Emergency Department Visit Classification Using the NYU Algorithm.
Objectives: Reliable measures of emergency department (ED) use are important for studying ED utilization and access to care. We assessed the association of emergent classification of an ED visit based on the New York University ED Algorithm (EDA) with hospital mortality and hospital admission. Study...
| Publicado en: | American Journal of Managed Care Vol. 20; no. 4; pp. 315 - 321 |
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| Autores principales: | , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
MJH Life Sciences
Apr2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=95786699&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 95786699 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10880224 5QN jtl: American Journal of Managed Care issn: 10880224 maglogo: N pubinfo: dt: Apr2014 vid: 20 iid: 4 pid: 54670 pub: MJH Life Sciences place: Cranbury, New Jersey artinfo: ui: 95786699 95786699 103938430 95786699 ppf: 315 ppct: 6 formats: tig: atl: Emergency Department Visit Classification Using the NYU Algorithm. aug: au: Gandhi, Sabina Ohri Sabik, Lindsay affil: RTI International, Washington, DC sug: subj: Emergency Service Classification Human Surveys Logistic Regression Odds Ratio Confidence Intervals Descriptive Statistics United States Probability Sample P-Value Adult Middle Age Aged Male Female Mortality Evaluation Hospitalization Evaluation Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Male Female ab: Objectives: Reliable measures of emergency department (ED) use are important for studying ED utilization and access to care. We assessed the association of emergent classification of an ED visit based on the New York University ED Algorithm (EDA) with hospital mortality and hospital admission. Study Design: Using diagnosis codes, we applied the EDA to classify ED visits into emergent, intermediate, and nonemergent categories and studied associations of emergent status with hospital mortality and hospital admissions. Methods: We used a nationally representative sample of patients with visits to hospital-based EDs from repeated cross sections of the National Hospital Ambulatory Medical Care Survey from 2006 to 2009. We performed survey-weighted logistic regression analyses, adjusting for year and patient demographic and socioeconomic characteristics, to estimate the association of emergent ED visits with the probability of hospital mortality or hospital admission. Results: The EDA measure of emergent visits was significantly and positively associated with mortality (odds ratio [OR]: 3.79, 95% confidence interval [CI]: 2.50-5.75) and hospital admission (OR: 5.28, 95% CI, 4.93-5.66). Conclusions: This analysis assessed the NYU algorithm in measuring emergent and nonemergent ED use in the general population. Emergent classification based on the algorithm was strongly and significantly positively associated with hospitalization and death in a nationally representative population. The algorithm can be useful in studying ED utilization and evaluating policies that aim to change it. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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