attendances with an increase in MRR for the general population in two of 7 weeks, despite exclusion of patients with COVID-19. The findings should be taken into consideration when planning for public information campaigns.

Purpose Abstract To determine the validity of the Australian clinical prediction tool Criteria for Screening and Triaging to Appropriate aLternative care (CRISTAL) based on objective clinical criteria to accurately identify risk of death within 3 months of admission among older patients. Methods Prospective study of ≥ 65 year-olds presenting at emergency departments in five Australian (Aus) and four Danish (DK) hospitals. Logistic regression analysis was used to model factors for death prediction; Sensitivity, specificity, area under the ROC curve and calibration with bootstrapping techniques were used to describe predictive accuracy. Results 2493 patients, with median age 78–80 years (DK–Aus). The deceased had significantly higher mean CriSTAL with Australian mean of 8.1 (95% CI 7.7–8.6 vs. 5.8 95% CI 5.6–5.9) and Danish mean 7.1 (95% CI 6.6–7.5 vs. 5.5 95% CI 5.4–5.6). The model with Fried Frailty score was optimal for the Australian cohort but prediction with the Clinical Frailty Scale (CFS) was also good (AUROC 0.825 and 0.81, respectively). Values for the Danish cohort were AUROC 0.764 with Fried and 0.794 using CFS. The most significant independent predictors of short-term death in both cohorts were advanced malignancy, frailty, male gender and advanced age. CriSTAL’s accuracy was only modest for in-hospital death prediction in either setting. Conclusions The modified CriSTAL tool (with CFS instead of Fried’s frailty instrument) has good discriminant power to improve prognostic certainty of short-term mortality for ED physicians in both health systems. This shows promise in enhancing clinician’s confidence in initiating earlier end-of-life discussions. Electronic supplementary material The online version of this article (10.1007/s41999-018-0123-6) contains supplementary material, which is available to authorized users.

BACKGROUND: Prognostic uncertainty inhibits clinicians from initiating timely end-of-life discussions and advance care planning. This study evaluates the efficacy of the CriSTAL (Criteria for Screening and Triaging to Appropriate aLternative care) checklist in emergency departments.METHODS: Prospective cohort study of patients aged ≥65 years with any diagnosis admitted via emergency departments in ten hospitals in Australia, Denmark and Ireland. Electronic and paper clinical records will be used to extract risk factors such as nursing home residency, physiological deterioration warranting a rapid response call, personal history of active chronic disease, history of hospitalisations or intensive care unit admission in the past year, evidence of proteinuria or ECG abnormalities, and evidence of frailty to be concurrently measured with Fried Score and Clinical Frailty Scale. Patients or their informal caregivers will be contacted by telephone around three months after initial assessment to ascertain survival, self-reported health, post-discharge frailty and health service utilisation since discharge. Logistic regression and bootstrapping techniques and AUROC curves will be used to test the predictive accuracy of CriSTAL for death within 90 days of admission and in-hospital death.DISCUSSION: The CriSTAL checklist is an objective and practical tool for use in emergency departments among older patients to determine individual probability of death in the short-term. Its validation in this cohort is expected to reduce clinicians' prognostic uncertainty on the time to patients' death and encourage timely end-of-life conversations to support clinical decisions with older frail patients and their families about their imminent or future care choices.

Frailty is associated with longer length of stay and adverse outcomes in elderly hospitalized patients, including early re-hospitalization and 12-month mortality. Identifying these risk levels on presentation at emergency departments is crucial to deliver family education, plan care, arrange referrals, and anticipate complications. Many instruments are available covering objective and subjective parameters. Our multi-center cohort study of 2,749 elderly patients in Australia, Denmark and Ireland used Fried’s, Rockwood’s, SUHB’s and Rylance’s frailty scores to predict outcomes at hospital discharge and 3-months. The exacerbation of chronic illness, poor recall, different timeframes for the estimates before presentation, absence of an informant for incompetent patients, organizational limitations and stresses of the emergency environment, and hospital policies about stretcher use on transfer impacted on our ability to reliably measure some of the parameters. Analysis showed substantial inconsistencies in the classification into pre-frail, frail or robust by different instruments on admission. Telephone administration of the frailty instruments at follow-up yielded incomplete or inexact scores due to reliance on self-report or proxy-report rather than direct observation. We concluded that doctors would have limited time to accurately assess all objective parameters during routine care. Emergency/aged care nurses and physiotherapists are best placed to conduct these measurements given their familiarity with the frailty components, training in recognizing physical abilities of patients, ongoing opportunity at the bedside, frequent visual assessment, and communication with patients/ caregivers. Fried’s and Rylance’s instruments were affected by many practical limitations. Telephone assessment on follow-up is not recommended to document decline or improvement over time.