title: Barriers to obtaining diagnostic testing for coronary artery disease among veterans.
abstract: OBJECTIVE
  We sought to identify factors associated with appointment nonattendance for diagnostic testing of coronary artery disease among veterans. For patients with possible heart disease, appointment nonattendance may seriously compromise short- and long-term outcomes. Understanding factors associated with nonattendance may help improve care while reducing inefficiency in service delivery.
  
  
  METHODS
  We surveyed patients who attended (n = 240) or did not attend (n = 139) a scheduled cardiac appointment at a midwestern Veterans Administration medical center. Multivariable regression models were used to assess factors associated with nonattendance.
  
  
  RESULTS
  Younger age, lower income, unemployment, and longer wait times for appointments were predictive of nonattendance. Nonattenders reported fewer cardiac symptoms and were more likely to attribute their symptoms to something other than heart disease. Nonattendance was also associated with a coping style characterized by avoidance of aversive information. Logistical issues, fear of diagnostic procedures, disbelief that one had heart disease, and medical mistrust were some of the reasons given for missed appointments.
  
  
  CONCLUSIONS
  Appointment nonattendance among veterans scheduled for cardiology evaluation was associated with several important cognitive factors. These factors should be considered when one is designing clinical systems to reduce patient nonattendance.
authors.affiliation: Department of Social and Behavioral Health, Virginia Commonwealth University, Richmond, VA 23298, USA. lasiminoff@vcu.edu
authors.forename: Laura A
authors.initials: LA
authors.lastname: Siminoff
authors.forename: Leslie R M
authors.initials: LR
authors.lastname: Hausmann
authors.forename: Said
authors.initials: S
authors.lastname: Ibrahim
mesh_terms: D000223:Adaptation, Psychological; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001071:Appointments and Schedules; D001362:Avoidance Learning; D003324:Coronary Artery Disease / Q000175:diagnosis*; D005239:Fear; D005260:Female; D019538:Health Care Surveys; D006297:Health Services Accessibility / Q000458:organization & administration*; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008887:Military Medicine / Q000458:organization & administration*; D009042:Motivation; D015999:Multivariate Analysis; D010349:Patient Compliance / Q000523:psychology / Q000706:statistics & numerical data; D010414:Pennsylvania; D012959:Socioeconomic Factors; D011795:Surveys and Questionnaires; D013997:Time Factors; D014481:United States; D014493:United States Department of Veterans Affairs; D014728:Veterans / Q000523:psychology / Q000706:statistics & numerical data