Predictive value of initial triage vital signs for critically ill older adults.

INTRODUCTION: Triage of patients is critical to patient safety, yet no clear information exists as to the utility of initial vital signs in identifying critically ill older emergency department (ED) patients. The objective of this study is to evaluate a set of initial vital sign thresholds as predictors of severe illness and injury among older adults presenting to the ED. METHODS: We reviewed all visits by patients aged 75 and older seen during 2007 at an academic ED serving a large community of older adults. Patients' charts were abstracted for demographic and clinical information including vital signs, via automated electronic methods. We used bivariate analysis to investigate the relationship between vital sign abnormalities and severe illness or injury, defined as intensive care unit (ICU) admission or ED death. In addition, we calculated likelihood ratios for normal and abnormal vital signs in predicting severe illness or injury. RESULTS: 4,873 visits by patients aged 75 and above were made to the ED during 2007, and of these 3,848 had a complete set of triage vital signs. For these elderly patients, the sensitivity and specificity of an abnormal vital sign taken at triage for predicting death or admission to an ICU were 73% (66,81) and 50% (48,52) respectively (positive likelihood ratio 1.47 (1.30,1.60); negative likelihood ratio 0.54 (0.30,0.60). CONCLUSION: Emergency provider assessment and triage scores that rely primarily on initial vital signs are likely to miss a substantial portion of critically ill older adults.

Computer-facilitated review of electronic medical records reliably identifies emergency department interventions in older adults.

OBJECTIVES: An estimated 14% to 25% of all scientific studies in peer-reviewed emergency medicine (EM) journals are medical records reviews. The majority of the chart reviews in these studies are performed manually, a process that is both time-consuming and error-prone. Computer-based text search engines have the potential to enhance chart reviews of electronic emergency department (ED) medical records. The authors compared the efficiency and accuracy of a computer-facilitated medical record review of ED clinical records of geriatric patients with a traditional manual review of the same data and describe the process by which this computer-facilitated review was completed. METHODS: Clinical data from consecutive ED patients age 65 years or older were collected retrospectively by manual and computer-facilitated medical record review. The frequency of three significant ED interventions in older adults was determined using each method. Performance characteristics of each search method, including sensitivity and positive predictive value, were determined, and the overall sensitivities of the two search methods were compared using McNemar's test. RESULTS: For 665 patient visits, there were 49 (7.4%) Foley catheters placed, 36 (5.4%) sedative medications administered, and 15 (2.3%) patients who received positive pressure ventilation. The computer-facilitated review identified more of the targeted procedures (99 of 100, 99%), compared to manual review (74 of 100 procedures, 74%; p < 0.0001). CONCLUSIONS: A practical, non-resource-intensive, computer-facilitated free-text medical record review was completed and was more efficient and accurate than manually reviewing ED records.

Predicting hospital admission and returns to the emergency department for elderly patients.

OBJECTIVES: Methods to accurately identify elderly patients with a high likelihood of hospital admission or subsequent return to the emergency department (ED) might facilitate the development of interventions to expedite the admission process, improve patient care, and reduce overcrowding. This study sought to identify variables found among elderly ED patients that could predict either hospital admission or return to the ED. METHODS: All visits by patients 75 years of age or older during 2007 at an academic ED serving a large community of elderly were reviewed. Clinical and demographic data were used to construct regression models to predict admission or ED return. These models were then validated in a second group of patients 75 and older who presented during two 1-month periods in 2008. RESULTS: Of 4,873 visits, 3,188 resulted in admission (65.4%). Regression modeling identified five variables statistically related to the probability of admission: age, triage score, heart rate, diastolic blood pressure, and chief complaint. Upon validation, the c-statistic of the receiver operating characteristic (ROC) curve was 0.73, moderately predictive of admission. We were unable to produce models that predicted ED return for these elderly patients. CONCLUSIONS: A derived and validated triage-based model is presented that provides a moderately accurate probability of hospital admission of elderly patients. If validated experimentally, this model might expedite the admission process for elderly ED patients. Our models failed, as have others, to accurately predict ED return among elderly patients, underscoring the challenge of identifying those individuals at risk for early ED returns.