title: Insurance impact on nonurgent and primary care-sensitive emergency department use.
abstract: OBJECTIVE
  To analyze the relationship between insurance and the likelihood of a nonurgent or primary care-sensitive (PCS) emergency department (ED) visit.
  
  
  METHODS
  Retrospective cohort study.
  
  
  METHODS
  The probabilities of nonurgent and PCS ED visits were derived on the basis of the New York University ED Classification Algorithm. We constructed a logit quasi-likelihood model to examine the insurance impact using 2008 Tennessee Hospital Outpatient Discharge Data.
  
  
  RESULTS
  Among a total of 2,177,955 ED visits in the analysis, uninsured status was significantly associated with the likelihood that an ED visit was nonurgent or PCS. These associations were different for men and women and across major racial groups. On average, uninsured status was associated with an increased probability of 0.038 of being nonurgent and 0.054 of being PCS, relative to private insurance status. The corresponding numbers for public insurance status were 0.060 and 0.075, respectively. For nonurgent or PCS probabilities that are not close to 0, higher nonurgent or PCS likelihoods corresponded to lower ED cost per visit to third-party insurers and patients.
  
  
  CONCLUSIONS
  Lack of insurance was associated with a higher probability of a nonurgent or PCS ED visit when compared with private insurance. When uninsured individuals gain coverage under the Affordable Care Act through either Medicaid expansion (public coverage) or insurance exchanges (private coverage), the average nonurgent or PCS probabilities could change either way given the opposite effects of public and private insurance coverage. If a lower nonurgent or PCS likelihood materialized, it could be associated with higher ED costs.
authors.affiliation: Florida International University, 11200 SW 8 St, Miami, FL 33199. E-mail: newweiwei@gmail.com.
authors.forename: Weiwei
authors.initials: W
authors.lastname: Chen
authors.forename: Teresa M
authors.initials: TM
authors.lastname: Waters
authors.forename: Cyril F
authors.initials: CF
authors.lastname: Chang
mesh_terms: D000328:Adult; D015331:Cohort Studies; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D007348:Insurance, Health / Q000706:statistics & numerical data; D008297:Male; D008484:Medicaid / Q000706:statistics & numerical data; D017057:Medically Uninsured / Q000706:statistics & numerical data; D006278:Medicare / Q000706:statistics & numerical data; D011320:Primary Health Care; D017149:Private Sector; D012189:Retrospective Studies; D014481:United States; D055815:Young Adult