title: Predictors of $4 generic prescription drug discount programs use in the low-income population.
abstract: BACKGROUND
  Generic drug discount programs (GDDPs) are an option to provide affordable prescription medication to low-income individuals. However, the factors that influence the use of GDDPs in low-income population are unknown.
  
  
  OBJECTIVE
  To evaluate factors associated with utilization of generic a drug discount program in a low-income population.
  
  
  METHODS
  A survey was administered to adult participants at health centers and community-based organizations in Houston, Texas, USA (n = 525). Exploratory factor analysis was conducted to determine the construct validity of the survey instrument and to assess distinct factors associated with GDDP utilization. Descriptive statistics were used to summarize the distribution of patient socio-demographic characteristics and questionnaire responses. Multivariate logistic regression was used to compute adjusted odds ratios and to examine the strength of association with GDDP utilization after adjusting for participant socio-demographic features that were statistically significant at a priori level of P < 0.05.
  
  
  RESULTS
  In this study, 72% of respondents were aware of the GDDP, and 61% had utilized the GDDP. Participants were 4 times likely to use a GDDP when their physician (AOR: 4.0, 95% CI: 2.6-6.4, P < 0.001) or pharmacist (AOR: 4.0, 95% CI: 2.6-6.3, P < 0.001) talked to them about it. Participants indicated that the most important barriers to utilization of GDDPs were lack of awareness (44%), and lack of recommendation by a physician (19%).
  
  
  CONCLUSIONS
  Increased patient awareness and physician recommendation may increase the use of GDDPs, which may lead to improved compliance with medications, better health outcomes and reduced health care costs.
authors.affiliation: The Dorothy I. Height - Center for Health Equity & Evaluation Research, The University of Texas M D Anderson Cancer Center, Houston, TX, USA. Electronic address: aomoja@aol.com.
authors.forename: Anthony
authors.initials: A
authors.lastname: Omojasola
authors.forename: Mike
authors.initials: M
authors.lastname: Hernandez
authors.forename: Sujit
authors.initials: S
authors.lastname: Sansgiry
authors.forename: Raheem
authors.initials: R
authors.lastname: Paxton
authors.forename: Lovell
authors.initials: L
authors.lastname: Jones
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D001364:Awareness; D003157:Community Pharmacy Services / Q000191:economics*; D016568:Drugs, Generic / Q000191:economics*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D010595:Pharmacists / Q000458:organization & administration; D010820:Physicians / Q000458:organization & administration; D011203:Poverty; D055553:Prescription Drugs / Q000191:economics*; D011306:Prescription Fees; D024382:Professional Role; D011795:Surveys and Questionnaires; D013781:Texas; D055815:Young Adult
chemical_list: D016568:Drugs, Generic; D055553:Prescription Drugs
keywords: Generic drugs; Health care access; Health care cost; Low-income