RESUMEN
INTRODUCTION: Emergency department (ED) crowding has significant adverse consequences, however, there is no widely accepted tool to measure it. This study validated the National Emergency Department Overcrowding score (NEDOCS) (range 0-200 points), which uses routinely collected ED data. METHODS: This prospective single-centre study sampled data during four periods of 2018. The outcome against which NEDOCS performance was assessed was a composite of clinician opinion of crowding (physician and nurse in charge). Area under the receiver operating characteristic curves (AUROCs) and calibration plots were produced. Six-hour stratified sampling was added to adjust for temporal correlation of clinician opinion. Staff inter-rater agreement and NEDOCS association with opinion of risk, safety and staffing levels were collected. RESULTS: From 905 sampled hours, 448 paired observations were obtained, with the ED deemed crowded 18.5% of the time. Inter-rater agreement between staff was moderate (weighted kappa 0.57 (95% CI 0.56 to 0.60)). AUROC for NEDOCS was 0.81 (95% CI 0.77 to 0.86). Adjusted for temporal correlation, AUROC was 0.80 (95% CI 0.73 to 0.88). At a cut-off of 100 points sensitivity was 75.9% (95% CI 65.3% to 84.6%), specificity 72.1% (95% CI 67.1% to 76.6%), positive predictive value 38.2% (95% CI 30.7% to 46.1%) and negative predictive value 92.9% (95% CI 89.3% to 95.6%). NEDOCS underpredicted clinical opinion on Calibration assessment, only partially correcting with intercept updating. For perceived risk of harm, safety and insufficient staffing, NEDOCS AUROCs were 0.71 (95% CI 0.61 to 0.82), 0.71 (95% CI 0.63 to 0.80) and 0.70 (95% CI 0.64 to 0.76), respectively. CONCLUSIONS: NEDOCS demonstrated good discriminatory power for clinical perception of crowding. Prior to implementation, determining individual unit ED cut-off point(s) would be important as published thresholds may not be generalisable. Future studies could explore refinement of existing variables or addition of new variables, including acute physiological data, which may improve performance.
Asunto(s)
Actitud del Personal de Salud , Aglomeración , Servicio de Urgencia en Hospital/organización & administración , Evaluación de Procesos, Atención de Salud , Humanos , Estudios Prospectivos , Reino UnidoRESUMEN
INTRODUCTION: Hip fractures are associated with significant morbidity and mortality in older people. Accurate risk stratification is important for planning of care, informed decision-making and communication with patients and relatives. The Older Persons' Emergency Risk Assessment (OPERA) score is a risk stratification score for older people admitted to hospital. Our aims were to validate OPERA in hip fracture patients, update the score and compare performance with the Nottingham Hip Fracture Score (NHFS). METHODS: This dual-centre 3-year observational study (2016-2018) included acutely admitted hip fracture patients managed surgically aged ⩾65 years. The primary outcome was 30-day mortality. Secondary outcomes included residence at 120 days and 1-year mortality. Model performance was assessed using area under the curve (AUC) analysis and Brier scores (discrimination) and calibration curves. The OPERA score was updated using regression analysis with additional independent predictors and validated using bootstrap analysis. RESULTS: 2142 patients (median age 86 [80-91] years) were included with a 30-day mortality of 5.2% and a 1-year mortality of 31.4%. 30-day mortality AUC for OPERA was 0.75 (95% CI, 0.73-0.77) and for NHFS 0.68 (0.65-0.70). For 1-year mortality AUC for OPERA was 0.74 (0.73-0.75) and for NHFS 0.70 (0.69-0.71). The OPERA Score was updated to Hip-OPERA, including ASA grade. Hip-OPERA demonstrated an AUC for 30-day mortality of 0.77 (0.73-0.81) and an AUC for 1-year mortality of 0.76 (0.75-0.77). AUC for new residential care status at 120 days was 0.79 (0.78-0.80). CONCLUSIONS: Hip-OPERA demonstrated superior discrimination to the NHFS and OPERA for 30-day mortality, 1-year mortality and residence at 120 days following hip fracture. External validation is desirable.
Asunto(s)
Artroplastia de Reemplazo de Cadera , Fracturas de Cadera , Humanos , Anciano , Anciano de 80 o más Años , Fracturas de Cadera/diagnóstico , Fracturas de Cadera/cirugía , Medición de Riesgo , Factores de Riesgo , Morbilidad , Mortalidad Hospitalaria , Estudios RetrospectivosRESUMEN
OBJECTIVES OF THE STUDY: Demographic changes alongside medical advances have resulted in older adults accounting for an increasing proportion of emergency hospital admissions. Current measures of illness severity, limited to physiological parameters, have shortcomings in this cohort, partly due to patient complexity. This study aimed to derive and validate a risk score for acutely unwell older adults which may enhance risk stratification and support clinical decision-making. METHODS: Data was collected from emergency admissions in patients ≥65 years from two UK general hospitals (April 2017- April 2018). Variables underwent regression analysis for in-hospital mortality and independent predictors were used to create a risk score. Performance was assessed on external validation. Secondary outcomes included seven-day mortality and extended hospital stay. RESULTS: Derivation (n = 8,974) and validation (n = 8,391) cohorts were analysed. The model included the National Early Warning Score 2 (NEWS2), clinical frailty scale (CFS), acute kidney injury, age, sex, and Malnutrition Universal Screening Tool. For mortality, area under the curve for the model was 0.79 (95% CI 0.78-0.80), superior to NEWS2 0.65 (0.62-0.67) and CFS 0.76 (0.74-0.77) (P<0.0001). Risk groups predicted prolonged hospital stay: the highest risk group had an odds ratio of 9.7 (5.8-16.1) to stay >30 days. CONCLUSIONS: Our simple validated model (Older Persons' Emergency Risk Assessment [OPERA] score) predicts in-hospital mortality and prolonged length of stay and could be easily integrated into electronic hospital systems, enabling automatic digital generation of risk stratification within hours of admission. Future studies may validate the OPERA score in external populations and consider an impact analysis.