6 resultados para Emergency Department services
em Duke University
Resumo:
BACKGROUND: Child maltreatment is underreported in the United States and in North Carolina. In North Carolina and other states, mandatory reporting laws require various professionals to make reports, thereby helping to reduce underreporting of child maltreatment. This study aims to understand why emergency medical services (EMS) professionals may fail to report suspicions of maltreatment despite mandatory reporting policies. METHODS: A web-based, anonymous, voluntary survey of EMS professionals in North Carolina was used to assess knowledge of their agency's written protocols and potential reasons for underreporting suspicion of maltreatment (n=444). Results were based on descriptive statistics. Responses of line staff and leadership personnel were compared using chi-square analysis. RESULTS: Thirty-eight percent of respondents were unaware of their agency's written protocols regarding reporting of child maltreatment. Additionally, 25% of EMS professionals who knew of their agency's protocol incorrectly believed that the report should be filed by someone other than the person with firsthand knowledge of the suspected maltreatment. Leadership personnel generally understood reporting requirements better than did line staff. Respondents indicated that peers may fail to report maltreatment for several reasons: they believe another authority would file the report, including the hospital (52.3%) or law enforcement (27.7%); they are uncertain whether they had witnessed abuse (47.7%); and they are uncertain about what should be reported (41.4%). LIMITATIONS: This survey may not generalize to all EMS professionals in North Carolina. CONCLUSIONS: Training opportunities for EMS professionals that address proper identification and reporting of child maltreatment, as well as cross-agency information sharing, are warranted.
Resumo:
Precision medicine is an emerging approach to disease treatment and prevention that considers variability in patient genes, environment, and lifestyle. However, little has been written about how such research impacts emergency care. Recent advances in analytical techniques have made it possible to characterize patients in a more comprehensive and sophisticated fashion at the molecular level, promising highly individualized diagnosis and treatment. Among these techniques are various systematic molecular phenotyping analyses (e.g., genomics, transcriptomics, proteomics, and metabolomics). Although a number of emergency physicians use such techniques in their research, widespread discussion of these approaches has been lacking in the emergency care literature and many emergency physicians may be unfamiliar with them. In this article, we briefly review the underpinnings of such studies, note how they already impact acute care, discuss areas in which they might soon be applied, and identify challenges in translation to the emergency department (ED). While such techniques hold much promise, it is unclear whether the obstacles to translating their findings to the ED will be overcome in the near future. Such obstacles include validation, cost, turnaround time, user interface, decision support, standardization, and adoption by end-users.
Resumo:
BACKGROUND: It is unclear whether diagnostic protocols based on cardiac markers to identify low-risk chest pain patients suitable for early release from the emergency department can be applied to patients older than 65 years or with traditional cardiac risk factors. METHODS AND RESULTS: In a single-center retrospective study of 231 consecutive patients with high-risk factor burden in which a first cardiac troponin (cTn) level was measured in the emergency department and a second cTn sample was drawn 4 to 14 hours later, we compared the performance of a modified 2-Hour Accelerated Diagnostic Protocol to Assess Patients with Chest Pain Using Contemporary Troponins as the Only Biomarker (ADAPT) rule to a new risk classification scheme that identifies patients as low risk if they have no known coronary artery disease, a nonischemic electrocardiogram, and 2 cTn levels below the assay's limit of detection. Demographic and outcome data were abstracted through chart review. The median age of our population was 64 years, and 75% had Thrombosis In Myocardial Infarction risk score ≥2. Using our risk classification rule, 53 (23%) patients were low risk with a negative predictive value for 30-day cardiac events of 98%. Applying a modified ADAPT rule to our cohort, 18 (8%) patients were identified as low risk with a negative predictive value of 100%. In a sensitivity analysis, the negative predictive value of our risk algorithm did not change when we relied only on undetectable baseline cTn and eliminated the second cTn assessment. CONCLUSIONS: If confirmed in prospective studies, this less-restrictive risk classification strategy could be used to safely identify chest pain patients with more traditional cardiac risk factors for early emergency department release.
Resumo:
OBJECTIVE: The Thrombolysis in Myocardial Infarction (TIMI) score is a validated tool for risk stratification of acute coronary syndrome. We hypothesized that the TIMI risk score would be able to risk stratify patients in observation unit for acute coronary syndrome. METHODS: STUDY DESIGN: Retrospective cohort study of consecutive adult patients placed in an urban academic hospital emergency department observation unit with an average annual census of 65,000 between 2004 and 2007. Exclusion criteria included elevated initial cardiac biomarkers, ST segment changes on ECG, unstable vital signs, or unstable arrhythmias. A composite of significant coronary artery disease (CAD) indicators, including diagnosis of myocardial infarction, percutaneous coronary intervention, coronary artery bypass surgery, or death within 30 days and 1 year, were abstracted via chart review and financial record query. The entire cohort was stratified by TIMI risk scores (0-7) and composite event rates with 95% confidence interval were calculated. RESULTS: In total 2228 patients were analyzed. Average age was 54.5 years, 42.0% were male. The overall median TIMI risk score was 1. Eighty (3.6%) patients had 30-day and 119 (5.3%) had 1-year CAD indicators. There was a trend toward increasing rate of composite CAD indicators at 30 days and 1 year with increasing TIMI score, ranging from a 1.2% event rate at 30 days and 1.9% at 1 year for TIMI score of 0 and 12.5% at 30 days and 21.4% at 1 year for TIMI ≥ 4. CONCLUSIONS: In an observation unit cohort, the TIMI risk score is able to risk stratify patients into low-, moderate-, and high-risk groups.