Selected article for: "binary regression model and eastern Taiwan Kaoshiung city"

Author: Liu, Keh-Sen; Yu, Tsung-Fu; Wu, Hsing-Ju; Lin, Chun-Yi
Title: The impact of global budgeting in Taiwan on inpatients with unexplained fever
  • Document date: 2019_9_13
  • ID: 432t0q7w_32
    Snippet: A generalized linear binary regression model was used for analysis. GB did not have a significant impact on the risk of revisiting the ED within 3 days (OR = 0.58; P = .25). There was no significant correlation between age, gender, income state index or Charlson comorbidity index and the risk of revisiting the ED within 3 days (OR = 1.04, P = .06; OR = 1.28, P = .61; OR = 1.10, P = .50; OR = 0.43, P = .10, respectively). In addition, there were n.....
    Document: A generalized linear binary regression model was used for analysis. GB did not have a significant impact on the risk of revisiting the ED within 3 days (OR = 0.58; P = .25). There was no significant correlation between age, gender, income state index or Charlson comorbidity index and the risk of revisiting the ED within 3 days (OR = 1.04, P = .06; OR = 1.28, P = .61; OR = 1.10, P = .50; OR = 0.43, P = .10, respectively). In addition, there were no significant differences in the risk of revisiting the ED within 3 days between regional hospitals and medical centers or between local hospitals and medical centers (OR = 2.07, P = .20; OR = 3.02, P = .10, respectively). Compared with hospitals in Taipei city, there were no significant differences in the risk of revisiting the ED within 3 days among hospitals in northern Taiwan, central Taiwan, southern Taiwan, Kaoshiung city, or eastern Taiwan (OR = 0.18, P = .12; OR = 0.50, P = .31; OR = 0.56, P = .44; OR = 1.17, P = .82; OR = 1.21, P = .83, respectively) ( Table 6 ).

    Search related documents:
    Co phrase search for related documents
    • income state and local hospital: 1
    • income state and regional hospital: 1
    • income state and significant correlation: 1, 2, 3, 4
    • income state and significant difference: 1, 2
    • income state and significant impact: 1, 2
    • income state and Taipei city: 1, 2, 3, 4, 5, 6
    • income state index and Kaoshiung city: 1, 2, 3, 4, 5, 6
    • income state index and local hospital: 1
    • income state index and regional hospital: 1
    • income state index and significant correlation: 1, 2, 3, 4
    • income state index and significant difference: 1
    • income state index and significant impact: 1, 2
    • income state index and Taipei city: 1, 2, 3, 4, 5, 6
    • Kaoshiung city and local hospital: 1
    • Kaoshiung city and regional hospital: 1
    • Kaoshiung city and significant correlation: 1, 2, 3
    • Kaoshiung city and significant impact: 1
    • Kaoshiung city and Taipei city: 1, 2, 3, 4, 5, 6
    • local hospital and medical center: 1, 2, 3, 4, 5, 6, 7