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      Comparing Statewide and Single‐center Data to Predict High‐frequency Emergency Department Utilization Among Patients With Asthma Exacerbation

      한글로보기

      https://www.riss.kr/link?id=O120329872

      • 저자
      • 발행기관
      • 학술지명
      • 권호사항
      • 발행연도

        2018년

      • 작성언어

        -

      • Print ISSN

        1069-6563

      • Online ISSN

        1553-2712

      • 등재정보

        SCI;SCIE;SCOPUS

      • 자료형태

        학술저널

      • 수록면

        657-667   [※수록면이 p5 이하이면, Review, Columns, Editor's Note, Abstract 등일 경우가 있습니다.]

      • 구독기관
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      다국어 초록 (Multilingual Abstract)

      Previous studies examining high‐frequency emergency department (ED) utilization have primarily used single‐center data, potentially leading to ascertainment bias if patients visit multiple centers. The goals of this study were 1) to create a predi...

      Previous studies examining high‐frequency emergency department (ED) utilization have primarily used single‐center data, potentially leading to ascertainment bias if patients visit multiple centers. The goals of this study were 1) to create a predictive model to prospectively identify patients at risk of high‐frequency ED utilization for asthma and 2) to examine how that model differed using statewide versus single‐center data.
      To track ED visits within a state, we analyzed 2011 to 2013 data from the New York State Healthcare Cost and Utilization Project State Emergency Department Databases. The first year of data (2011) was used to determine prior utilization, 2012 was used to identify index ED visits for asthma and for demographics, and 2013 was used for outcome ascertainment. High‐frequency utilization was defined as 4+ ED visits for asthma within 1 year after the index visit. We performed analyses separately for children (age < 21 years) and adults and constructed two models: one included all statewide (multicenter) visits and the other was restricted to index hospital (single‐center) visits. Multivariable logistic regression models were developed from potential predictors selected a priori. The final model was chosen by evaluating model performance using Akaike's Information Criterion scores, 10‐fold cross‐validation, and receiver operating characteristic curves.
      Among children, high‐frequency ED utilization for asthma was observed in 2,417 of 94,258 (2.56%) using all statewide visits, compared to 1,853 of 94,258 (1.97%) for index hospital visits only. Among adults, the corresponding results were 7,779 of 159,874 (4.87%) and 5,053 of 159,874 (3.16%), respectively. In the multicenter visit model, the area under the curve (AUC) from 10‐fold cross‐validation for children was 0.70 (95% confidence interval [CI] = 0.69–0.72), compared to 0.71 (95% CI = 0.69–0.72) in the single‐center visit model. The corresponding AUC results for adults were 0.76 (95% CI = 0.76–0.77) and 0.76 (95% CI = 0.75–0.77), respectively.
      Data available at the index ED visit can predict subsequent high‐frequency utilization for asthma with AUC ranging from 0.70 to 0.76. Model accuracy was similar regardless of whether outcome ascertainment included all statewide visits (multicenter) or was limited to the index hospital (single‐center).

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